diff --git a/.gitignore b/.gitignore
index 2985d00..e69de29 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,11 +0,0 @@
-# Ignore everything
-*
-
-# But not these!
-!.gitignore
-!README.md
-!*.py
-!*.template
-# Optional: Keep subdirectories and their Python files
-
-!*/
diff --git a/results-and-plotting/archives/data.zip b/results-and-plotting/archives/data.zip
new file mode 100644
index 0000000..0080931
Binary files /dev/null and b/results-and-plotting/archives/data.zip differ
diff --git a/results-and-plotting/data/data-multi-MPIF-100cflag-complete.csv b/results-and-plotting/data/data-multi-MPIF-100cflag-complete.csv
new file mode 100644
index 0000000..eff25e3
--- /dev/null
+++ b/results-and-plotting/data/data-multi-MPIF-100cflag-complete.csv
@@ -0,0 +1,2289 @@
+benchmark_type,proc_num,msg_size_bytes,repetitions,t_min_usec,t_max_usec,t_avg_usec,mpi_datatype,mpi_red_datatype,mpi_red_op,creation_time,n_nodes,off_cache_flag
+Allreduce,360,0,1000,0.05,0.48,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,4,1000,7.9,12.08,9.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,8,1000,9.17,10.78,10.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,16,1000,7.33,11.5,9.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,32,1000,6.85,10.9,8.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,64,1000,7.64,14.37,10.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,128,1000,8.65,16.94,10.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,256,1000,10.95,17.89,13.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,512,1000,12.0,18.6,13.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,1024,1000,17.67,31.12,28.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,2048,1000,15.97,24.69,18.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,4096,1000,34.97,46.13,37.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,8192,1000,37.27,49.1,40.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,16384,1000,96.82,116.05,106.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,32768,1000,102.17,122.53,108.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,65536,640,101.96,125.18,109.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,131072,320,167.3,205.71,180.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,262144,160,299.49,366.35,324.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,524288,80,684.08,826.91,733.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,1048576,40,1226.05,1363.58,1259.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,2097152,20,2590.39,3423.84,2730.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,360,4194304,10,8859.42,9640.11,9357.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,648,0,1000,0.05,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,4,1000,6.83,30.42,13.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,8,1000,6.31,30.59,13.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,16,1000,7.32,27.8,13.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,32,1000,0.59,22.28,3.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,64,1000,0.6,17.1,3.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,128,1000,0.61,28.38,3.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,256,1000,0.62,18.16,3.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,512,1000,6.65,19.94,10.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,1024,1000,8.08,20.7,11.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,2048,1000,9.06,24.09,12.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,4096,1000,12.07,28.37,15.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,8192,1000,18.36,39.98,22.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,16384,1000,31.32,79.67,38.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,32768,1000,71.84,133.14,79.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,65536,640,46.22,244.66,108.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,131072,320,81.13,402.73,180.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,262144,160,100.93,628.92,336.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,524288,80,164.61,1177.56,617.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,1048576,40,208.87,1438.03,723.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,2097152,20,1418.03,3040.33,1930.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,648,4194304,10,6218.2,44921.19,20217.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,360,0,1000,1.55,1.97,1.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,4,1000,1.89,19.4,4.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,8,1000,2.14,17.2,4.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,16,1000,1.88,16.98,4.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,32,1000,2.13,16.6,4.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,64,1000,2.14,17.58,4.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,128,1000,2.17,18.61,5.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,256,1000,2.14,19.14,6.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,512,1000,2.31,27.06,11.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,1024,1000,6.59,31.56,22.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,2048,1000,34.04,48.94,41.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,4096,1000,33.24,44.21,39.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,8192,1000,66.66,83.92,76.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,16384,1000,93.35,114.41,105.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,32768,1000,189.98,212.74,203.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,65536,640,184.6,348.52,264.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,131072,320,327.78,509.32,421.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,262144,160,688.49,791.7,732.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,524288,80,1041.38,1154.14,1094.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,1048576,40,1433.32,1538.24,1482.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,2097152,20,2004.88,2427.78,2240.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,360,4194304,10,3366.85,3963.22,3666.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,720,0,1000,5.53,12.5,8.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,1,1000,5.99,41.26,10.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,2,1000,5.91,45.51,10.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,4,1000,5.9,42.23,10.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,8,1000,5.47,44.94,9.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,16,1000,5.57,54.97,10.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,32,1000,5.84,69.11,10.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,64,1000,6.03,63.14,10.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,128,1000,6.31,81.59,11.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,256,1000,6.83,840.3,20.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,512,1000,7.55,875.36,19.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,1024,1000,9.34,381.58,17.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,2048,1000,11.46,2783.4,37.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,4096,1000,7.44,883.9,18.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,8192,1000,9.68,2958.95,108.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,16384,1000,14.05,4705.49,44.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,32768,1000,211.67,5361.7,4493.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,65536,640,892.98,9805.59,5154.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,131072,320,670.06,9089.87,5179.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,262144,160,1109.87,17579.6,9834.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,524288,80,2715.78,34353.35,19061.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,1048576,40,12202.2,67800.33,37730.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,720,2097152,20,24013.11,184697.6,72437.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,504,0,1000,2.84,2.97,2.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,1,1000,33.16,39.39,36.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,2,1000,48.51,62.32,54.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,4,1000,45.27,61.29,53.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,8,1000,83.5,104.35,94.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,16,1000,46.75,62.87,56.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,32,1000,68.41,110.13,91.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,64,1000,123.59,186.2,162.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,128,1000,413.6,483.59,445.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,256,1000,635.89,1384.77,967.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,512,1000,409.13,525.87,503.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,1024,1000,705.45,792.23,772.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,2048,1000,1180.04,1729.04,1277.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,4096,1000,1409.76,1516.73,1465.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,8192,1000,2386.34,2568.02,2475.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,16384,1000,5112.08,6015.72,5609.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,32768,1000,9244.89,10326.04,9777.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,65536,640,16460.83,18117.77,17269.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,131072,320,31461.54,36224.91,33904.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,262144,160,70275.66,83645.2,77878.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,524288,80,113628.11,117462.39,115291.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,1048576,40,232987.26,255921.18,242178.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgatherv,504,2097152,20,580705.51,623561.09,602613.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,576,0,1000,0.05,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,4,1000,11.97,19.14,15.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,8,1000,10.8,18.66,15.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,16,1000,11.03,19.67,16.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,32,1000,20.71,35.98,31.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,64,1000,22.88,36.27,28.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,128,1000,12.18,22.6,17.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,256,1000,12.86,26.75,21.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,512,1000,15.63,24.08,21.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,1024,1000,20.87,28.35,26.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,2048,1000,26.8,35.67,32.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,4096,1000,29.92,42.36,36.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,8192,1000,47.01,57.6,52.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,16384,1000,84.69,93.89,89.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,32768,1000,265.06,325.81,286.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,65536,640,96.54,133.17,110.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,131072,320,173.52,219.92,189.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,262144,160,300.25,376.72,324.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,524288,80,678.77,829.39,721.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,1048576,40,1205.93,1288.26,1224.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,2097152,20,2423.94,2603.55,2473.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,576,4194304,10,8605.76,9601.44,9224.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,288,0,1000,1.32,1.59,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,4,1000,1.66,31.75,5.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,8,1000,1.65,26.25,6.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,16,1000,1.68,21.02,5.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,32,1000,1.81,177.47,9.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,64,1000,1.83,33.92,4.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,128,1000,1.84,42.83,6.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,256,1000,2.89,26.06,10.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,512,1000,3.04,30.11,14.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,1024,1000,9.27,28.53,22.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,2048,1000,25.71,38.87,32.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,4096,1000,32.04,43.26,37.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,8192,1000,52.47,64.44,58.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,16384,1000,88.94,109.29,100.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,32768,1000,132.92,246.59,187.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,65536,640,206.86,348.06,276.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,131072,320,287.69,446.38,372.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,262144,160,647.57,739.91,687.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,524288,80,934.87,1025.06,974.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,1048576,40,1383.84,1478.62,1427.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,2097152,20,1977.24,2357.98,2188.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce_scatter,288,4194304,10,3763.88,4265.04,4011.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,144,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,1,1000,32.92,47.1,42.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,2,1000,34.71,41.65,38.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,4,1000,35.23,43.48,39.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,8,1000,40.03,47.73,43.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,16,1000,42.57,53.21,47.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,32,1000,47.48,58.52,53.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,64,1000,56.05,76.32,68.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,128,1000,98.49,128.77,117.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,256,1000,165.71,229.22,204.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,512,1000,310.84,321.01,315.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,1024,1000,513.44,523.13,517.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,2048,1000,984.82,996.27,990.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,4096,1000,1832.26,1858.01,1844.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,8192,1000,4287.04,4421.56,4350.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,16384,1000,7148.46,7193.53,7167.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,32768,887,14389.21,15716.95,15327.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,65536,640,28241.68,28323.72,28282.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,131072,20,64039.87,64747.79,64340.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,262144,20,111021.19,112117.06,111616.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,524288,20,228968.61,230689.07,229913.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,1048576,20,484949.55,487544.72,486258.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,2097152,20,915047.3,920163.58,918221.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,144,4194304,10,1949563.11,1955421.43,1953196.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,432,0,1000,0.05,0.1,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,4,1000,2.6,7.13,3.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,8,1000,2.96,11.31,4.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,16,1000,5.38,11.47,5.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,32,1000,0.56,11.23,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,64,1000,0.57,11.74,1.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,128,1000,0.58,11.9,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,256,1000,0.61,13.8,1.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,512,1000,4.98,13.63,6.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,1024,1000,5.13,11.95,6.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,2048,1000,7.62,15.7,8.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,4096,1000,9.33,19.8,10.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,8192,1000,16.66,31.22,17.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,16384,1000,32.8,60.61,34.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,32768,1000,48.76,253.05,96.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,65536,640,67.68,218.33,117.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,131072,320,148.34,398.04,236.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,262144,160,85.95,1283.21,438.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,524288,80,163.47,1064.1,569.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,1048576,40,214.23,1370.65,732.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,2097152,20,1387.32,3111.89,1951.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,432,4194304,10,6658.61,43111.72,18884.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,144,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,1,1000,0.45,10.08,1.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,2,1000,0.45,10.49,1.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,4,1000,0.46,10.52,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,8,1000,0.41,10.13,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,16,1000,0.41,9.61,1.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,32,1000,0.4,10.12,1.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,64,1000,0.42,11.52,1.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,128,1000,0.44,14.7,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,256,1000,0.46,22.58,1.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,512,1000,0.68,34.59,2.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,1024,1000,0.8,62.86,3.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,2048,1000,1.25,150.47,6.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,4096,1000,2.02,183.27,6.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,8192,1000,3.67,301.41,8.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,16384,1000,7.26,518.99,13.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,32768,1000,13.97,884.91,23.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,65536,640,45.6,1067.75,546.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,131072,320,94.28,2234.96,1078.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,262144,160,169.63,3662.34,1847.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,524288,80,333.69,6924.59,3668.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,1048576,40,236.79,18144.16,9205.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,2097152,20,4802.25,37049.49,22008.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,144,4194304,10,12243.75,58555.47,36454.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,720,0,1000,0.03,0.61,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,1,1000,2.85,9.85,6.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,2,1000,3.82,8.54,5.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,4,1000,2.83,9.78,6.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,8,1000,3.55,7.28,5.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,16,1000,1.83,5.47,3.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,32,1000,1.86,5.58,3.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,64,1000,3.71,11.73,5.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,128,1000,3.82,8.41,5.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,256,1000,4.76,10.0,7.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,512,1000,4.5,10.8,8.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,1024,1000,7.4,25.65,22.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,2048,1000,9.14,26.99,24.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,4096,1000,10.79,22.95,18.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,8192,1000,16.04,40.37,31.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,16384,1000,89.75,105.44,98.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,32768,1000,43.62,62.17,52.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,65536,640,49.33,83.83,69.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,131072,320,93.05,144.46,122.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,262144,160,183.18,253.78,226.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,524288,80,351.37,488.02,433.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,1048576,40,852.68,895.58,875.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,2097152,20,2616.82,3008.78,2820.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Bcast,720,4194304,10,3129.14,5516.73,5102.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,648,0,1000,2.49,2.76,2.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,4,1000,2.83,30.2,8.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,8,1000,3.27,30.37,8.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,16,1000,2.82,31.15,8.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,32,1000,2.83,42.68,8.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,64,1000,2.85,46.44,9.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,128,1000,2.87,34.98,9.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,256,1000,2.91,49.43,11.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,512,1000,3.06,100.8,27.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,1024,1000,3.23,48.65,21.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,2048,1000,9.77,77.04,52.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,4096,1000,72.24,108.83,88.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,8192,1000,55.82,91.1,73.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,16384,1000,100.37,146.39,126.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,32768,1000,224.81,252.46,242.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,65536,640,203.05,465.63,331.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,131072,320,322.52,642.99,480.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,262144,160,656.07,989.15,821.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,524288,80,1395.64,1552.19,1472.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,1048576,40,1692.19,1845.54,1780.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,2097152,20,3014.95,3179.43,3111.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,648,4194304,10,3945.67,4795.41,4440.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,432,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,1,1000,1.8,8.48,5.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,2,1000,2.03,9.62,5.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,4,1000,2.85,12.58,7.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,8,1000,2.75,10.27,6.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,16,1000,3.17,10.67,7.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,32,1000,5.15,15.03,10.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,64,1000,8.04,18.82,13.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,128,1000,13.6,27.14,20.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,256,1000,24.3,53.14,37.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,512,1000,45.24,79.45,63.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,1024,1000,36.57,79.6,62.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,2048,1000,18.15,133.42,89.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,4096,1000,7.3,246.61,148.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,8192,1000,33.19,483.37,284.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,16384,1000,41.31,954.63,538.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,32768,1000,27.82,1895.11,872.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,65536,640,30.08,4094.57,1284.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,131072,320,52.84,4559.98,3072.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,262144,160,199.97,7748.94,4239.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,524288,80,313.64,20074.45,9932.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,1048576,40,812.46,41586.54,22967.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,2097152,20,8314.1,73655.42,54760.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatter,432,4194304,10,10966.2,168694.69,121885.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,648,0,1000,3.56,4.23,3.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,1,1000,37.55,43.33,40.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,2,1000,40.87,47.99,44.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,4,1000,64.65,75.83,69.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,8,1000,204.84,911.26,489.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,16,1000,137.82,174.62,161.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,32,1000,116.53,136.27,127.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,64,1000,372.5,705.5,399.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,128,1000,530.89,608.5,566.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,256,1000,635.68,687.9,658.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,512,1000,528.71,686.3,649.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,1024,1000,1173.6,1797.16,1225.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,2048,1000,1780.4,2793.56,2340.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,4096,1000,1871.47,1964.62,1916.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,8192,1000,3397.62,4149.57,3782.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,16384,1000,5955.97,6336.18,6146.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,32768,1000,11816.67,13380.55,12533.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,65536,640,25209.74,28778.76,27323.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,131072,320,40596.05,44677.13,42725.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,262144,160,78631.56,88215.27,83866.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,524288,64,208395.09,217488.78,212956.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,1048576,40,364839.53,391330.99,377284.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgatherv,648,2097152,20,730249.44,783152.56,744174.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,144,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,1,1000,9.47,13.6,10.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,2,1000,9.72,20.07,11.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,4,1000,12.02,23.41,14.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,8,1000,14.84,26.74,22.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,16,1000,12.84,20.07,15.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,32,1000,14.01,27.2,19.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,64,1000,16.72,38.58,26.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,128,1000,24.74,65.92,46.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,256,1000,144.82,179.88,168.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,512,1000,72.42,233.17,161.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,1024,1000,152.95,165.78,159.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,2048,1000,223.29,257.11,240.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,4096,1000,348.12,406.35,377.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,8192,1000,580.82,681.03,627.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,16384,1000,1167.57,1863.63,1607.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,32768,1000,2071.39,2654.86,2377.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,65536,640,3871.81,5022.38,4485.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,131072,320,7711.08,9692.74,8807.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,262144,160,14923.84,19219.51,17258.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,524288,80,30686.55,33747.03,32055.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,1048576,40,76164.1,82576.69,80488.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,2097152,20,173342.0,256306.63,241444.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,144,4194304,10,457617.0,749715.28,696336.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,432,0,1000,3.82,10.16,7.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,1,1000,4.89,32.62,9.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,2,1000,5.06,36.01,10.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,4,1000,5.08,42.83,10.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,8,1000,4.05,34.27,8.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,16,1000,4.19,34.26,8.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,32,1000,4.41,39.16,8.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,64,1000,4.31,45.69,9.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,128,1000,5.2,80.49,11.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,256,1000,5.97,167.53,14.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,512,1000,5.85,161.48,13.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,1024,1000,7.14,238.92,16.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,2048,1000,7.35,375.77,18.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,4096,1000,7.04,518.45,22.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,8192,1000,102.99,961.38,779.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,16384,1000,144.02,1620.37,1333.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,32768,1000,222.16,3551.15,2554.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,65536,640,366.45,3316.19,1941.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,131072,320,1568.84,5688.67,3426.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,262144,160,3132.86,11060.17,6548.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,524288,80,5880.95,21472.32,12649.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,1048576,40,12145.43,42819.3,25249.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,2097152,20,24528.4,116774.64,50813.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,432,4194304,10,27994.51,393921.13,74070.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,0,1000,1.85,2.0,1.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,4,1000,2.16,23.87,4.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,8,1000,2.2,23.59,4.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,16,1000,2.19,23.43,4.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,32,1000,2.54,24.65,5.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,64,1000,2.23,24.62,5.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,128,1000,2.23,25.43,5.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,256,1000,2.26,33.18,8.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,512,1000,2.61,29.84,11.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,1024,1000,3.24,32.92,19.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,2048,1000,24.94,38.59,33.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,4096,1000,31.81,48.36,42.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,8192,1000,268.69,789.58,409.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,16384,1000,118.73,152.46,143.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,32768,1000,133.29,301.49,211.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,65536,640,201.41,376.81,284.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,131072,320,330.59,547.34,436.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,262144,160,722.46,837.78,774.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,524288,80,1115.44,1233.22,1175.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,1048576,40,1509.85,1625.26,1569.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,2097152,20,2218.93,2688.55,2480.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce_scatter,432,4194304,10,3452.04,4099.62,3780.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,1,1000,0.48,23.59,2.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,2,1000,0.49,23.64,2.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,4,1000,0.48,32.82,2.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,8,1000,0.45,33.65,2.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,16,1000,0.45,36.0,2.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,32,1000,0.43,36.27,2.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,64,1000,0.46,39.08,2.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,128,1000,0.49,67.74,5.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,256,1000,0.52,83.28,4.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,512,1000,0.75,113.31,3.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,1024,1000,0.79,215.21,5.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,2048,1000,1.05,242.77,8.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,4096,1000,1.34,389.45,13.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,8192,1000,2.1,761.35,25.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,16384,1000,3.92,1491.42,45.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,32768,1000,6.39,2794.5,89.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,65536,640,12.49,3033.77,1739.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,131072,320,23.98,5586.92,3088.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,262144,160,42.28,10699.32,5840.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,524288,80,92.91,21105.81,11411.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,1048576,40,235.77,42552.36,23088.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,2097152,20,4769.37,109336.26,47691.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,432,4194304,10,16070.09,405886.6,76342.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,648,0,1000,5.1,12.86,8.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,1,1000,5.94,44.23,10.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,2,1000,5.74,40.33,10.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,4,1000,5.96,41.94,10.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,8,1000,5.51,40.33,9.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,16,1000,5.53,41.49,9.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,32,1000,5.81,52.56,9.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,64,1000,6.18,61.23,10.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,128,1000,6.14,74.25,10.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,256,1000,6.59,127.22,12.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,512,1000,7.38,465.92,16.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,1024,1000,8.67,337.14,15.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,2048,1000,8.21,522.89,18.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,4096,1000,7.16,864.94,21.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,8192,1000,8.47,1327.54,25.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,16384,1000,11.63,3102.42,41.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,32768,1000,278.94,5319.31,4288.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,65536,640,649.24,11406.43,6402.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,131072,320,2733.56,13095.96,7494.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,262144,160,2073.03,16131.58,9201.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,524288,80,5084.78,31160.39,17534.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,1048576,40,12124.95,61445.34,34475.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gatherv,648,2097152,20,23919.6,172172.33,66600.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,576,0,1000,2.24,2.43,2.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,4,1000,2.93,24.07,7.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,8,1000,2.94,27.2,8.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,16,1000,2.56,33.39,7.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,32,1000,2.56,26.52,7.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,64,1000,2.95,29.16,8.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,128,1000,3.0,30.12,9.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,256,1000,2.62,32.48,11.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,512,1000,4.72,39.54,14.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,1024,1000,4.96,66.43,32.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,2048,1000,20.27,58.27,46.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,4096,1000,48.27,64.92,54.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,8192,1000,98.09,112.66,104.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,16384,1000,123.89,137.84,129.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,32768,1000,226.39,247.3,239.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,65536,640,213.0,437.37,320.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,131072,320,315.7,589.62,448.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,262144,160,1114.22,1307.42,1168.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,524288,80,1302.94,1498.77,1373.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,1048576,40,1644.22,1781.56,1718.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,2097152,20,2946.94,3082.96,3020.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce_scatter,576,4194304,10,3846.42,4619.45,4291.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,504,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,1,1000,2.46,12.7,7.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,2,1000,1.92,8.04,5.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,4,1000,1.86,7.87,5.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,8,1000,1.89,8.48,5.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,16,1000,1.7,7.79,4.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,32,1000,1.96,8.34,5.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,64,1000,1.95,8.4,5.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,128,1000,1.99,8.67,6.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,256,1000,2.16,10.36,7.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,512,1000,2.11,13.44,9.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,1024,1000,1.54,18.23,14.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,2048,1000,5.08,27.49,21.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,4096,1000,7.81,30.81,21.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,8192,1000,13.69,47.41,34.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,16384,1000,84.21,164.56,107.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,32768,1000,36.17,110.58,69.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,65536,640,61.31,91.95,77.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,131072,320,88.55,137.53,116.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,262144,160,177.51,244.41,218.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,524288,80,330.51,412.87,394.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,1048576,40,765.08,948.41,909.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,2097152,20,1639.93,1881.94,1818.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Bcast,504,4194304,10,3527.42,5523.3,5024.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,720,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,1,1000,137.79,146.74,142.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,2,1000,164.64,186.51,177.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,4,1000,158.02,175.59,165.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,8,1000,183.52,205.41,193.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,16,1000,208.22,226.71,217.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,32,1000,327.45,356.81,342.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,64,1000,383.71,393.33,389.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,128,1000,761.08,773.73,767.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,256,1000,1587.73,2073.31,1643.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,512,1000,2488.59,2522.79,2506.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,1024,1000,5262.94,5277.78,5269.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,2048,1000,11004.94,11102.85,11062.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,4096,1000,24396.56,24501.06,24473.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,8192,1000,43271.43,43358.15,43326.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,16384,796,82111.46,82345.16,82235.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,32768,378,161728.6,162252.05,162044.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,65536,14,1913407.01,1956651.46,1939093.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,131072,9,711125.0,715714.54,712996.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,262144,9,1191167.7,1195260.15,1193383.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,524288,9,2564544.72,2576355.26,2569866.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,720,1048576,1,5389193.85,5389255.8,5389226.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,576,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,1,1000,27.73,64.91,47.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,2,1000,67.13,104.6,83.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,4,1000,68.86,124.72,92.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,8,1000,33.86,47.44,42.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,16,1000,80.58,249.49,182.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,32,1000,91.19,117.88,110.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,64,1000,165.65,219.0,204.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,128,1000,447.22,517.04,479.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,256,1000,558.27,607.57,582.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,512,1000,955.72,1734.31,1364.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,1024,1000,1171.41,2000.52,1576.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,2048,1000,989.22,1018.25,1010.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,4096,1000,1710.24,2405.36,2099.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,8192,1000,3111.68,4147.62,3619.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,16384,1000,5370.96,6103.38,5765.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,32768,1000,9925.02,10758.75,10364.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,65536,640,19273.12,21593.73,20438.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,131072,320,42460.3,48055.71,45647.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,262144,160,69030.49,75237.84,72331.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,524288,80,130845.03,139778.12,135759.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,1048576,40,420570.58,523459.94,499942.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,576,2097152,20,1152137.6,1517550.26,1440388.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allreduce,432,0,1000,0.05,0.07,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,4,1000,14.95,20.13,17.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,8,1000,8.87,9.78,9.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,16,1000,21.08,26.96,23.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,32,1000,7.03,14.5,9.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,64,1000,8.65,16.89,10.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,128,1000,8.96,17.65,11.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,256,1000,11.53,19.2,13.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,512,1000,13.67,19.79,17.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,1024,1000,13.02,20.3,15.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,2048,1000,15.8,26.83,18.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,4096,1000,22.46,31.7,25.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,8192,1000,175.22,400.21,182.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,16384,1000,102.14,184.17,110.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,32768,1000,136.59,156.73,145.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,65536,640,142.18,174.93,153.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,131072,320,172.63,207.61,185.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,262144,160,306.02,376.92,332.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,524288,80,705.27,841.64,753.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,1048576,40,2481.17,3091.06,2754.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,2097152,20,3595.03,6068.11,4870.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,432,4194304,10,9028.61,9968.77,9607.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Reduce,144,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,4,1000,3.71,6.64,4.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,8,1000,3.65,6.66,4.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,16,1000,3.78,6.91,4.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,32,1000,0.56,9.96,1.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,64,1000,4.36,7.48,5.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,128,1000,0.59,11.02,1.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,256,1000,5.02,8.85,5.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,512,1000,3.32,11.34,6.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,1024,1000,4.53,10.12,5.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,2048,1000,7.23,12.55,7.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,4096,1000,9.65,16.64,10.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,8192,1000,16.18,24.12,16.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,16384,1000,29.56,40.03,30.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,32768,1000,72.1,96.57,76.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,65536,640,81.64,199.63,137.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,131072,320,116.58,278.8,196.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,262144,160,73.4,377.87,244.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,524288,80,155.47,757.1,475.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,1048576,40,232.33,1032.01,653.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,2097152,20,1393.11,2727.63,2104.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce,144,4194304,10,6973.06,30927.68,19038.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,504,0,1000,3.99,17.91,10.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,1,1000,2.62,40.36,6.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,2,1000,2.39,46.01,7.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,4,1000,3.03,45.88,7.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,8,1000,3.65,623.69,55.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,16,1000,2.37,94.83,10.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,32,1000,2.7,55.58,7.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,64,1000,3.19,91.23,8.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,128,1000,2.14,71.9,7.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,256,1000,3.06,113.5,8.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,512,1000,4.28,182.14,10.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,1024,1000,3.73,308.95,13.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,2048,1000,8.76,1302.02,41.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,4096,1000,3.99,600.84,18.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,8192,1000,107.95,1092.96,912.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,16384,1000,144.65,1879.22,1580.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,32768,1000,176.3,3726.3,2946.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,65536,640,397.13,3624.03,2192.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,131072,320,1444.38,6660.11,3968.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,262144,160,2988.06,12646.53,7393.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,524288,80,5286.97,24659.03,14215.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,1048576,40,12147.45,49023.21,28303.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gatherv,504,2097152,20,22796.05,171764.67,53231.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,576,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,1,1000,0.48,24.85,3.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,2,1000,0.49,25.45,3.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,4,1000,0.48,27.9,3.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,8,1000,0.49,32.04,3.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,16,1000,0.49,86.02,12.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,32,1000,0.5,46.09,3.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,64,1000,0.51,76.56,8.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,128,1000,0.54,71.36,4.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,256,1000,0.58,979.26,91.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,512,1000,0.74,146.39,5.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,1024,1000,0.8,295.89,9.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,2048,1000,1.04,342.49,10.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,4096,1000,1.35,609.09,15.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,8192,1000,2.18,1210.92,29.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,16384,1000,3.88,3179.55,77.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,32768,1000,6.18,6470.03,370.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,65536,640,11.61,4970.41,2185.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,131072,320,22.18,10288.69,3989.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,262144,160,35.36,13830.23,7574.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,524288,80,73.03,27544.97,14587.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,1048576,40,218.82,55022.04,29766.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gather,576,2097152,20,4504.09,143125.92,59644.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,288,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,1,1000,2.34,11.96,4.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,2,1000,1.18,4.51,2.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,4,1000,1.06,4.14,2.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,8,1000,1.07,4.76,2.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,16,1000,1.04,4.5,2.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,32,1000,1.09,4.52,2.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,64,1000,2.84,6.3,4.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,128,1000,2.87,6.74,4.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,256,1000,3.3,7.96,5.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,512,1000,2.76,8.87,6.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,1024,1000,3.8,20.41,17.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,2048,1000,8.64,26.08,24.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,4096,1000,7.97,19.25,14.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,8192,1000,12.84,30.91,23.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,16384,1000,81.43,91.22,86.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,32768,1000,26.69,43.04,33.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,65536,640,50.49,69.38,58.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,131072,320,90.62,124.27,103.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,262144,160,180.92,224.85,197.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,524288,80,331.53,366.18,353.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,1048576,40,758.79,800.98,786.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,2097152,20,1567.1,1610.37,1589.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,288,4194304,10,2806.78,5186.16,4526.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,0,1000,3.35,9.19,5.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,1,1000,9.78,14.89,11.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,2,1000,11.57,17.96,13.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,4,1000,11.93,18.6,14.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,8,1000,10.01,15.73,12.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,16,1000,9.96,16.5,12.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,32,1000,10.7,17.62,13.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,64,1000,11.5,20.31,15.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,128,1000,13.65,24.0,17.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,256,1000,16.27,31.69,23.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,512,1000,19.61,43.81,33.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,1024,1000,23.14,60.92,47.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,2048,1000,31.75,96.49,73.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,4096,1000,17.09,177.87,107.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,8192,1000,43.61,322.46,193.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,16384,1000,50.26,533.01,331.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,32768,1000,35.04,773.78,552.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,65536,640,46.85,1537.96,1128.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,131072,320,192.04,4441.34,2537.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,262144,160,220.72,7251.34,2557.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,524288,80,265.9,11287.82,8103.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,1048576,40,525.09,18590.49,12940.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,2097152,20,1482.67,37198.48,29152.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatterv,288,4194304,10,19034.78,91275.64,69079.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,504,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,1,1000,2.04,8.13,4.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,2,1000,2.82,10.39,6.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,4,1000,2.94,10.18,6.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,8,1000,2.92,8.88,6.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,16,1000,3.4,9.89,6.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,32,1000,5.58,13.36,9.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,64,1000,8.72,18.99,13.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,128,1000,14.8,29.61,23.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,256,1000,72.69,460.13,90.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,512,1000,72.78,123.45,94.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,1024,1000,89.17,138.14,109.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,2048,1000,16.22,158.15,104.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,4096,1000,8.47,303.56,183.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,8192,1000,36.46,599.58,359.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,16384,1000,49.04,1169.11,692.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,32768,1000,26.92,2261.88,1052.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,65536,640,30.46,3870.67,1409.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,131072,320,66.53,5379.19,3866.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,262144,160,176.07,9284.4,5088.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,524288,80,296.35,18528.38,12144.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,1048576,40,1782.14,37007.72,28182.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatter,504,2097152,20,7898.91,90228.43,68049.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,648,0,1000,0.05,0.09,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,4,1000,9.18,12.89,10.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,8,1000,10.28,13.9,11.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,16,1000,8.39,13.34,10.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,32,1000,8.17,13.17,9.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,64,1000,9.88,18.21,13.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,128,1000,10.04,19.75,12.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,256,1000,17.09,27.16,19.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,512,1000,14.52,22.51,16.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,1024,1000,22.57,38.41,33.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,2048,1000,25.5,34.17,29.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,4096,1000,41.46,62.54,52.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,8192,1000,47.58,62.31,52.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,16384,1000,478.79,1223.43,708.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,32768,1000,232.68,265.43,247.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,65536,640,169.56,202.25,180.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,131072,320,185.01,230.74,200.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,262144,160,318.0,390.86,341.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,524288,80,693.75,845.17,742.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,1048576,40,1398.58,1832.87,1457.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,2097152,20,2536.63,2830.88,2619.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,648,4194304,10,9438.34,10571.44,10016.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allreduce,288,0,1000,0.05,0.07,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,4,1000,6.56,7.25,6.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,8,1000,5.22,6.7,5.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,16,1000,6.47,8.37,7.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,32,1000,7.13,9.23,7.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,64,1000,7.47,11.71,9.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,128,1000,9.39,16.22,12.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,256,1000,9.44,14.85,10.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,512,1000,12.97,15.86,14.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,1024,1000,14.4,23.6,21.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,2048,1000,13.65,19.32,14.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,4096,1000,18.67,23.48,19.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,8192,1000,32.91,38.35,34.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,16384,1000,73.68,83.25,76.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,32768,1000,61.91,81.76,69.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,65536,640,91.54,111.23,98.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,131072,320,162.88,199.21,175.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,262144,160,282.64,346.06,303.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,524288,80,595.21,725.33,631.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,1048576,40,1172.67,1391.75,1206.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,2097152,20,2240.82,2697.96,2324.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,288,4194304,10,9151.9,10199.49,9811.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,216,0,1000,0.04,0.3,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,1,1000,2.11,8.99,4.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,2,1000,2.17,20.93,5.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,4,1000,2.58,6.51,4.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,8,1000,2.1,5.7,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,16,1000,2.89,7.2,5.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,32,1000,3.55,8.26,5.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,64,1000,4.86,10.59,7.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,128,1000,8.97,15.92,13.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,256,1000,9.3,18.31,13.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,512,1000,13.13,26.82,21.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,1024,1000,12.07,40.52,29.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,2048,1000,23.06,63.73,51.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,4096,1000,14.76,134.13,83.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,8192,1000,33.73,321.8,177.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,16384,1000,43.97,595.55,318.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,32768,1000,53.09,1056.84,562.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,65536,640,36.68,836.49,457.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,131072,320,80.82,2325.57,1421.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,262144,160,133.82,3123.63,2008.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,524288,80,286.09,6214.22,4182.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,1048576,40,500.42,12390.86,8290.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,2097152,20,3688.33,24781.97,18514.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatter,216,4194304,10,20114.28,60127.63,45769.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,432,0,1000,2.48,2.63,2.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,1,1000,30.0,40.41,35.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,2,1000,42.01,57.62,48.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,4,1000,42.17,64.53,51.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,8,1000,91.85,134.26,109.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,16,1000,45.08,59.04,53.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,32,1000,64.71,90.9,80.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,64,1000,117.37,163.39,144.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,128,1000,340.04,401.18,369.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,256,1000,406.47,442.59,426.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,512,1000,596.99,684.37,641.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,1024,1000,480.37,496.34,488.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,2048,1000,729.58,783.0,759.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,4096,1000,1191.65,1278.16,1237.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,8192,1000,2024.7,2173.18,2100.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,16384,1000,3715.06,4045.16,3887.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,32768,1000,7379.65,8633.72,8074.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,65536,640,17164.9,19984.35,18649.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,131072,320,28062.67,31281.94,29716.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,262144,160,50978.5,55232.72,53376.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,524288,80,90269.52,92892.65,91576.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,1048576,40,209399.66,217020.95,211149.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,2097152,20,571955.39,615925.77,595655.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgatherv,432,4194304,10,1073579.56,1174502.45,1115068.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gatherv,288,0,1000,3.15,9.08,5.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,1,1000,2.31,25.69,6.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,2,1000,2.85,30.02,7.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,4,1000,2.89,30.25,7.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,8,1000,2.49,27.76,6.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,16,1000,2.52,29.08,6.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,32,1000,2.26,30.99,6.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,64,1000,2.31,35.72,6.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,128,1000,2.33,41.53,6.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,256,1000,2.55,55.65,7.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,512,1000,3.33,107.03,9.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,1024,1000,3.57,179.34,11.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,2048,1000,3.9,343.5,22.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,4096,1000,3.91,346.69,23.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,8192,1000,97.66,634.77,476.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,16384,1000,133.81,1062.69,808.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,32768,1000,207.22,1927.6,1470.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,65536,640,413.09,2344.7,1462.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,131072,320,749.26,4167.67,2521.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,262144,160,4306.96,13866.45,7395.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,524288,80,4698.37,15950.11,9882.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,1048576,40,12104.07,30514.48,19297.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,2097152,20,24942.23,61749.91,39356.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gatherv,288,4194304,10,31397.38,290100.61,58184.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allreduce,504,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,4,1000,16.5,36.6,31.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,8,1000,13.09,17.74,16.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,16,1000,12.17,17.51,14.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,32,1000,14.63,16.7,15.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,64,1000,11.55,16.78,13.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,128,1000,12.22,18.18,13.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,256,1000,13.54,20.3,15.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,512,1000,14.3,19.72,15.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,1024,1000,20.93,36.85,31.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,2048,1000,19.96,28.05,21.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,4096,1000,26.83,37.8,29.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,8192,1000,41.75,52.72,45.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,16384,1000,65.71,80.87,71.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,32768,1000,107.53,128.77,116.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,65536,640,141.75,175.57,154.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,131072,320,183.52,221.34,200.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,262144,160,668.9,977.45,738.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,524288,80,989.52,1377.11,1089.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,1048576,40,1783.21,2094.15,2003.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,2097152,20,2552.76,3197.24,2780.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,504,4194304,10,9241.0,10160.02,9833.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,144,0,1000,5.53,11.4,8.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,1,1000,11.14,16.86,13.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,2,1000,11.2,17.01,14.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,4,1000,11.32,17.78,14.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,8,1000,9.56,15.15,12.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,16,1000,9.89,16.68,13.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,32,1000,9.92,15.8,12.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,64,1000,10.77,17.65,13.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,128,1000,11.9,23.64,17.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,256,1000,12.06,23.95,17.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,512,1000,12.19,34.8,23.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,1024,1000,15.75,49.5,34.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,2048,1000,18.81,82.68,57.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,4096,1000,15.44,193.99,122.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,8192,1000,26.9,300.76,157.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,16384,1000,33.14,449.25,210.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,32768,1000,56.06,829.09,401.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,65536,640,77.8,2442.47,1471.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,131072,320,77.99,859.56,632.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,262144,160,324.5,7159.04,3931.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,524288,80,326.66,3353.51,1823.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,1048576,40,3435.79,6304.27,5984.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,2097152,20,926.06,12562.56,8392.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatterv,144,4194304,10,20508.57,39191.16,30726.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Alltoall,216,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,1,1000,47.15,50.99,49.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,2,1000,50.5,55.99,52.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,4,1000,50.9,55.82,53.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,8,1000,54.44,60.48,57.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,16,1000,65.77,74.22,70.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,32,1000,81.79,98.26,90.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,64,1000,105.82,138.12,124.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,128,1000,165.54,172.27,168.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,256,1000,337.86,348.33,341.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,512,1000,587.26,604.58,596.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,1024,1000,1018.28,1031.73,1024.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,2048,1000,1886.4,1896.14,1890.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,4096,1000,4346.29,4396.12,4384.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,8192,1000,8477.26,8523.84,8490.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,16384,1000,17076.45,17156.87,17126.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,32768,1000,31421.81,31523.89,31463.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,65536,492,63211.13,63383.34,63278.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,131072,15,140462.67,141298.41,140937.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,262144,15,259135.01,260340.15,259856.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,524288,15,533181.2,535899.67,534854.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,1048576,15,1070778.54,1075610.93,1073706.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,2097152,15,2064790.4,2072750.91,2069893.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,216,4194304,10,4258611.43,4275017.8,4268469.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,720,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,1,1000,0.4,13.26,1.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,2,1000,0.4,13.15,1.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,4,1000,0.42,15.15,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,8,1000,0.41,19.73,1.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,16,1000,0.41,18.31,1.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,32,1000,0.42,23.23,1.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,64,1000,0.43,29.04,1.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,128,1000,0.46,42.21,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,256,1000,0.52,114.93,2.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,512,1000,0.88,143.06,3.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,1024,1000,1.03,213.25,5.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,2048,1000,1.44,389.22,9.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,4096,1000,2.56,663.82,15.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,8192,1000,3.96,1594.23,30.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,16384,1000,8.49,2753.66,53.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,32768,1000,15.58,4963.26,102.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,65536,640,39.75,4768.14,2735.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,131072,320,86.0,10399.16,4956.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,262144,160,159.56,17297.25,9435.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,524288,80,322.16,35799.85,18584.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,1048576,40,254.03,67690.22,36442.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,720,2097152,20,8075.51,210108.78,70853.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,360,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,1,1000,12.65,18.32,14.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,2,1000,15.08,21.65,18.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,4,1000,18.85,26.43,21.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,8,1000,25.8,33.6,29.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,16,1000,30.57,40.88,36.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,32,1000,51.33,69.8,61.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,64,1000,99.83,131.06,116.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,128,1000,283.51,330.22,307.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,256,1000,333.99,357.19,345.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,512,1000,455.45,508.06,482.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,1024,1000,395.78,407.56,401.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,2048,1000,775.29,1337.75,1123.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,4096,1000,1035.37,1121.12,1079.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,8192,1000,1723.83,1878.49,1806.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,16384,1000,3166.85,3532.85,3356.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,32768,1000,6587.58,7700.61,7167.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,65536,640,11719.09,13412.65,12616.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,131072,320,21804.43,24028.16,23000.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,262144,160,42923.67,50890.96,46806.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,524288,80,89203.53,92023.8,90442.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,1048576,40,245744.6,285799.87,274928.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,2097152,20,693936.63,832033.71,795122.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,360,4194304,10,1970981.05,2610468.42,2435001.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,576,0,1000,0.03,0.04,0.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,1,1000,1.47,26.91,4.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,2,1000,1.6,7.13,3.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,4,1000,3.6,6.86,4.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,8,1000,2.59,11.69,6.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,16,1000,3.65,28.95,4.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,32,1000,3.51,6.55,4.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,64,1000,3.76,9.05,4.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,128,1000,3.94,8.77,5.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,256,1000,4.39,8.66,5.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,512,1000,3.84,10.93,5.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,1024,1000,5.74,25.11,22.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,2048,1000,8.36,28.9,24.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,4096,1000,7.96,24.69,19.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,8192,1000,13.17,38.3,29.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,16384,1000,83.35,103.45,96.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,32768,1000,33.28,62.87,46.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,65536,640,53.1,81.8,66.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,131072,320,101.65,140.3,118.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,262144,160,184.57,248.6,221.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,524288,80,417.19,492.29,450.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,1048576,40,830.93,885.89,871.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,2097152,20,1628.5,1709.07,1667.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,576,4194304,10,3177.71,5583.49,5096.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Bcast,360,0,1000,0.03,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,1,1000,2.39,5.36,4.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,2,1000,2.69,5.66,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,4,1000,3.17,6.26,4.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,8,1000,1.53,5.76,3.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,16,1000,3.08,5.98,4.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,32,1000,1.25,5.62,3.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,64,1000,3.2,6.32,4.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,128,1000,3.23,6.74,5.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,256,1000,3.65,7.74,6.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,512,1000,1.98,9.1,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,1024,1000,4.22,23.6,21.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,2048,1000,7.59,28.39,25.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,4096,1000,6.8,24.01,18.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,8192,1000,11.01,36.95,28.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,16384,1000,84.29,107.08,95.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,32768,1000,27.0,64.38,45.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,65536,640,43.73,82.57,64.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,131072,320,83.71,136.64,115.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,262144,160,182.98,240.51,210.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,524288,80,274.29,445.61,379.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,1048576,40,631.8,958.61,879.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,2097152,20,1464.32,1887.64,1779.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,360,4194304,10,3152.16,5704.0,4807.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allreduce,720,0,1000,0.05,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,4,1000,12.46,23.91,18.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,8,1000,12.76,23.9,18.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,16,1000,16.72,32.55,26.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,32,1000,13.44,26.85,18.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,64,1000,14.68,26.92,20.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,128,1000,41.19,138.6,103.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,256,1000,41.44,64.79,47.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,512,1000,22.28,35.9,29.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,1024,1000,19.64,31.47,25.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,2048,1000,25.78,37.65,31.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,4096,1000,35.67,52.92,43.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,8192,1000,218.85,719.42,428.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,16384,1000,104.79,166.74,135.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,32768,1000,441.0,1002.16,690.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,65536,640,205.03,235.44,220.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,131072,320,300.89,341.44,317.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,262144,160,331.34,395.58,355.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,524288,80,720.4,863.17,770.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,1048576,40,1284.17,1412.72,1325.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,2097152,20,2588.77,2902.52,2702.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allreduce,720,4194304,10,9451.28,10364.12,10007.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,432,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,1,1000,376.72,420.92,397.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,2,1000,96.95,107.82,103.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,4,1000,91.31,104.1,99.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,8,1000,106.84,127.78,117.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,16,1000,113.37,131.44,122.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,32,1000,164.02,193.63,180.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,64,1000,221.79,233.54,228.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,128,1000,410.05,431.88,415.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,256,1000,983.75,1402.17,1066.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,512,1000,1416.02,1434.77,1424.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,1024,1000,2917.58,2930.16,2924.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,2048,1000,5091.33,5103.65,5096.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,4096,1000,9594.41,9608.77,9600.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,8192,1000,25205.67,25284.54,25241.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,16384,1000,39790.07,39883.11,39840.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,32768,527,79447.36,79634.45,79513.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,65536,34,649514.31,673335.52,665031.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,131072,34,342367.78,342751.21,342584.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,262144,34,655343.83,657809.9,656272.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,524288,34,1271040.48,1274742.65,1272911.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,1048576,16,2574237.41,2585984.7,2582004.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,432,2097152,9,5139885.84,5183680.73,5166847.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Alltoall,360,0,1000,0.04,0.29,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,1,1000,74.93,111.11,78.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,2,1000,86.79,99.74,91.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,4,1000,78.64,84.79,81.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,8,1000,88.78,102.41,94.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,16,1000,96.62,105.44,100.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,32,1000,143.58,160.72,152.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,64,1000,227.09,259.76,245.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,128,1000,322.68,329.63,326.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,256,1000,645.19,656.1,650.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,512,1000,1139.04,1149.18,1144.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,1024,1000,2971.99,2991.12,2979.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,2048,1000,4045.93,4052.8,4048.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,4096,1000,8387.69,8412.52,8392.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,8192,1000,17272.93,17316.81,17291.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,16384,1000,32208.54,32338.42,32291.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,32768,595,68336.16,68544.54,68425.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,65536,411,132231.2,132427.61,132342.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,131072,12,263856.01,264998.98,264522.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,262144,12,544223.81,546130.13,545214.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,524288,12,1080890.73,1085097.51,1083482.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,1048576,12,2101857.18,2111376.74,2106588.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,360,2097152,10,4325460.09,4355276.05,4342259.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce_scatter,216,0,1000,1.11,2.04,1.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,4,1000,1.44,11.29,2.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,8,1000,1.43,11.02,2.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,16,1000,1.43,11.79,3.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,32,1000,1.45,11.44,3.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,64,1000,1.47,12.93,3.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,128,1000,1.48,14.08,4.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,256,1000,1.5,17.35,6.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,512,1000,1.8,22.2,12.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,1024,1000,15.8,21.59,18.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,2048,1000,18.7,25.98,22.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,4096,1000,22.45,32.37,27.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,8192,1000,42.33,55.13,48.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,16384,1000,64.39,87.52,78.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,32768,1000,124.94,207.7,168.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,65536,640,199.45,301.2,255.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,131072,320,372.59,459.36,408.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,262144,160,592.9,670.38,624.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,524288,80,985.84,1076.32,1023.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,1048576,40,1317.45,1434.16,1376.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,2097152,20,1802.6,2125.15,1939.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,216,4194304,10,3271.48,3925.78,3540.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,0,1000,0.03,0.24,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,1,1000,1.63,9.15,5.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,2,1000,1.59,8.38,5.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,4,1000,1.55,9.14,5.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,8,1000,1.18,6.27,3.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,16,1000,1.15,6.36,3.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,32,1000,1.58,8.42,5.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,64,1000,1.61,8.33,5.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,128,1000,1.71,9.36,5.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,256,1000,1.02,7.09,5.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,512,1000,0.95,10.25,6.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,1024,1000,2.59,38.27,20.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,2048,1000,4.33,17.73,14.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,4096,1000,7.23,22.46,15.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,8192,1000,12.16,34.46,24.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,16384,1000,80.59,90.87,86.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,32768,1000,25.17,35.94,30.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,65536,640,50.73,64.67,56.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,131072,320,79.56,123.62,101.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,262144,160,158.81,225.13,192.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,524288,80,269.0,354.22,325.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,1048576,40,628.77,802.34,742.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,2097152,20,1482.49,1717.81,1643.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Bcast,216,4194304,10,3107.27,5214.37,4674.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Alltoall,504,0,1000,0.04,0.09,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,1,1000,96.37,108.57,100.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,2,1000,97.65,107.08,101.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,4,1000,113.41,126.76,118.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,8,1000,121.37,135.62,128.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,16,1000,137.13,158.48,148.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,32,1000,208.06,243.92,228.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,64,1000,259.55,269.42,265.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,128,1000,505.64,520.56,512.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,256,1000,1008.83,1019.36,1013.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,512,1000,1647.81,1659.19,1653.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,1024,1000,5466.54,5643.56,5532.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,2048,1000,8708.99,8768.63,8724.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,4096,1000,12822.91,12879.92,12838.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,8192,1000,24027.08,24086.04,24050.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,16384,805,50441.52,50615.37,50517.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,32768,608,103942.33,104252.45,104104.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,65536,48,421208.0,439861.45,434663.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,131072,10,384374.05,386577.21,385700.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,262144,10,806498.6,813244.16,809587.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,524288,10,1632534.01,1643345.59,1638438.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,1048576,10,3039781.43,3060605.71,3051117.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Alltoall,504,2097152,8,6214503.04,6266749.18,6246502.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,720,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,1,1000,45.65,73.5,59.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,2,1000,46.06,92.77,64.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,4,1000,76.98,167.75,95.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,8,1000,41.71,57.59,50.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,16,1000,61.27,82.35,73.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,32,1000,114.43,143.97,130.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,64,1000,223.62,270.83,249.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,128,1000,567.12,643.99,601.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,256,1000,679.59,803.12,740.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,512,1000,980.34,1047.1,1016.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,1024,1000,808.01,879.61,846.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,2048,1000,1261.02,1304.34,1291.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,4096,1000,2168.6,2886.26,2510.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,8192,1000,3442.07,3641.27,3546.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,16384,1000,6849.29,8114.34,7408.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,32768,1000,15777.03,18664.85,17542.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,65536,546,24551.54,27409.09,26091.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,131072,320,48217.08,55649.13,51574.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,262144,160,100123.68,115562.41,107599.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,524288,44,230823.88,272994.41,262064.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,1048576,40,617368.36,731375.75,692897.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgather,720,2097152,20,1505473.57,1878101.26,1773109.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gather,648,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,1,1000,0.49,19.89,2.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,2,1000,0.5,33.11,4.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,4,1000,0.49,27.08,2.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,8,1000,0.5,63.95,7.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,16,1000,0.5,26.69,2.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,32,1000,0.5,90.83,10.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,64,1000,0.49,98.13,8.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,128,1000,0.55,68.41,3.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,256,1000,0.55,82.84,3.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,512,1000,0.7,139.46,4.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,1024,1000,0.85,313.93,12.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,2048,1000,1.0,364.04,10.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,4096,1000,1.37,1472.39,54.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,8192,1000,2.2,1785.43,101.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,16384,1000,3.8,3276.38,113.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,32768,1000,6.04,8979.83,347.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,65536,640,11.73,5764.95,2769.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,131072,320,23.66,9814.38,4399.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,262144,160,37.57,15424.93,8419.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,524288,80,75.69,30773.82,16486.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,1048576,40,219.4,61164.84,33019.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Gather,648,2097152,20,6111.83,163593.67,65908.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,504,0,1000,0.05,0.07,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,4,1000,2.55,6.24,3.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,8,1000,3.03,7.51,3.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,16,1000,0.55,9.97,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,32,1000,0.55,10.98,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,64,1000,0.56,10.11,1.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,128,1000,0.58,11.03,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,256,1000,0.6,14.04,1.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,512,1000,4.8,10.11,5.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,1024,1000,5.07,15.31,6.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,2048,1000,8.0,15.86,8.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,4096,1000,9.44,19.5,10.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,8192,1000,16.95,36.76,18.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,16384,1000,34.73,67.62,36.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,32768,1000,41.47,138.64,76.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,65536,640,69.94,220.36,120.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,131072,320,138.91,456.41,237.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,262144,160,84.54,782.28,384.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,524288,80,164.75,1071.58,563.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,1048576,40,214.76,1332.09,710.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,2097152,20,1394.89,3032.37,1956.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce,504,4194304,10,6854.32,43355.72,19585.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allreduce,216,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,4,1000,5.6,7.66,6.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,8,1000,5.85,7.87,6.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,16,1000,5.55,7.57,6.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,32,1000,5.45,7.62,6.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,64,1000,7.38,11.35,9.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,128,1000,8.39,13.74,9.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,256,1000,11.3,19.81,14.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,512,1000,10.43,12.31,11.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,1024,1000,15.81,27.84,26.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,2048,1000,17.3,20.87,19.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,4096,1000,17.14,21.84,18.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,8192,1000,31.94,40.71,33.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,16384,1000,70.1,83.85,74.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,32768,1000,75.8,93.3,82.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,65536,640,95.22,119.97,104.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,131072,320,174.74,210.23,188.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,262144,160,284.23,357.43,313.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,524288,80,615.1,762.91,672.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,1048576,40,1716.5,1779.46,1747.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,2097152,20,8032.1,11015.78,9450.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allreduce,216,4194304,10,8264.42,9705.78,9112.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,360,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,1,1000,0.49,15.01,2.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,2,1000,0.5,16.94,2.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,4,1000,0.5,72.94,9.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,8,1000,0.5,22.31,2.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,16,1000,0.48,36.88,4.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,32,1000,0.46,56.62,7.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,64,1000,0.5,51.37,4.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,128,1000,0.52,62.64,5.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,256,1000,0.54,138.17,12.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,512,1000,0.71,103.3,4.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,1024,1000,0.79,176.08,5.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,2048,1000,1.01,221.1,9.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,4096,1000,1.38,378.89,14.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,8192,1000,2.17,692.5,25.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,16384,1000,3.81,1236.93,43.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,32768,1000,7.16,2614.96,92.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,65536,640,12.04,2530.61,1428.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,131072,320,24.16,6375.72,2674.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,262144,160,39.66,9124.11,4961.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,524288,80,88.66,18099.43,9786.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,1048576,40,236.68,36452.16,19766.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,2097152,20,4679.94,82347.82,41523.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gather,360,4194304,10,15930.73,278813.55,71324.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Alltoall,576,0,1000,0.04,0.27,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,1,1000,112.47,118.23,115.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,2,1000,115.75,122.41,119.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,4,1000,140.61,169.88,148.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,8,1000,158.5,179.35,167.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,16,1000,192.91,210.37,205.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,32,1000,176.97,181.56,178.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,64,1000,303.39,308.75,305.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,128,1000,632.61,684.32,661.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,256,1000,3000.87,3034.23,3016.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,512,1000,2196.85,2557.75,2258.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,1024,1000,5043.5,5084.35,5066.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,2048,1000,9362.0,9496.56,9419.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,4096,1000,15960.94,15989.87,15978.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,8192,1000,29103.2,29579.67,29378.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,16384,599,58817.55,59051.5,58925.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,32768,532,111722.78,112552.84,112040.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,65536,239,238166.36,239109.59,238436.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,131072,42,458312.3,460997.68,459895.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,262144,17,882527.81,893560.64,886653.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,524288,17,1847006.01,1853410.11,1850090.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Alltoall,576,1048576,12,3548066.7,3562758.32,3555644.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgather,216,0,1000,0.04,0.1,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,1,1000,12.4,21.84,14.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,2,1000,13.4,17.73,15.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,4,1000,14.67,20.33,17.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,8,1000,17.85,27.87,23.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,16,1000,27.83,39.84,34.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,32,1000,24.04,39.13,32.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,64,1000,41.75,71.79,59.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,128,1000,172.12,198.09,184.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,256,1000,207.93,231.93,220.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,512,1000,257.08,288.62,272.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,1024,1000,235.23,246.28,240.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,2048,1000,353.02,388.6,371.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,4096,1000,557.96,620.68,590.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,8192,1000,1142.6,1782.74,1393.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,16384,1000,2050.38,2830.4,2502.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,32768,1000,3382.81,3969.78,3688.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,65536,640,6564.45,8584.7,7581.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,131072,320,12396.9,14602.68,13565.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,262144,160,24044.44,28019.4,26273.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,524288,80,45974.92,46971.48,46414.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,1048576,40,98172.27,99495.1,98845.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,2097152,20,408951.77,435667.07,425063.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgather,216,4194304,10,1077258.55,1224094.16,1158238.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,576,0,1000,3.19,4.2,3.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,1,1000,37.88,45.46,40.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,2,1000,46.37,54.76,50.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,4,1000,43.19,54.04,48.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,8,1000,53.41,80.27,65.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,16,1000,60.26,74.2,68.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,32,1000,92.9,122.21,113.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,64,1000,164.31,223.89,207.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,128,1000,458.65,518.31,482.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,256,1000,562.41,628.11,593.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,512,1000,1723.12,2570.6,2103.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,1024,1000,1128.56,1878.12,1444.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,2048,1000,945.96,971.99,964.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,4096,1000,1673.44,1804.54,1736.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,8192,1000,2817.21,3049.82,2960.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,16384,1000,5250.79,5643.31,5457.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,32768,1000,10000.55,10757.04,10405.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,65536,640,21268.91,24926.76,23199.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,131072,224,39824.14,46453.86,43040.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,262144,160,68024.79,72620.37,70436.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,524288,80,126746.84,131476.59,128760.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,1048576,40,324206.55,359059.08,342702.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,576,2097152,20,737295.65,784783.42,751456.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,720,0,1000,5.86,13.05,9.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,1,1000,16.04,23.59,19.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,2,1000,15.73,22.91,18.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,4,1000,15.97,23.58,19.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,8,1000,15.05,22.42,18.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,16,1000,16.24,24.81,20.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,32,1000,19.97,30.16,24.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,64,1000,22.99,34.95,28.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,128,1000,33.14,49.91,41.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,256,1000,56.94,82.45,69.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,512,1000,58.89,99.21,81.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,1024,1000,41.81,123.32,96.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,2048,1000,27.12,219.87,155.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,4096,1000,22.15,390.1,259.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,8192,1000,42.85,1208.75,483.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,16384,1000,38.01,1521.3,995.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,32768,1000,43.39,2891.87,1804.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,65536,640,185.84,5835.83,3679.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,131072,320,109.54,7157.6,3735.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,262144,160,182.84,14577.23,11743.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,524288,80,362.24,27747.52,18799.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,1048576,40,3179.86,55445.04,43051.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatterv,720,2097152,20,10107.04,129092.31,100426.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,288,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,1,1000,61.54,78.23,69.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,2,1000,64.35,77.04,70.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,4,1000,67.91,85.1,77.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,8,1000,77.33,96.53,85.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,16,1000,100.57,125.98,113.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,32,1000,104.95,118.95,113.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,64,1000,171.31,192.37,184.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,128,1000,229.23,240.32,235.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,256,1000,440.82,451.2,446.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,512,1000,1064.34,1472.21,1257.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,1024,1000,1780.27,1794.75,1786.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,2048,1000,3022.24,3034.79,3027.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,4096,1000,6416.66,6443.24,6424.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,8192,1000,11258.0,11282.78,11267.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,16384,1000,24706.28,24809.69,24760.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,32768,810,45898.5,46083.65,45985.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,65536,542,95241.75,95455.84,95324.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,131072,176,190392.07,190884.57,190627.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,262144,150,368131.26,368877.33,368330.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,524288,27,728956.58,731544.6,730426.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,1048576,27,1445968.44,1451277.67,1448239.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Alltoall,288,2097152,13,2946712.4,2965054.87,2957858.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,0,1000,0.05,0.09,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,4,1000,3.82,7.5,4.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,8,1000,2.64,5.97,3.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,16,1000,3.12,7.79,4.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,32,1000,3.76,7.75,4.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,64,1000,4.35,8.54,5.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,128,1000,0.59,12.13,1.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,256,1000,5.06,9.99,5.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,512,1000,4.24,9.83,5.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,1024,1000,5.54,11.83,6.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,2048,1000,7.4,18.19,8.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,4096,1000,9.41,17.39,9.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,8192,1000,16.5,31.3,17.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,16384,1000,30.75,47.35,31.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,32768,1000,38.24,138.3,74.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,65536,640,62.3,179.76,108.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,131072,320,142.17,355.34,228.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,262144,160,83.14,734.83,378.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,524288,80,163.86,1329.36,603.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,1048576,40,210.61,1309.97,704.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,2097152,20,1484.24,2927.44,2263.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Reduce,288,4194304,10,7433.54,42541.93,18478.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,648,0,1000,0.04,0.11,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,1,1000,4.24,343.52,29.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,2,1000,2.8,49.27,11.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,4,1000,2.86,20.57,10.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,8,1000,3.63,25.16,12.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,16,1000,2.88,18.5,10.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,32,1000,7.27,41.53,20.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,64,1000,9.58,32.23,19.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,128,1000,17.16,60.94,35.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,256,1000,54.59,110.87,65.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,512,1000,56.53,208.96,86.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,1024,1000,35.95,117.41,80.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,2048,1000,16.59,205.96,127.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,4096,1000,11.78,709.21,226.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,8192,1000,32.81,708.29,418.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,16384,1000,26.08,1369.23,801.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,32768,1000,29.33,3931.48,1556.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,65536,640,29.4,4253.78,1980.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,131072,320,71.86,6981.57,5238.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,262144,160,152.78,12422.46,7108.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,524288,80,201.5,24675.12,16823.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,1048576,40,358.98,49301.97,38235.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,648,2097152,20,9404.76,112212.36,88072.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,432,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,1,1000,1.65,19.24,9.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,2,1000,2.19,17.28,9.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,4,1000,2.43,20.66,11.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,8,1000,1.63,15.73,8.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,16,1000,1.63,14.27,8.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,32,1000,1.71,14.28,9.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,64,1000,1.71,14.3,8.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,128,1000,1.73,14.94,9.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,256,1000,1.81,15.78,10.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,512,1000,1.82,16.8,11.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,1024,1000,1.31,18.23,12.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,2048,1000,4.9,27.39,19.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,4096,1000,7.85,31.61,21.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,8192,1000,13.5,46.63,33.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,16384,1000,82.64,107.74,97.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,32768,1000,30.0,62.91,48.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,65536,640,48.35,81.17,66.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,131072,320,89.02,141.61,116.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,262144,160,178.2,238.62,211.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,524288,80,332.19,414.1,385.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,1048576,40,766.86,961.41,888.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,2097152,20,1682.21,2074.79,1847.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Bcast,432,4194304,10,3102.35,5581.26,4751.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allreduce,144,0,1000,0.05,0.08,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,4,1000,6.66,7.3,6.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,8,1000,5.34,7.66,6.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,16,1000,5.01,7.48,5.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,32,1000,5.05,7.49,5.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,64,1000,6.24,11.21,8.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,128,1000,6.67,13.66,8.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,256,1000,7.72,13.54,8.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,512,1000,7.21,13.52,9.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,1024,1000,8.07,13.22,9.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,2048,1000,12.14,26.34,13.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,4096,1000,16.42,22.59,17.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,8192,1000,30.99,39.84,32.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,16384,1000,60.3,68.55,61.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,32768,1000,55.45,65.59,59.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,65536,640,77.69,92.46,82.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,131072,320,133.65,158.12,140.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,262144,160,243.04,288.64,255.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,524288,80,597.1,690.96,623.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,1048576,40,1065.85,1374.11,1101.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,2097152,20,5674.66,7223.1,6423.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allreduce,144,4194304,10,7743.34,8753.88,8375.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,720,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,1,1000,2.24,10.72,6.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,2,1000,2.24,11.4,6.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,4,1000,2.75,12.2,7.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,8,1000,3.43,12.74,7.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,16,1000,4.52,13.47,8.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,32,1000,7.36,21.04,13.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,64,1000,11.18,22.66,16.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,128,1000,19.04,42.31,29.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,256,1000,24.5,60.49,45.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,512,1000,44.35,82.87,67.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,1024,1000,27.75,110.47,82.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,2048,1000,12.15,204.47,137.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,4096,1000,8.94,377.29,245.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,8192,1000,36.0,743.96,476.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,16384,1000,27.23,1454.03,914.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,32768,1000,30.54,3089.31,1797.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,65536,640,52.48,5750.38,1997.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,131072,320,83.96,7785.96,6062.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,262144,160,151.93,17063.92,7864.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,524288,80,194.63,27742.34,18771.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,1048576,40,1268.49,56374.83,43074.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Scatter,720,2097152,20,9852.13,126263.19,101243.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Alltoall,648,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,1,1000,122.14,130.65,124.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,2,1000,126.81,134.87,130.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,4,1000,141.08,152.49,145.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,8,1000,762.21,1068.02,838.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,16,1000,230.04,259.08,238.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,32,1000,198.31,202.81,200.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,64,1000,342.83,348.6,345.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,128,1000,693.52,703.81,698.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,256,1000,1871.83,2409.91,2059.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,512,1000,2911.25,3373.68,3047.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,1024,1000,6612.49,6666.18,6633.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,2048,1000,9183.99,9246.23,9195.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,4096,1000,16660.99,16735.9,16680.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,8192,1000,38362.02,38483.68,38412.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,16384,875,70449.92,70777.46,70618.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,32768,428,140324.95,140754.11,140585.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,65536,201,292300.64,293395.26,292704.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,131072,8,616891.71,620098.12,618972.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,262144,8,1357398.48,1363898.69,1360801.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,524288,8,2252225.01,2267489.04,2259176.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Alltoall,648,1048576,8,4431872.41,4446437.42,4439749.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,0,1000,3.64,20.75,11.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,1,1000,14.6,156.08,26.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,2,1000,16.13,43.93,27.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,4,1000,15.0,33.06,22.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,8,1000,14.75,35.0,22.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,16,1000,15.57,34.82,23.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,32,1000,18.88,38.91,27.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,64,1000,21.54,44.06,30.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,128,1000,29.22,52.04,39.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,256,1000,37.08,73.19,53.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,512,1000,62.26,105.38,82.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,1024,1000,55.21,282.85,102.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,2048,1000,30.16,236.64,154.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,4096,1000,24.64,379.4,233.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,8192,1000,50.78,1008.96,445.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,16384,1000,40.62,1634.65,826.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,32768,1000,42.11,2613.05,1585.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,65536,640,37.69,6699.84,1887.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,131072,320,79.85,8630.27,5219.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,262144,160,138.5,12441.41,7142.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,524288,80,375.61,28283.08,16876.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,1048576,40,3978.4,49317.87,38263.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatterv,648,2097152,20,9414.81,112449.2,86810.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce_scatter,144,0,1000,0.85,1.82,0.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,4,1000,1.31,20.51,4.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,8,1000,1.3,20.45,4.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,16,1000,1.31,12.0,3.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,32,1000,1.51,12.35,4.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,64,1000,1.82,14.73,5.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,128,1000,1.83,15.16,6.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,256,1000,2.17,18.12,9.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,512,1000,5.11,16.77,12.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,1024,1000,12.07,20.12,15.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,2048,1000,15.17,25.76,19.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,4096,1000,20.13,28.6,23.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,8192,1000,28.86,41.04,34.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,16384,1000,50.52,72.01,61.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,32768,1000,110.7,142.52,127.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,65536,640,173.31,267.74,223.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,131072,320,260.2,380.02,322.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,262144,160,525.19,602.36,557.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,524288,80,684.4,835.22,755.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,1048576,40,1227.46,1345.19,1280.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,2097152,20,1778.5,2026.17,1888.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Reduce_scatter,144,4194304,10,2803.93,3288.98,2988.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,576,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,1,1000,2.46,30.72,13.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,2,1000,2.7,26.64,12.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,4,1000,5.07,22.9,12.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,8,1000,5.54,23.78,13.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,16,1000,5.95,25.77,15.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,32,1000,8.58,30.78,17.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,64,1000,10.41,32.71,19.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,128,1000,14.11,63.26,36.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,256,1000,17.24,425.81,57.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,512,1000,56.16,119.55,83.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,1024,1000,39.43,115.13,79.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,2048,1000,58.12,228.35,171.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,4096,1000,100.22,389.14,287.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,8192,1000,34.22,664.69,386.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,16384,1000,39.01,1270.72,742.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,32768,1000,33.45,2627.76,1259.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,65536,640,30.05,4080.23,1694.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,131072,320,59.05,6133.7,4362.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,262144,160,193.36,11612.92,6192.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,524288,80,357.15,29110.29,14626.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,1048576,40,407.36,43190.11,33177.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,576,2097152,20,7526.6,103060.71,78056.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,216,0,1000,4.94,20.8,10.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,1,1000,1.61,33.19,6.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,2,1000,3.2,40.18,7.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,4,1000,1.41,26.82,5.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,8,1000,1.43,89.14,11.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,16,1000,1.26,25.94,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,32,1000,1.18,28.26,4.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,64,1000,1.44,32.99,5.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,128,1000,1.3,36.88,5.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,256,1000,1.37,45.97,5.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,512,1000,2.21,89.28,7.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,1024,1000,4.06,151.53,10.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,2048,1000,52.35,255.05,151.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,4096,1000,3.61,280.04,26.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,8192,1000,92.27,447.24,260.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,16384,1000,132.69,764.59,382.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,32768,1000,196.27,1362.37,564.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,65536,640,428.79,1704.74,1173.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,131072,320,1517.32,3266.45,2458.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,262144,160,2897.31,6267.32,4917.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,524288,80,5898.89,12494.8,10105.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,1048576,40,11957.23,24161.62,19785.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,2097152,20,25134.64,49495.04,41060.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,216,4194304,10,35225.33,83868.63,67278.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,576,0,1000,5.07,12.42,7.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,1,1000,14.16,21.53,16.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,2,1000,15.92,23.78,18.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,4,1000,16.43,26.36,19.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,8,1000,14.09,22.13,16.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,16,1000,14.87,23.57,17.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,32,1000,16.92,27.26,20.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,64,1000,19.98,36.62,24.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,128,1000,25.09,41.37,31.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,256,1000,28.76,61.15,43.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,512,1000,53.84,92.99,70.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,1024,1000,47.29,114.05,82.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,2048,1000,19.81,198.7,124.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,4096,1000,19.69,353.14,210.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,8192,1000,45.6,665.75,398.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,16384,1000,42.94,1277.92,752.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,32768,1000,44.1,2587.5,1484.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,65536,640,175.46,5971.9,3131.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,131072,320,71.07,5571.71,3163.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,262144,160,322.54,14496.27,8730.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,524288,80,376.85,30559.01,14420.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,1048576,40,1977.8,43334.08,33126.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,576,2097152,20,9782.65,102345.71,76668.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatter,144,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,1,1000,2.23,14.09,4.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,2,1000,2.23,6.55,4.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,4,1000,2.46,6.88,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,8,1000,2.48,8.0,5.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,16,1000,2.49,7.22,4.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,32,1000,2.87,7.36,4.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,64,1000,3.85,8.93,6.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,128,1000,5.14,14.43,9.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,256,1000,4.68,14.14,9.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,512,1000,5.29,22.7,14.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,1024,1000,8.0,36.49,24.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,2048,1000,11.2,69.55,47.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,4096,1000,6.97,179.7,111.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,8192,1000,24.27,290.79,148.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,16384,1000,29.15,396.93,181.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,32768,1000,52.14,746.4,351.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,65536,640,51.22,459.47,272.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,131072,320,142.66,1615.77,1217.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,262144,160,162.5,1661.02,932.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,524288,80,314.36,3165.79,1748.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,1048576,40,381.47,6309.27,5930.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,2097152,20,1018.32,12540.4,7684.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,144,4194304,10,19061.46,26554.69,25424.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgather,648,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,1,1000,21.51,28.44,24.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,2,1000,25.17,34.03,28.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,4,1000,27.23,38.7,32.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,8,1000,45.17,56.48,50.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,16,1000,57.36,71.96,65.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,32,1000,108.99,130.18,120.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,64,1000,370.01,708.84,399.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,128,1000,504.55,568.35,533.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,256,1000,603.31,658.0,638.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,512,1000,822.93,911.28,861.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,1024,1000,732.47,767.9,751.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,2048,1000,1150.42,1187.5,1180.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,4096,1000,1856.0,2003.87,1938.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,8192,1000,3165.55,3410.29,3306.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,16384,1000,5897.52,6313.99,6098.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,32768,1000,12144.79,14070.94,13054.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,65536,640,24185.45,28216.34,26385.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,131072,320,39682.15,43804.38,41552.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,262144,160,86219.12,102014.02,92987.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,524288,80,167719.64,185597.92,176096.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,1048576,40,457660.01,570626.38,527277.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Allgather,648,2097152,20,1343056.43,1744490.72,1612791.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Reduce,720,0,1000,0.05,0.32,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,4,1000,0.51,12.7,1.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,8,1000,0.54,17.77,1.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,16,1000,0.55,15.16,1.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,32,1000,0.55,15.1,1.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,64,1000,5.29,13.96,6.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,128,1000,0.58,15.36,1.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,256,1000,0.57,21.5,1.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,512,1000,5.16,15.48,6.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,1024,1000,5.43,15.55,6.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,2048,1000,6.85,19.04,7.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,4096,1000,9.84,23.5,10.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,8192,1000,16.82,35.47,17.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,16384,1000,19.44,101.9,42.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,32768,1000,73.42,127.25,76.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,65536,640,73.17,254.77,129.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,131072,320,125.94,412.18,226.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,262144,160,96.44,589.74,305.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,524288,80,170.63,1161.7,584.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,1048576,40,216.93,1527.06,762.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,2097152,20,1398.52,3091.46,1948.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,720,4194304,10,6162.47,44409.48,20270.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,144,0,1000,0.99,25.48,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,1,1000,21.86,31.0,26.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,2,1000,24.58,54.04,48.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,4,1000,16.92,23.43,19.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,8,1000,23.71,31.39,27.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,16,1000,22.19,30.42,26.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,32,1000,17.66,28.18,23.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,64,1000,24.2,44.59,37.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,128,1000,41.69,76.71,65.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,256,1000,77.34,141.23,117.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,512,1000,172.44,203.73,185.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,1024,1000,155.27,164.54,160.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,2048,1000,226.51,258.75,245.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,4096,1000,354.14,415.38,384.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,8192,1000,592.11,683.29,636.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,16384,1000,1085.67,1336.2,1216.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,32768,1000,2212.99,3230.15,2841.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,65536,640,3980.74,5108.84,4589.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,131072,320,7798.05,9915.64,8933.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,262144,160,14805.21,18570.28,16952.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,524288,80,30581.66,31527.0,31004.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,1048576,40,65557.55,67185.64,66384.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,2097152,20,153543.24,159512.14,156172.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Allgatherv,144,4194304,10,330086.26,338560.88,334465.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Scatter,360,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,1,1000,1.85,8.45,5.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,2,1000,2.1,10.18,6.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,4,1000,3.75,10.91,6.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,8,1000,2.93,8.75,5.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,16,1000,3.08,9.32,6.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,32,1000,4.33,10.74,7.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,64,1000,6.6,14.04,10.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,128,1000,11.69,26.46,18.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,256,1000,14.83,28.19,21.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,512,1000,44.5,72.13,61.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,1024,1000,44.61,102.1,77.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,2048,1000,21.61,91.68,72.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,4096,1000,14.1,220.01,123.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,8192,1000,33.23,341.48,218.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,16384,1000,46.23,1158.46,428.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,32768,1000,54.24,1303.93,800.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,65536,640,37.58,1720.93,954.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,131072,320,72.64,3823.05,2512.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,262144,160,127.06,6209.26,3494.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,524288,80,312.24,12425.56,8177.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,1048576,40,383.25,24740.13,17679.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,2097152,20,10116.64,53505.3,41050.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatter,360,4194304,10,18949.08,128542.49,95629.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,0,1000,2.09,2.27,2.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,1,1000,23.55,29.68,26.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,2,1000,55.97,61.0,59.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,4,1000,29.17,36.12,32.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,8,1000,33.36,45.08,38.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,16,1000,37.49,46.87,43.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,32,1000,57.64,75.48,67.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,64,1000,100.76,132.79,118.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,128,1000,513.44,1035.46,794.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,256,1000,345.11,385.35,367.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,512,1000,444.56,509.95,473.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,1024,1000,398.74,409.25,403.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,2048,1000,634.36,675.49,656.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,4096,1000,1019.83,1095.12,1059.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,8192,1000,1818.53,2511.68,2182.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,16384,1000,3332.27,4113.9,3724.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,32768,1000,7500.68,8430.03,8015.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,65536,640,12452.55,14457.18,13477.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,131072,320,22072.76,24412.12,23293.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,262144,160,42172.94,46301.65,44445.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,524288,80,81964.82,85734.22,84024.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,1048576,40,190387.52,204487.55,195730.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,2097152,20,432870.58,483313.27,449121.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgatherv,360,4194304,10,921969.53,1002212.53,975988.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,432,0,1000,4.55,13.43,8.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,1,1000,13.45,25.32,17.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,2,1000,13.46,21.51,17.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,4,1000,13.89,22.46,18.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,8,1000,11.38,18.96,15.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,16,1000,12.41,35.71,19.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,32,1000,14.61,24.3,19.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,64,1000,16.4,27.06,21.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,128,1000,18.93,34.04,27.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,256,1000,20.28,46.86,35.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,512,1000,50.81,82.22,68.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,1024,1000,47.78,94.09,75.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,2048,1000,27.84,139.66,98.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,4096,1000,17.87,250.34,157.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,8192,1000,46.17,487.1,297.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,16384,1000,54.35,1173.83,563.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,32768,1000,52.73,1873.1,1034.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,65536,640,65.5,4351.23,2103.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,131072,320,87.05,5244.15,2319.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,262144,160,270.63,12160.36,5649.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,524288,80,270.98,15460.14,10061.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,1048576,40,365.61,30914.97,23332.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,2097152,20,9288.76,73730.47,54661.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,432,4194304,10,18968.27,175886.81,116633.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Scatterv,360,0,1000,3.75,10.03,7.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,1,1000,10.57,16.74,13.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,2,1000,12.66,20.19,16.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,4,1000,12.94,20.97,16.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,8,1000,10.25,16.52,13.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,16,1000,10.88,17.78,14.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,32,1000,12.05,19.41,15.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,64,1000,14.15,22.41,18.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,128,1000,16.14,26.96,22.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,256,1000,22.29,37.43,30.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,512,1000,34.62,68.94,51.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,1024,1000,50.54,85.98,67.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,2048,1000,35.37,289.6,92.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,4096,1000,22.95,185.44,128.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,8192,1000,42.77,351.9,228.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,16384,1000,53.42,682.57,427.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,32768,1000,51.41,1403.65,801.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,65536,640,54.3,2812.26,1598.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,131072,320,201.29,6177.1,3286.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,262144,160,188.46,6259.85,3691.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,524288,80,316.19,12843.22,9515.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,1048576,40,382.46,33444.15,18152.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,2097152,20,4431.94,49470.06,39383.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,360,4194304,10,14286.89,136560.95,91134.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Scatterv,216,0,1000,2.95,6.56,4.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,1,1000,10.28,15.38,12.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,2,1000,10.18,15.1,12.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,4,1000,10.8,16.18,12.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,8,1000,8.66,12.97,10.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,16,1000,9.45,14.68,11.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,32,1000,9.53,14.64,11.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,64,1000,10.78,17.24,13.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,128,1000,12.14,19.52,15.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,256,1000,14.6,24.31,18.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,512,1000,18.98,33.58,28.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,1024,1000,38.38,71.21,53.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,2048,1000,30.56,73.18,59.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,4096,1000,22.27,142.38,91.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,8192,1000,42.81,608.39,188.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,16384,1000,52.7,609.28,332.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,32768,1000,60.24,1072.15,573.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,65536,640,53.64,1185.41,731.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,131072,320,84.45,4243.39,1698.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,262144,160,181.7,3136.49,2016.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,524288,80,350.51,6374.47,4209.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,1048576,40,402.48,12397.96,8322.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,2097152,20,7869.02,24797.52,20076.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Scatterv,216,4194304,10,10299.35,58926.27,41691.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,4,1000,6.0,9.8,6.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,8,1000,3.84,8.38,4.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,16,1000,3.93,7.63,4.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,32,1000,3.84,7.77,4.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,64,1000,0.56,8.25,1.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,128,1000,0.58,8.69,1.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,256,1000,0.6,10.19,1.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,512,1000,4.38,11.18,5.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,1024,1000,5.01,8.39,5.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,2048,1000,6.98,10.89,7.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,4096,1000,9.93,17.7,10.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,8192,1000,16.73,27.26,17.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,16384,1000,30.51,41.99,31.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,32768,1000,47.1,130.02,81.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,65536,640,74.75,230.41,134.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,131072,320,136.81,328.36,215.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,262144,160,79.73,703.36,370.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,524288,80,151.51,993.58,536.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,1048576,40,214.26,1224.0,684.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,2097152,20,1457.24,2767.52,2158.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,216,4194304,10,5822.65,40299.81,19205.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce,576,0,1000,0.05,0.08,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,4,1000,2.6,8.37,3.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,8,1000,3.12,9.79,3.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,16,1000,5.34,14.47,6.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,32,1000,0.55,15.4,1.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,64,1000,0.57,19.69,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,128,1000,0.58,15.77,1.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,256,1000,0.6,17.79,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,512,1000,6.67,182.02,28.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,1024,1000,7.82,30.68,9.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,2048,1000,9.14,63.62,15.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,4096,1000,10.12,36.1,12.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,8192,1000,17.05,40.64,17.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,16384,1000,33.28,693.27,111.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,32768,1000,43.04,190.8,83.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,65536,640,72.91,247.47,125.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,131072,320,143.3,427.59,237.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,262144,160,84.07,789.21,383.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,524288,80,161.58,1116.18,570.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,1048576,40,214.14,1341.25,709.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,2097152,20,1399.85,3096.01,1973.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Reduce,576,4194304,10,7484.07,44290.14,19981.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Allgatherv,288,0,1000,1.72,6.92,1.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,1,1000,128.01,395.4,140.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,2,1000,46.92,60.12,53.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,4,1000,56.03,62.02,59.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,8,1000,26.67,52.27,31.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,16,1000,30.22,39.09,35.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,32,1000,43.83,58.01,53.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,64,1000,77.45,100.52,91.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,128,1000,229.17,258.75,242.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,256,1000,277.45,364.05,328.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,512,1000,229.42,318.17,291.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,1024,1000,383.45,424.44,410.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,2048,1000,700.05,735.59,722.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,4096,1000,799.65,891.55,851.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,8192,1000,1363.31,1489.04,1432.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,16384,1000,2535.01,2838.81,2700.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,32768,1000,4793.73,5413.02,5119.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,65536,640,9301.28,11379.21,10421.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,131072,320,17091.87,20548.9,18921.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,262144,160,32927.84,39796.94,36673.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,524288,80,65942.23,72182.08,68674.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,1048576,40,142814.14,150249.6,147802.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,2097152,20,339824.34,354431.64,344498.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,288,4194304,10,671027.6,688647.47,679766.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,216,0,1000,1.36,1.81,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,1,1000,23.43,32.52,27.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,2,1000,17.48,22.41,19.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,4,1000,19.81,25.13,22.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,8,1000,20.41,26.47,23.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,16,1000,24.75,32.39,28.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,32,1000,28.98,44.01,37.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,64,1000,44.66,74.95,62.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,128,1000,166.33,191.72,178.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,256,1000,212.31,244.39,228.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,512,1000,260.16,306.03,280.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,1024,1000,240.83,251.77,246.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,2048,1000,354.9,389.97,372.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,4096,1000,598.3,691.61,641.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,8192,1000,1105.36,1643.35,1410.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,16384,1000,1750.56,2004.82,1883.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,32768,1000,3397.4,4060.26,3741.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,65536,640,6615.62,8503.91,7530.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,131072,320,12369.81,14576.68,13566.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,262144,160,23725.9,27633.17,25945.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,524288,80,45141.36,46143.09,45605.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,1048576,40,107323.58,116423.26,111462.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,2097152,20,241129.96,267787.05,256184.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Allgatherv,216,4194304,10,497202.05,521168.18,510335.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Reduce_scatter,504,0,1000,2.0,2.4,2.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,4,1000,2.3,14.12,4.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,8,1000,2.33,16.94,4.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,16,1000,2.32,16.8,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,32,1000,2.68,17.47,4.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,64,1000,2.34,18.11,4.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,128,1000,2.36,22.89,5.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,256,1000,2.69,20.3,6.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,512,1000,2.69,28.07,9.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,1024,1000,2.97,27.01,14.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,2048,1000,26.78,32.32,29.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,4096,1000,46.85,53.32,49.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,8192,1000,58.4,64.92,61.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,16384,1000,74.01,83.16,78.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,32768,1000,140.15,152.14,147.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,65536,640,183.85,381.99,283.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,131072,320,313.1,556.75,437.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,262144,160,812.77,936.75,864.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,524288,80,1110.27,1229.74,1171.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,1048576,40,1487.11,1624.19,1564.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,2097152,20,2614.88,2732.96,2675.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,504,4194304,10,3692.74,4429.67,4077.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,432,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,1,1000,16.1,36.14,25.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,2,1000,27.28,42.65,34.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,4,1000,19.38,42.61,29.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,8,1000,30.27,54.87,40.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,16,1000,36.36,53.09,45.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,32,1000,58.66,84.55,74.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,64,1000,110.51,155.58,138.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,128,1000,334.83,383.2,356.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,256,1000,402.65,438.27,421.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,512,1000,554.12,629.48,587.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,1024,1000,475.37,501.64,485.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,2048,1000,962.34,1569.53,1298.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,4096,1000,1450.6,1622.9,1570.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,8192,1000,2031.06,2179.5,2109.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,16384,1000,3786.74,4615.5,4115.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,32768,1000,7321.8,8047.22,7688.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,65536,640,13923.52,16450.36,15272.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,131072,298,27114.28,34810.87,30909.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,262144,160,56658.7,66276.12,60982.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,524288,80,95963.46,103517.59,99806.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,1048576,40,281216.47,325484.35,303573.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,2097152,20,798677.04,1020801.02,912509.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Allgather,432,4194304,10,2230271.25,3027905.82,2649269.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,6, 100
+Gather,288,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,1,1000,0.4,10.21,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,2,1000,0.42,12.5,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,4,1000,0.46,15.56,1.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,8,1000,0.43,13.51,1.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,16,1000,0.41,14.22,1.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,32,1000,0.42,16.86,1.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,64,1000,0.43,20.53,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,128,1000,0.44,26.67,1.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,256,1000,0.46,37.1,1.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,512,1000,0.82,57.83,2.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,1024,1000,0.95,131.68,5.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,2048,1000,1.33,267.81,8.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,4096,1000,1.85,337.75,4.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,8192,1000,3.24,561.63,7.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,16384,1000,6.57,988.44,12.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,32768,1000,12.3,1819.31,22.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,65536,640,43.55,2283.45,1301.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,131072,320,90.72,4146.4,2291.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,262144,160,166.56,8577.85,4350.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,524288,80,349.3,15906.75,8668.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,1048576,40,239.23,30367.38,16287.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,2097152,20,4307.79,61940.6,35070.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Gather,288,4194304,10,18729.6,178101.46,64143.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Bcast,648,0,1000,0.03,0.1,0.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,1,1000,2.97,5.86,4.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,2,1000,2.24,9.2,3.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,4,1000,1.96,9.26,3.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,8,1000,1.88,5.87,3.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,16,1000,1.84,5.73,3.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,32,1000,3.56,7.03,4.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,64,1000,3.67,7.48,5.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,128,1000,3.93,7.72,5.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,256,1000,4.73,8.84,6.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,512,1000,3.88,8.89,6.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,1024,1000,6.38,24.39,22.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,2048,1000,6.88,23.43,19.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,4096,1000,10.94,22.78,18.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,8192,1000,18.0,43.95,33.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,16384,1000,94.86,109.95,100.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,32768,1000,43.11,64.14,51.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,65536,640,50.72,83.99,69.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,131072,320,94.79,143.63,122.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,262144,160,181.89,257.57,224.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,524288,80,335.03,441.73,414.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,1048576,40,838.33,873.41,861.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,2097152,20,2440.12,2842.58,2631.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Bcast,648,4194304,10,3211.05,5678.0,5066.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,9, 100
+Scatter,288,0,1000,0.04,0.19,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,1,1000,1.85,8.07,3.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,2,1000,2.53,6.9,4.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,4,1000,3.03,8.69,5.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,8,1000,2.45,10.57,5.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,16,1000,3.12,11.23,6.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,32,1000,4.0,10.21,5.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,64,1000,4.97,13.18,8.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,128,1000,6.93,24.6,15.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,256,1000,9.22,23.93,15.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,512,1000,13.0,36.73,26.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,1024,1000,13.97,53.97,39.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,2048,1000,23.71,91.5,65.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,4096,1000,5.25,475.17,256.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,8192,1000,32.29,291.57,179.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,16384,1000,15.59,690.63,320.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,32768,1000,37.1,784.82,561.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,65536,640,43.51,1332.67,780.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,131072,320,73.58,4695.59,1715.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,262144,160,136.59,4674.59,2439.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,524288,80,261.13,9332.7,6271.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,1048576,40,436.96,18584.45,12762.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,2097152,20,3823.89,37192.67,29291.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Scatter,288,4194304,10,97919.16,158188.34,134907.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgatherv,720,0,1000,3.92,4.11,3.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,1,1000,42.29,49.1,46.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,2,1000,42.34,50.68,44.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,4,1000,48.23,57.53,52.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,8,1000,76.04,91.54,83.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,16,1000,73.73,89.77,82.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,32,1000,122.5,148.15,136.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,64,1000,239.52,291.36,268.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,128,1000,574.89,677.84,622.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,256,1000,688.07,751.22,716.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,512,1000,1022.53,1142.76,1084.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,1024,1000,904.16,1031.33,987.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,2048,1000,1284.83,1319.16,1309.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,4096,1000,2103.46,2195.74,2153.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,8192,1000,3623.18,3781.95,3714.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,16384,1000,7198.65,7871.41,7587.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,32768,1000,14262.27,16513.05,15529.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,65536,640,25147.48,27234.69,26202.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,131072,320,50147.91,54840.74,52752.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,262144,160,97667.3,111496.18,105347.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,524288,51,166743.57,174482.38,171328.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,1048576,40,378707.21,392991.32,386028.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Allgatherv,720,2097152,20,941376.65,1000213.55,963609.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Gatherv,144,0,1000,2.83,6.81,4.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,1,1000,3.17,21.09,6.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,2,1000,2.83,20.35,6.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,4,1000,2.88,21.22,6.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,8,1000,2.36,18.85,5.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,16,1000,2.3,19.68,5.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,32,1000,2.16,19.86,5.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,64,1000,2.22,24.2,5.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,128,1000,2.2,30.94,5.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,256,1000,2.26,34.9,5.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,512,1000,2.54,48.3,6.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,1024,1000,3.53,130.09,25.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,2048,1000,33.44,169.04,98.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,4096,1000,4.04,194.64,35.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,8192,1000,75.6,324.09,192.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,16384,1000,106.43,550.2,298.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,32768,1000,117.15,920.48,463.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,65536,640,464.33,1648.42,1094.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,131072,320,857.29,4022.67,1960.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,262144,160,2075.89,4761.2,3559.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,524288,80,4872.85,9444.63,7333.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,1048576,40,11999.59,18090.03,14943.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,2097152,20,24633.67,36859.28,30686.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,144,4194304,10,34734.45,58923.47,46722.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gather,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,1,1000,0.45,28.58,1.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,2,1000,0.46,47.09,2.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,4,1000,0.46,9.84,1.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,8,1000,0.42,8.02,1.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,16,1000,0.41,9.11,1.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,32,1000,0.4,9.29,1.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,64,1000,0.43,12.64,1.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,128,1000,0.44,16.27,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,256,1000,0.46,23.84,1.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,512,1000,0.71,41.33,2.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,1024,1000,0.91,101.47,4.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,2048,1000,1.32,212.11,8.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,4096,1000,1.9,258.68,5.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,8192,1000,3.52,436.38,7.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,16384,1000,6.77,737.57,12.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,32768,1000,13.26,1329.09,23.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,65536,640,55.49,1729.33,1053.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,131072,320,100.11,3000.31,1740.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,262144,160,171.38,4953.04,2827.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,524288,80,326.16,9629.12,5486.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,1048576,40,240.69,24273.24,16018.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,2097152,20,3108.4,49295.85,34928.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gather,216,4194304,10,16383.27,130511.71,63093.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,3, 100
+Gatherv,576,0,1000,5.83,47.71,14.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,1,1000,3.02,71.9,13.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,2,1000,1.64,48.78,8.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,4,1000,3.07,60.3,10.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,8,1000,1.92,53.96,9.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,16,1000,1.86,54.64,8.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,32,1000,1.75,70.92,10.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,64,1000,1.7,68.05,8.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,128,1000,1.95,87.82,10.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,256,1000,1.81,135.21,11.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,512,1000,2.44,197.93,11.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,1024,1000,2.48,338.66,14.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,2048,1000,2.69,543.79,19.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,4096,1000,2.6,668.44,17.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,8192,1000,137.66,1249.4,1056.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,16384,1000,185.96,2135.96,1834.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,32768,1000,251.73,3956.0,3421.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,65536,640,340.29,4064.72,2444.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,131072,320,1236.23,7223.77,4154.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,262144,160,2885.9,14265.15,8216.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,524288,80,5125.65,28007.67,15964.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,1048576,40,12224.88,55406.03,31545.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Gatherv,576,2097152,20,22638.12,200977.61,58725.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,8, 100
+Scatterv,504,0,1000,4.09,8.42,6.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,1,1000,12.48,17.91,14.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,2,1000,14.32,20.42,17.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,4,1000,14.74,21.93,17.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,8,1000,12.11,18.12,14.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,16,1000,12.94,19.16,16.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,32,1000,15.06,22.46,18.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,64,1000,17.7,27.62,22.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,128,1000,21.25,35.81,28.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,256,1000,26.07,57.01,47.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,512,1000,49.1,85.5,69.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,1024,1000,42.9,102.11,78.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,2048,1000,26.27,167.44,115.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,4096,1000,20.32,314.21,197.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,8192,1000,46.41,621.54,372.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,16384,1000,52.92,1174.87,686.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,32768,1000,54.27,2316.71,1306.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,65536,640,61.09,4974.28,2590.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,131072,320,121.98,4842.99,2720.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,262144,160,245.81,9861.75,7232.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,524288,80,300.78,18982.85,12718.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,1048576,40,5466.07,37026.28,30030.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Scatterv,504,2097152,20,10136.77,97189.79,67283.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,1,1000,0.41,10.06,1.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,2,1000,0.44,12.17,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,4,1000,0.46,21.22,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,8,1000,0.4,11.45,1.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,16,1000,0.42,18.61,1.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,32,1000,0.42,22.4,1.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,64,1000,0.43,22.05,1.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,128,1000,0.44,30.53,1.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,256,1000,0.51,56.5,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,512,1000,0.9,79.18,3.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,1024,1000,1.04,173.37,5.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,2048,1000,1.36,296.67,8.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,4096,1000,2.4,539.75,13.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,8192,1000,3.92,1780.48,36.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,16384,1000,8.61,3558.5,71.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,32768,1000,13.69,4961.89,96.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,65536,640,38.12,3784.82,2042.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,131072,320,84.27,6500.08,3633.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,262144,160,156.12,12336.97,6737.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,524288,80,304.8,24498.9,13341.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,1048576,40,247.71,48837.2,26475.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Gather,504,2097152,20,5884.75,132396.6,54418.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Reduce_scatter,720,0,1000,2.69,3.94,2.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,4,1000,3.49,25.97,6.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,8,1000,2.97,23.93,6.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,16,1000,2.98,22.68,6.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,32,1000,2.99,23.74,6.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,64,1000,3.49,25.4,6.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,128,1000,3.05,62.59,8.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,256,1000,3.05,28.85,8.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,512,1000,3.39,34.81,11.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,1024,1000,3.72,48.63,20.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,2048,1000,13.02,53.71,40.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,4096,1000,50.02,60.9,56.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,8192,1000,128.41,319.67,164.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,16384,1000,145.03,174.95,163.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,32768,1000,207.48,228.61,220.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,65536,640,187.11,462.3,319.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,131072,320,580.87,917.71,743.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,262144,160,693.11,1053.24,871.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,524288,80,3370.66,8452.34,3457.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,1048576,40,2143.04,2742.29,2245.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,2097152,20,2986.14,3160.62,3087.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce_scatter,720,4194304,10,8533.04,12843.16,8784.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,10, 100
+Reduce,360,0,1000,0.05,0.08,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,4,1000,3.76,17.95,6.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,8,1000,3.77,18.81,6.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,16,1000,5.32,10.53,6.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,32,1000,0.56,19.91,1.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,64,1000,0.57,11.92,1.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,128,1000,0.6,32.0,2.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,256,1000,0.6,13.15,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,512,1000,4.89,10.51,5.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,1024,1000,5.87,11.95,6.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,2048,1000,7.61,14.5,8.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,4096,1000,9.56,18.07,10.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,8192,1000,16.63,31.4,17.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,16384,1000,31.68,54.79,32.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,32768,1000,40.69,132.91,74.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,65536,640,74.56,224.63,125.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,131072,320,144.74,384.0,231.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,262144,160,84.18,747.02,380.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,524288,80,163.65,1091.35,572.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,1048576,40,219.06,1428.78,734.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,2097152,20,1402.16,3008.28,1956.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Reduce,360,4194304,10,6925.78,43376.54,19879.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Bcast,144,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,1,1000,3.46,5.26,4.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,2,1000,0.72,3.89,2.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,4,1000,2.17,5.76,3.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,8,1000,2.19,5.7,3.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,16,1000,0.74,3.74,2.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,32,1000,0.74,3.82,2.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,64,1000,2.3,6.05,4.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,128,1000,2.36,6.27,4.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,256,1000,2.78,7.56,5.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,512,1000,1.82,6.34,3.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,1024,1000,3.32,57.95,27.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,2048,1000,9.15,36.13,25.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,4096,1000,6.55,18.47,13.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,8192,1000,10.78,28.59,21.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,16384,1000,78.71,87.04,82.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,32768,1000,23.65,34.75,28.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,65536,640,43.49,57.63,49.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,131072,320,83.09,106.43,91.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,262144,160,165.22,182.65,172.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,524288,80,292.98,321.04,314.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,1048576,40,534.87,574.37,556.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,2097152,20,1436.47,1515.49,1482.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Bcast,144,4194304,10,3003.82,4801.09,4316.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,2, 100
+Gatherv,360,0,1000,3.19,17.02,10.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,1,1000,1.98,47.23,9.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,2,1000,1.91,37.55,7.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,4,1000,1.84,37.82,6.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,8,1000,1.52,139.34,10.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,16,1000,3.88,64.27,12.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,32,1000,1.5,135.32,10.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,64,1000,2.34,55.7,8.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,128,1000,2.2,72.28,9.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,256,1000,1.94,186.63,11.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,512,1000,2.51,136.88,9.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,1024,1000,3.62,217.31,12.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,2048,1000,2.39,455.11,20.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,4096,1000,3.16,438.59,20.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,8192,1000,104.22,1243.04,660.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,16384,1000,137.5,1323.44,1058.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,32768,1000,205.94,2387.2,1914.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,65536,640,356.73,2731.55,1675.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,131072,320,1110.72,8475.69,3207.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,262144,160,2783.83,10629.97,6013.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,524288,80,4977.43,18828.5,11393.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,1048576,40,12058.93,36742.56,22320.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,2097152,20,24826.18,73981.47,45175.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Gatherv,360,4194304,10,26510.96,331209.83,64708.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,5, 100
+Allgather,504,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,1,1000,24.38,37.18,30.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,2,1000,18.18,30.15,25.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,4,1000,28.42,39.71,33.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,8,1000,27.84,39.42,34.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,16,1000,47.63,65.51,57.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,32,1000,71.64,104.14,90.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,64,1000,119.95,177.92,155.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,128,1000,397.76,456.66,431.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,256,1000,487.09,546.69,521.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,512,1000,640.94,718.2,684.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,1024,1000,675.12,748.96,717.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,2048,1000,840.19,929.53,883.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,4096,1000,1648.44,1857.91,1818.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,8192,1000,2426.65,2632.0,2523.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,16384,1000,4323.63,4681.3,4520.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,32768,1000,8888.04,9994.78,9425.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,65536,640,20078.83,23044.57,21754.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,131072,320,32570.32,36697.78,34379.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,262144,160,60200.7,67886.73,63720.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,524288,80,113040.05,116552.89,114810.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,1048576,40,369053.64,416331.15,391596.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,504,2097152,20,862159.44,948324.37,905915.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,7, 100
+Allgather,288,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,1,1000,18.81,26.35,21.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,2,1000,16.42,22.35,19.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,4,1000,14.98,22.16,18.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,8,1000,18.47,28.64,23.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,16,1000,25.05,37.4,31.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,32,1000,39.85,55.33,50.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,64,1000,74.19,97.43,88.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,128,1000,225.9,253.29,238.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,256,1000,261.92,285.3,272.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,512,1000,372.65,418.98,396.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,1024,1000,314.35,323.7,318.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,2048,1000,652.53,1162.58,912.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,4096,1000,803.34,890.84,858.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,8192,1000,1356.59,1508.53,1441.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,16384,1000,2488.26,2780.92,2644.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,32768,1000,5222.65,6049.06,5669.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,65536,640,8933.47,10201.27,9606.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,131072,320,16709.75,18955.65,18000.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,262144,160,32645.17,36771.6,35018.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,524288,80,71307.31,75879.68,73818.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,1048576,40,164202.62,177703.46,170485.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,2097152,20,584755.87,652607.02,622421.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
+Allgather,288,4194304,10,1670680.91,1993604.3,1876502.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_23-53-00,4, 100
diff --git a/results-and-plotting/data/data-multi-defand100cflag.csv b/results-and-plotting/data/data-multi-defand100cflag.csv
new file mode 100644
index 0000000..c14b677
--- /dev/null
+++ b/results-and-plotting/data/data-multi-defand100cflag.csv
@@ -0,0 +1,3675 @@
+benchmark_type,proc_num,msg_size_bytes,repetitions,t_min_usec,t_max_usec,t_avg_usec,mpi_datatype,mpi_red_datatype,mpi_red_op,creation_time,n_nodes,off_cache_flag
+Alltoall,360,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,1,1000,439.33,740.43,538.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,2,1000,75.27,83.69,79.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,4,1000,78.34,87.11,82.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,8,1000,95.31,110.12,102.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,16,1000,102.3,115.93,108.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,32,1000,141.67,159.3,151.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,64,1000,222.77,259.03,243.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,128,1000,402.59,480.5,449.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,256,1000,1128.36,1152.91,1140.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,512,1000,1547.33,1572.05,1557.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,1024,1000,3710.76,3916.45,3840.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,2048,1000,4034.52,4043.12,4038.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,4096,1000,7714.1,7728.94,7720.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,8192,1000,17554.76,17584.9,17565.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,16384,1000,32690.2,32811.59,32729.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,32768,1000,64980.0,65151.48,65049.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,65536,403,138177.06,139259.61,138866.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,131072,12,272854.46,273144.5,272974.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,262144,12,529436.2,529702.94,529558.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,524288,12,962055.03,969229.67,966438.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,1048576,12,1887068.02,1888622.38,1887741.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,2097152,10,3712873.07,3715672.57,3714654.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,360,4194304,8,7355777.31,7365243.09,7359588.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,432,0,1000,4.93,13.79,5.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,1,1000,26.29,33.05,30.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,2,1000,27.06,35.8,31.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,4,1000,31.95,48.91,41.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,8,1000,45.97,61.56,53.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,16,1000,40.56,55.54,48.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,32,1000,62.58,90.8,78.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,64,1000,96.12,146.18,131.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,128,1000,220.16,304.82,272.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,256,1000,193.59,284.42,259.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,512,1000,350.51,470.35,437.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,1024,1000,623.22,706.7,681.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,2048,1000,1052.01,1426.48,1164.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,4096,1000,1646.52,2200.89,1905.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,8192,1000,1948.63,2134.16,2052.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,16384,1000,3803.33,4508.83,4145.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,32768,1000,7519.86,8653.66,8131.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,65536,640,13907.85,15860.66,14879.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,131072,297,25688.78,29942.76,27868.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,262144,160,48772.57,55197.48,52190.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,524288,80,111354.93,115807.1,113429.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,1048576,40,198591.95,215330.09,208485.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,2097152,20,486262.65,497539.47,491411.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,432,4194304,10,985363.36,1005363.94,994597.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,576,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,1,1000,112.68,123.03,116.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,2,1000,115.22,130.21,121.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,4,1000,129.48,148.0,136.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,8,1000,178.61,202.04,189.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,16,1000,164.04,178.44,173.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,32,1000,249.08,281.13,271.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,64,1000,432.61,494.59,474.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,128,1000,820.61,936.76,897.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,256,1000,2863.37,3053.07,2931.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,512,1000,2749.11,2779.47,2761.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,1024,1000,4993.73,5327.36,5213.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,2048,1000,10121.2,10241.77,10218.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,4096,1000,15782.01,15818.3,15801.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,8192,1000,30026.82,30125.05,30057.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,16384,1000,61490.64,61705.08,61573.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,32768,570,121020.6,121458.09,121229.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,65536,86,254169.97,255884.56,254806.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,131072,79,461812.92,462518.87,462124.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,262144,17,870048.4,874041.95,871186.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,524288,17,1769318.74,1772563.94,1770533.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Alltoall,576,1048576,12,3401545.19,3413244.99,3406651.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allgather,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,1,1000,10.57,16.73,13.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,2,1000,10.88,16.99,13.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,4,1000,15.87,21.35,18.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,8,1000,15.41,23.46,18.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,16,1000,19.03,32.5,24.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,32,1000,17.33,25.9,22.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,64,1000,41.97,73.53,60.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,128,1000,37.96,59.65,55.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,256,1000,73.91,122.28,115.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,512,1000,156.82,204.4,195.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,1024,1000,283.96,392.22,362.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,2048,1000,361.54,422.5,402.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,4096,1000,662.02,765.06,733.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,8192,1000,921.0,1019.96,966.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,16384,1000,1725.57,1999.2,1865.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,32768,1000,3348.54,4028.13,3714.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,65536,640,6109.06,7840.18,7055.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,131072,320,11323.31,15691.65,13379.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,262144,160,24153.56,34082.06,29876.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,524288,80,45574.32,46673.77,46103.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,1048576,40,114311.24,123854.17,118628.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,2097152,20,227370.84,235668.47,231962.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,4194304,10,463107.31,479481.28,472209.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,144,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,4,1000,6.22,9.73,8.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,8,1000,4.8,8.19,6.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,16,1000,6.12,9.97,8.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,32,1000,4.81,8.18,6.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,64,1000,8.29,13.14,10.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,128,1000,7.24,14.1,10.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,256,1000,8.74,15.71,11.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,512,1000,10.75,17.67,13.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,1024,1000,10.06,14.74,11.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,2048,1000,23.79,51.16,37.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,4096,1000,14.29,18.51,15.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,8192,1000,33.25,72.87,62.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,16384,1000,73.83,104.37,90.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,32768,1000,54.36,66.1,58.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,65536,640,77.52,92.55,82.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,131072,320,133.47,157.46,141.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,262144,160,240.81,285.72,256.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,524288,80,520.59,605.55,540.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,1048576,40,1434.87,1532.38,1475.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,2097152,20,2643.71,2843.08,2736.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,144,4194304,10,5228.56,5247.75,5239.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,288,0,1000,7.63,13.33,9.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,1,1000,8.07,14.88,10.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,2,1000,9.19,17.85,12.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,4,1000,9.41,18.08,12.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,8,1000,8.34,15.58,11.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,16,1000,8.94,15.95,11.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,32,1000,9.45,17.19,12.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,64,1000,10.11,19.39,14.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,128,1000,12.15,22.84,16.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,256,1000,14.8,30.55,22.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,512,1000,19.61,45.81,35.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,1024,1000,22.28,58.97,46.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,2048,1000,29.86,93.78,72.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,4096,1000,16.79,174.22,103.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,8192,1000,43.36,311.8,190.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,16384,1000,35.34,442.25,293.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,32768,1000,43.04,785.98,560.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,65536,640,43.18,1816.44,1154.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,131072,320,237.36,4894.37,2627.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,262144,160,350.3,5303.48,3915.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,524288,80,583.07,18239.81,11618.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,1048576,40,1112.13,36899.6,24719.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,2097152,20,1742.0,71232.36,49435.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,4194304,10,4089.0,161047.62,102965.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,1,1000,0.98,8.79,3.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,2,1000,1.06,10.23,4.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,4,1000,1.32,12.56,5.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,8,1000,1.51,10.59,5.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,16,1000,2.37,14.17,5.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,32,1000,3.67,13.47,7.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,64,1000,4.79,17.66,10.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,128,1000,6.5,23.26,14.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,256,1000,9.32,32.73,22.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,512,1000,15.25,59.24,42.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,1024,1000,25.34,88.55,68.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,2048,1000,31.57,156.34,114.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,4096,1000,49.42,240.98,183.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,8192,1000,88.75,453.22,331.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,16384,1000,164.91,798.1,579.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,32768,1000,17.99,897.57,413.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,65536,640,26.37,1235.34,600.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,131072,320,89.38,2377.65,1226.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,262144,160,197.45,4787.58,2729.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,524288,80,185.82,9309.36,6161.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,1048576,40,348.13,18588.13,13870.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,2097152,20,10404.14,37183.36,29353.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,4194304,10,23610.38,74335.8,60676.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,504,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,1,1000,96.67,105.67,100.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,2,1000,99.8,108.43,103.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,4,1000,116.39,130.36,123.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,8,1000,135.0,157.19,145.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,16,1000,140.99,161.29,151.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,32,1000,205.45,242.53,225.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,64,1000,356.65,429.02,397.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,128,1000,664.22,807.72,753.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,256,1000,4585.32,4938.58,4769.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,512,1000,3535.25,3783.66,3643.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,1024,1000,5866.61,6108.32,5972.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,2048,1000,6763.5,6773.76,6767.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,4096,1000,11784.65,11801.76,11791.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,8192,1000,26613.05,26726.5,26683.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,16384,1000,48585.12,48650.12,48610.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,32768,419,93168.83,93404.7,93263.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,65536,282,219448.69,220923.58,220171.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,131072,133,373249.58,374068.3,373691.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,262144,33,764856.87,766397.64,765511.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,524288,24,1461043.85,1464006.24,1462611.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,1048576,13,2816470.48,2817955.54,2817233.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,2097152,7,5561989.43,5566037.38,5564097.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,288,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,1,1000,0.97,4.47,3.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,2,1000,1.1,5.81,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,4,1000,1.1,5.83,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,8,1000,1.1,5.75,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,16,1000,1.11,5.74,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,32,1000,1.14,6.09,4.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,64,1000,1.13,5.81,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,128,1000,1.17,5.9,4.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,256,1000,1.22,6.2,5.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,512,1000,1.07,6.46,4.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,1024,1000,1.16,5.4,4.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,2048,1000,2.03,6.42,4.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,4096,1000,4.23,9.96,7.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,8192,1000,7.25,16.33,11.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,16384,1000,13.05,27.46,23.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,32768,1000,18.4,44.61,37.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,65536,640,37.37,62.68,54.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,131072,320,69.34,109.23,96.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,262144,160,151.03,195.36,179.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,524288,80,308.64,339.32,329.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,1048576,40,624.48,664.18,650.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,2097152,20,1171.32,1202.44,1198.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Bcast,288,4194304,10,2408.21,2450.59,2436.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,360,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,1,1000,1.13,10.14,5.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,2,1000,1.23,12.25,6.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,4,1000,1.48,14.19,7.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,8,1000,1.82,12.25,6.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,16,1000,2.87,12.39,7.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,32,1000,4.43,15.77,9.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,64,1000,6.45,19.6,12.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,128,1000,10.26,26.44,17.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,256,1000,18.68,38.01,26.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,512,1000,28.37,72.51,52.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,1024,1000,43.99,98.95,75.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,2048,1000,52.53,158.73,116.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,4096,1000,84.01,269.7,194.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,8192,1000,148.6,506.52,354.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,16384,1000,271.91,901.26,632.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,32768,1000,32.16,1268.99,613.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,65536,640,47.38,2389.03,970.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,131072,320,89.65,3204.45,1672.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,262144,160,195.47,6208.03,3481.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,524288,80,245.76,12387.93,8173.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,1048576,40,5343.85,24788.75,18554.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,2097152,20,5718.99,49723.72,39721.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,4194304,10,14888.06,98882.01,81608.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,216,0,1000,6.81,12.37,9.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,1,1000,7.7,14.33,10.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,2,1000,7.78,14.45,10.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,4,1000,7.86,15.01,11.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,8,1000,6.9,13.18,9.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,16,1000,7.63,14.62,10.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,32,1000,7.93,14.76,10.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,64,1000,9.52,17.16,12.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,128,1000,10.94,19.7,14.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,256,1000,12.96,24.68,17.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,512,1000,19.8,46.59,29.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,1024,1000,18.2,47.31,36.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,2048,1000,22.52,74.08,56.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,4096,1000,14.3,158.92,94.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,8192,1000,40.32,293.16,170.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,16384,1000,50.56,512.46,293.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,32768,1000,58.75,955.95,513.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,65536,640,53.89,1019.31,646.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,131072,320,71.71,1991.49,1206.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,262144,160,357.69,5781.97,3616.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,524288,80,572.66,17852.62,10242.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,1048576,40,1141.43,36863.99,20677.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,2097152,20,1845.85,74600.57,43593.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,4194304,10,4259.22,155513.71,89297.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,432,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,1,1000,17.61,26.09,22.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,2,1000,16.05,26.35,20.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,4,1000,17.57,27.88,22.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,8,1000,26.64,39.68,32.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,16,1000,32.12,49.65,41.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,32,1000,56.29,83.86,71.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,64,1000,44.39,92.89,77.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,128,1000,74.04,152.28,134.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,256,1000,149.96,242.67,217.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,512,1000,307.7,414.44,385.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,1024,1000,609.33,694.78,668.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,2048,1000,824.05,938.88,902.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,4096,1000,1400.66,1595.02,1516.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,8192,1000,1948.19,2106.76,2025.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,16384,1000,3716.5,4155.9,3942.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,32768,1000,8048.78,9212.29,8617.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,65536,640,15294.88,18230.99,16810.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,131072,277,27113.54,33434.82,30532.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,262144,160,51455.53,67828.68,59115.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,524288,80,97229.93,100523.93,99036.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,1048576,40,218138.5,234345.55,226152.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,2097152,20,507575.6,540680.44,526447.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,432,4194304,10,982236.17,1053884.06,1033775.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgatherv,288,0,1000,3.54,9.14,3.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,1,1000,20.95,27.39,24.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,2,1000,22.98,29.21,26.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,4,1000,23.97,33.02,28.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,8,1000,27.29,39.3,33.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,16,1000,29.44,39.6,35.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,32,1000,43.66,59.57,53.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,64,1000,87.37,107.77,103.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,128,1000,107.84,151.89,138.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,256,1000,139.94,204.35,191.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,512,1000,241.95,320.36,299.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,1024,1000,387.19,422.06,416.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,2048,1000,494.3,523.08,514.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,4096,1000,768.11,862.42,812.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,8192,1000,1592.49,2012.27,1797.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,16384,1000,2403.85,2725.12,2574.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,32768,1000,5084.1,5918.33,5572.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,65536,640,8272.72,9381.7,8864.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,131072,320,15765.1,17667.6,16790.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,262144,160,29713.78,33490.6,31608.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,524288,80,60174.37,61321.17,60720.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,1048576,40,130692.34,135512.74,132434.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,2097152,20,306921.18,316159.26,311175.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,4194304,10,731431.84,757103.4,744569.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,360,0,1000,4.23,11.23,4.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,1,1000,24.79,32.24,28.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,2,1000,26.35,34.58,29.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,4,1000,35.09,44.1,39.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,8,1000,41.07,53.03,47.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,16,1000,40.8,56.3,47.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,32,1000,56.47,77.11,68.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,64,1000,86.15,133.57,119.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,128,1000,191.56,251.67,229.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,256,1000,152.91,253.49,231.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,512,1000,302.42,396.04,368.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,1024,1000,440.59,567.58,534.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,2048,1000,748.9,1523.28,931.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,4096,1000,1004.67,1222.24,1123.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,8192,1000,1652.19,1788.99,1717.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,16384,1000,3029.95,3338.31,3190.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,32768,1000,6064.45,6786.23,6442.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,65536,640,11746.59,14140.79,13052.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,131072,320,21514.17,26101.7,23962.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,262144,160,39515.62,44542.02,41902.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,524288,80,84178.15,87878.09,86237.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,1048576,40,173559.15,178171.34,176629.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,2097152,20,401815.91,417219.79,408471.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgatherv,360,4194304,10,830812.95,901641.54,872761.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,432,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,1,1000,1.72,6.54,5.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,2,1000,1.77,6.66,5.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,4,1000,1.75,6.57,5.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,8,1000,1.75,6.52,5.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,16,1000,1.65,6.49,5.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,32,1000,1.66,6.54,5.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,64,1000,1.67,6.55,5.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,128,1000,1.72,6.76,5.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,256,1000,1.82,7.46,5.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,512,1000,1.46,7.28,4.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,1024,1000,1.15,9.94,6.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,2048,1000,2.1,12.22,7.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,4096,1000,3.79,17.03,11.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,8192,1000,7.21,23.74,17.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,16384,1000,11.36,35.84,28.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,32768,1000,23.03,72.94,58.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,65536,640,55.43,182.91,97.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,131072,320,128.21,320.3,182.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,262144,160,149.81,213.75,194.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,524288,80,308.8,387.87,360.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,1048576,40,615.18,745.94,699.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,2097152,20,1221.82,1451.78,1372.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,4194304,10,2487.21,2952.62,2766.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,216,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,1,1000,0.81,5.65,4.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,2,1000,0.81,5.61,4.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,4,1000,0.8,5.65,4.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,8,1000,0.81,5.7,4.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,16,1000,0.81,5.56,4.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,32,1000,0.81,5.64,4.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,64,1000,0.85,5.7,4.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,128,1000,0.87,5.82,4.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,256,1000,0.97,6.13,4.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,512,1000,0.87,4.45,3.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,1024,1000,1.01,5.09,4.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,2048,1000,1.62,6.04,4.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,4096,1000,3.64,9.26,7.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,8192,1000,6.05,13.72,11.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,16384,1000,10.17,22.37,18.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,32768,1000,16.45,36.68,31.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,65536,640,37.1,56.06,52.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,131072,320,61.12,108.66,93.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,262144,160,130.89,194.26,174.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,524288,80,259.59,338.95,312.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,1048576,40,532.07,660.57,614.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,2097152,20,1068.55,1284.76,1213.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,216,4194304,10,2233.06,2582.43,2464.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,144,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,1,1000,9.26,12.36,10.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,2,1000,11.81,17.19,14.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,4,1000,12.12,18.04,14.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,8,1000,38.51,83.04,65.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,16,1000,15.88,33.16,24.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,32,1000,20.72,35.14,28.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,64,1000,16.97,27.56,23.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,128,1000,24.71,65.5,47.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,256,1000,82.02,117.79,107.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,512,1000,89.82,153.35,140.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,1024,1000,187.46,254.41,237.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,2048,1000,246.71,280.16,270.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,4096,1000,460.53,487.15,479.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,8192,1000,906.49,933.17,925.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,16384,1000,1065.67,1350.08,1210.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,32768,1000,2049.88,2658.17,2370.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,65536,640,3934.58,5068.27,4539.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,131072,320,8763.18,11684.88,10190.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,262144,160,15793.14,21271.18,18524.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,524288,80,29828.24,31021.35,30321.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,1048576,40,66274.39,67470.55,66904.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,2097152,20,152919.25,160346.29,156313.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,4194304,10,306392.56,315129.92,310290.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,360,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,1,1000,16.97,24.01,20.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,2,1000,15.32,23.48,19.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,4,1000,15.48,26.33,21.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,8,1000,36.74,47.22,42.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,16,1000,41.2,123.11,117.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,32,1000,61.78,83.64,75.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,64,1000,38.94,86.87,72.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,128,1000,57.83,129.07,113.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,256,1000,116.66,218.48,195.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,512,1000,251.93,341.5,313.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,1024,1000,366.97,469.35,448.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,2048,1000,544.12,708.87,676.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,4096,1000,1417.2,2062.98,1643.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,8192,1000,1604.21,1751.74,1679.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,16384,1000,3055.81,3360.38,3208.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,32768,1000,6037.96,6858.48,6421.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,65536,640,11168.82,13141.89,12066.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,131072,320,20916.24,25917.18,22679.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,262144,160,41080.41,59282.3,49319.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,524288,80,89755.41,93460.99,91510.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,1048576,40,174125.64,180537.11,176406.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,2097152,20,382006.11,394057.29,387057.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,4194304,10,778495.96,801549.8,789961.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,504,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,4,1000,7.32,18.91,9.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,8,1000,11.93,16.87,14.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,16,1000,24.74,42.93,40.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,32,1000,9.85,13.12,11.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,64,1000,10.9,16.55,13.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,128,1000,12.6,19.57,15.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,256,1000,13.99,22.34,17.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,512,1000,14.7,21.25,17.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,1024,1000,19.06,26.41,22.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,2048,1000,19.19,25.6,21.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,4096,1000,25.19,32.83,28.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,8192,1000,54.61,65.25,59.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,16384,1000,106.76,123.57,114.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,32768,1000,71.23,92.51,79.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,65536,640,99.28,126.14,111.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,131072,320,167.65,207.74,185.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,262144,160,303.37,376.24,334.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,524288,80,700.31,840.3,761.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,1048576,40,1701.75,1991.15,1915.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,2097152,20,3536.5,3757.8,3712.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,504,4194304,10,6090.96,6479.93,6406.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,360,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,1,1000,0.5,11.78,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,2,1000,0.55,14.65,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,4,1000,0.55,14.54,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,8,1000,0.49,12.61,1.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,16,1000,0.46,13.88,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,32,1000,0.46,15.61,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,64,1000,0.47,20.33,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,128,1000,0.49,31.92,1.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,256,1000,0.56,45.01,2.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,512,1000,0.89,92.17,4.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,1024,1000,0.99,177.13,6.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,2048,1000,1.29,209.63,8.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,4096,1000,2.16,333.88,12.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,8192,1000,3.83,638.7,23.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,16384,1000,8.03,1200.78,43.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,32768,1000,14.23,3012.16,86.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,65536,640,32.83,2455.66,1362.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,131072,320,81.68,4595.0,2492.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,262144,160,164.12,9123.55,4961.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,524288,80,314.45,18311.76,10001.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,1048576,40,233.94,36747.9,19914.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,2097152,20,2401.14,73200.28,41005.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,4194304,10,11913.15,130965.02,69796.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,648,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,4,1000,8.63,12.2,10.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,8,1000,9.33,13.61,11.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,16,1000,9.94,17.01,11.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,32,1000,9.68,17.62,11.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,64,1000,11.44,17.37,13.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,128,1000,13.01,19.92,16.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,256,1000,14.52,25.75,17.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,512,1000,14.83,21.95,17.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,1024,1000,20.17,27.88,23.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,2048,1000,22.05,29.91,25.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,4096,1000,25.79,32.03,29.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,8192,1000,43.42,54.45,50.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,16384,1000,80.38,110.05,96.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,32768,1000,260.74,295.23,278.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,65536,640,109.52,141.4,119.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,131072,320,170.87,217.02,188.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,262144,160,320.52,393.82,344.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,524288,80,670.16,821.13,715.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,1048576,40,1715.26,2044.97,1845.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,2097152,20,3487.82,3707.79,3559.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Allreduce,648,4194304,10,6277.48,6672.75,6391.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Scatter,504,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,1,1000,1.23,13.66,6.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,2,1000,1.42,13.14,8.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,4,1000,1.7,13.2,8.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,8,1000,2.1,12.05,7.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,16,1000,3.37,27.7,9.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,32,1000,5.72,18.82,12.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,64,1000,8.48,25.07,17.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,128,1000,13.81,32.9,24.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,256,1000,26.36,52.61,39.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,512,1000,48.29,80.16,61.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,1024,1000,78.04,110.48,91.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,2048,1000,121.84,528.95,150.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,4096,1000,218.83,321.5,261.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,8192,1000,403.3,607.27,481.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,16384,1000,775.69,1104.7,899.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,32768,1000,33.12,1829.57,861.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,65536,640,25.02,2466.57,1237.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,131072,320,94.12,4877.4,2686.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,262144,160,184.56,9297.66,5192.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,524288,80,277.42,18562.05,12454.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,1048576,40,4431.12,37015.58,28247.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,2097152,20,3228.8,74041.41,59807.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,4194304,10,7007.2,148022.41,124614.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,0,1000,0.03,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,1,1000,2.04,7.17,5.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,2,1000,2.03,7.03,5.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,4,1000,2.04,6.97,5.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,8,1000,2.03,6.98,5.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,16,1000,1.93,6.8,5.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,32,1000,1.93,6.87,5.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,64,1000,1.93,6.93,5.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,128,1000,2.01,7.09,5.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,256,1000,2.09,7.83,6.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,512,1000,1.65,7.51,4.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,1024,1000,1.32,10.74,7.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,2048,1000,2.08,11.69,8.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,4096,1000,3.78,15.94,12.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,8192,1000,6.82,21.84,17.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,16384,1000,14.65,44.11,37.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,32768,1000,24.03,76.51,61.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,65536,640,60.46,159.69,106.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,131072,320,93.72,141.19,125.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,262144,160,151.28,215.91,200.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,524288,80,314.69,388.68,373.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,1048576,40,618.85,740.01,716.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,2097152,20,1220.81,1448.33,1404.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,4194304,10,2509.66,2945.06,2832.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,720,0,1000,2.62,3.15,2.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,4,1000,3.19,26.44,4.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,8,1000,3.21,21.59,3.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,16,1000,3.23,44.96,4.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,32,1000,2.95,27.84,6.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,64,1000,2.93,27.51,7.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,128,1000,2.96,26.51,7.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,256,1000,2.99,32.21,9.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,512,1000,3.26,52.51,14.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,1024,1000,3.67,45.68,19.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,2048,1000,11.6,52.46,38.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,4096,1000,47.95,62.96,55.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,8192,1000,90.08,114.35,99.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,16384,1000,145.43,171.96,162.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,32768,1000,229.27,249.88,240.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,65536,640,402.68,445.81,432.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,131072,320,324.81,664.95,494.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,262144,160,665.32,1025.41,851.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,524288,80,1398.56,1575.96,1484.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,1048576,40,9702.47,15742.67,10220.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,2097152,20,4050.88,4990.16,4167.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,4194304,10,4959.18,5201.77,5105.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,216,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,4,1000,5.95,8.96,7.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,8,1000,5.07,8.22,6.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,16,1000,5.39,8.5,6.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,32,1000,5.16,8.24,6.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,64,1000,7.02,11.9,9.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,128,1000,8.65,15.71,11.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,256,1000,10.69,18.13,13.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,512,1000,8.53,12.86,10.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,1024,1000,12.07,17.17,14.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,2048,1000,11.09,15.77,12.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,4096,1000,16.21,20.72,17.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,8192,1000,33.27,42.44,35.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,16384,1000,73.78,86.66,78.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,32768,1000,84.24,105.03,92.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,65536,640,86.33,111.74,95.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,131072,320,151.24,189.65,165.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,262144,160,277.75,348.23,305.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,524288,80,593.72,754.37,672.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,1048576,40,1642.86,1704.94,1668.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,2097152,20,3036.77,3152.46,3063.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,216,4194304,10,5237.8,5274.63,5257.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,432,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,1,1000,0.49,12.48,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,2,1000,0.55,14.54,1.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,4,1000,0.55,15.69,1.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,8,1000,0.49,13.0,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,16,1000,0.46,13.88,1.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,32,1000,0.46,16.25,1.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,64,1000,0.47,21.94,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,128,1000,0.49,28.73,1.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,256,1000,0.53,46.62,2.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,512,1000,0.87,92.22,3.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,1024,1000,1.04,195.0,5.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,2048,1000,1.3,221.16,9.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,4096,1000,2.32,365.27,13.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,8192,1000,4.03,708.91,24.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,16384,1000,8.0,1364.87,45.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,32768,1000,14.24,3564.19,88.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,65536,640,33.16,2950.05,1639.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,131072,320,85.42,5435.55,2969.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,262144,160,160.39,12616.47,5788.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,524288,80,316.19,21500.91,11765.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,1048576,40,232.5,42935.8,23389.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,2097152,20,1541.23,85835.56,47844.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,4194304,10,11427.24,155717.72,82565.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,288,0,1000,0.06,0.09,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,4,1000,0.34,7.14,0.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,8,1000,0.32,7.59,0.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,16,1000,0.35,8.87,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,32,1000,0.35,9.27,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,64,1000,0.36,9.49,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,128,1000,0.34,10.36,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,256,1000,0.34,11.21,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,512,1000,0.32,9.14,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,1024,1000,0.33,10.26,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,2048,1000,0.41,12.24,1.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,4096,1000,0.73,15.18,1.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,8192,1000,2.63,24.53,4.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,16384,1000,7.25,37.8,11.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,32768,1000,37.2,160.88,102.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,65536,640,74.42,178.54,136.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,131072,320,158.5,318.07,260.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,262144,160,86.59,754.37,392.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,524288,80,131.75,860.29,474.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,1048576,40,219.25,1254.01,704.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,2097152,20,482.97,1857.34,1540.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,4194304,10,700.55,3975.04,2148.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,432,0,1000,3.47,11.54,7.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,1,1000,51.34,313.22,221.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,2,1000,50.55,313.29,221.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,4,1000,51.24,376.58,222.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,8,1000,50.68,315.33,222.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,16,1000,50.96,316.32,223.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,32,1000,51.15,323.39,229.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,64,1000,51.26,367.77,266.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,128,1000,52.77,372.13,269.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,256,1000,54.96,381.95,279.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,512,1000,74.17,435.44,326.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,1024,1000,93.76,532.7,411.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,2048,1000,99.04,628.04,490.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,4096,1000,107.46,706.77,561.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,8192,1000,136.53,962.58,784.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,16384,1000,189.77,1595.05,1316.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,32768,1000,281.26,3439.56,2476.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,65536,640,456.41,3828.2,2017.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,131072,320,804.11,5795.88,3407.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,262144,160,1446.37,11090.58,6404.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,524288,80,3213.89,21622.52,12404.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,1048576,40,12169.99,42832.11,25262.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,2097152,20,25078.2,86344.51,51240.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gatherv,432,4194304,10,35276.25,157757.78,87579.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,1,1000,83.81,91.48,87.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,2,1000,86.07,94.4,90.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,4,1000,93.87,105.74,99.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,8,1000,113.13,131.14,121.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,16,1000,111.65,126.64,119.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,32,1000,355.09,735.05,476.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,64,1000,287.38,335.71,313.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,128,1000,521.93,627.89,585.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,256,1000,1471.56,1502.79,1488.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,512,1000,1936.71,1966.85,1953.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,1024,1000,3823.95,4080.75,3959.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,2048,1000,5720.28,5734.86,5727.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,4096,1000,11485.36,11588.81,11527.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,8192,1000,21366.33,21401.33,21385.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,16384,1000,42559.3,42655.35,42602.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,32768,798,83315.06,83489.77,83374.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,65536,35,614119.08,645116.29,637349.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,131072,35,326460.77,328314.33,327772.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,262144,35,605400.84,605689.53,605525.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,524288,35,1220491.8,1223464.29,1221834.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,1048576,17,2400724.43,2407984.77,2404588.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Alltoall,432,2097152,9,4691456.3,4711832.76,4697013.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,360,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,4,1000,6.17,23.7,8.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,8,1000,6.24,10.39,8.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,16,1000,8.27,11.27,9.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,32,1000,11.68,16.15,14.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,64,1000,27.76,294.42,265.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,128,1000,18.56,28.5,24.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,256,1000,16.87,32.52,27.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,512,1000,12.61,18.71,15.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,1024,1000,16.87,23.72,19.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,2048,1000,19.44,30.89,21.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,4096,1000,22.0,28.4,24.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,8192,1000,39.58,48.39,42.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,16384,1000,93.02,114.54,101.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,32768,1000,63.0,80.06,68.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,65536,640,95.69,120.91,104.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,131072,320,165.16,204.47,177.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,262144,160,349.97,414.9,372.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,524288,80,626.85,770.51,681.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,1048576,40,1611.9,1965.79,1788.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,2097152,20,3502.0,3728.87,3608.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,360,4194304,10,6071.02,6477.68,6240.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Alltoall,432,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,1,1000,83.68,91.84,87.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,2,1000,86.56,96.24,90.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,4,1000,94.17,111.15,101.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,8,1000,119.84,146.6,132.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,16,1000,115.37,129.84,123.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,32,1000,168.7,194.7,182.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,64,1000,294.62,347.0,320.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,128,1000,521.24,630.04,585.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,256,1000,1495.01,1528.79,1513.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,512,1000,1935.64,1967.86,1953.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,1024,1000,3288.84,3329.13,3311.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,2048,1000,5259.44,5268.7,5263.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,4096,1000,9614.34,9629.98,9620.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,8192,1000,22302.73,22362.94,22328.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,16384,1000,37790.21,37859.18,37820.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,32768,799,82389.02,82530.65,82452.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,65536,30,184717.65,187188.48,185466.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,131072,19,297612.79,297796.71,297710.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,262144,19,590295.88,590643.91,590434.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,524288,19,1222252.97,1227975.87,1225304.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,1048576,16,2325104.72,2326458.69,2325839.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,2097152,9,4629037.42,4631918.19,4630475.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,0,1000,1.71,1.87,1.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,4,1000,2.25,14.3,3.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,8,1000,2.29,16.29,3.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,16,1000,2.3,17.0,3.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,32,1000,2.29,19.01,3.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,64,1000,2.05,18.52,4.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,128,1000,2.07,20.15,5.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,256,1000,2.07,21.88,6.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,512,1000,2.33,30.91,10.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,1024,1000,2.64,31.43,17.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,2048,1000,26.18,38.63,32.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,4096,1000,33.9,49.21,42.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,8192,1000,48.01,67.74,60.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,16384,1000,99.95,125.29,113.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,32768,1000,183.0,215.5,203.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,65536,640,272.42,383.6,344.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,131072,320,713.82,801.7,763.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,262144,160,726.18,852.46,777.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,524288,80,1161.75,1308.35,1230.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,1048576,40,1643.13,1787.68,1716.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,2097152,20,2870.8,3021.22,2947.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,4194304,10,4594.57,4742.44,4677.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,288,0,1000,1.27,1.37,1.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,4,1000,1.84,24.5,2.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,8,1000,1.83,34.6,3.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,16,1000,1.83,27.06,3.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,32,1000,1.58,20.31,5.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,64,1000,1.59,29.27,6.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,128,1000,1.61,22.58,6.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,256,1000,2.75,23.43,9.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,512,1000,2.79,27.37,12.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,1024,1000,8.54,27.01,20.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,2048,1000,22.35,34.5,27.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,4096,1000,31.52,43.19,37.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,8192,1000,51.18,64.91,57.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,16384,1000,93.05,111.58,102.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,32768,1000,171.97,200.0,189.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,65536,640,258.81,336.7,293.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,131072,320,307.98,469.7,394.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,262144,160,650.9,739.82,684.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,524288,80,919.47,1023.17,965.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,1048576,40,1397.12,1500.71,1441.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,2097152,20,2391.34,2515.64,2449.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,288,4194304,10,3722.98,4221.97,3966.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatterv,288,0,1000,7.69,13.37,9.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,1,1000,8.2,15.03,10.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,2,1000,9.19,17.41,12.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,4,1000,9.47,17.93,12.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,8,1000,8.4,15.62,11.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,16,1000,8.73,15.63,11.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,32,1000,9.43,16.82,12.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,64,1000,10.33,19.65,14.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,128,1000,12.45,22.78,16.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,256,1000,15.3,29.65,22.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,512,1000,22.56,46.94,35.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,1024,1000,21.78,56.3,44.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,2048,1000,14.56,90.04,63.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,4096,1000,15.4,148.46,95.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,8192,1000,40.6,284.43,181.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,16384,1000,49.09,516.09,328.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,32768,1000,39.39,807.93,542.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,65536,640,55.88,1707.63,1085.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,131072,320,239.75,2725.96,2097.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,262144,160,348.12,5761.92,4170.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,524288,80,629.92,17461.57,11342.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,1048576,40,1095.57,36339.8,24069.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,2097152,20,1839.48,74472.38,50098.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,4194304,10,4082.84,154891.11,101934.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,0,1000,0.05,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,4,1000,5.22,8.03,6.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,8,1000,6.3,9.67,7.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,16,1000,6.59,10.22,8.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,32,1000,6.45,9.8,7.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,64,1000,8.26,13.48,10.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,128,1000,8.95,15.86,11.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,256,1000,10.04,17.51,13.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,512,1000,8.8,13.02,10.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,1024,1000,12.35,17.57,14.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,2048,1000,12.58,17.19,14.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,4096,1000,16.9,21.28,18.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,8192,1000,35.62,43.25,39.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,16384,1000,86.75,101.86,89.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,32768,1000,79.23,98.53,87.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,65536,640,95.44,116.24,103.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,131072,320,154.91,192.16,168.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,262144,160,289.36,352.32,309.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,524288,80,641.81,780.29,681.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,1048576,40,1891.25,2459.95,2185.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,2097152,20,3184.88,3223.94,3213.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,4194304,10,5331.63,5385.72,5361.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,504,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,1,1000,1.85,6.85,4.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,2,1000,2.0,7.02,5.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,4,1000,2.0,6.89,5.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,8,1000,2.0,6.85,5.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,16,1000,1.9,6.81,5.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,32,1000,1.94,6.79,5.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,64,1000,1.93,6.87,5.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,128,1000,2.0,7.06,5.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,256,1000,2.06,7.78,5.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,512,1000,1.69,6.74,5.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,1024,1000,1.29,9.74,6.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,2048,1000,2.35,16.18,8.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,4096,1000,4.27,17.62,13.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,8192,1000,6.89,21.9,17.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,16384,1000,10.61,33.05,27.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,32768,1000,22.71,73.55,59.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,65536,640,60.34,315.32,107.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,131072,320,125.35,204.43,181.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,262144,160,151.66,217.96,201.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,524288,80,325.18,387.75,374.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,1048576,40,990.83,10177.88,1116.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,2097152,20,1237.71,1588.46,1416.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Bcast,504,4194304,10,2615.49,4328.26,3006.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,648,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,4,1000,8.81,12.06,10.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,8,1000,10.63,13.86,12.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,16,1000,9.9,12.94,11.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,32,1000,10.4,13.45,11.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,64,1000,11.54,17.38,14.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,128,1000,11.79,19.16,15.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,256,1000,14.39,22.57,17.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,512,1000,18.48,25.4,21.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,1024,1000,18.32,30.01,21.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,2048,1000,22.56,30.88,26.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,4096,1000,24.15,29.97,27.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,8192,1000,43.74,54.58,50.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,16384,1000,82.69,112.62,99.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,32768,1000,283.2,323.23,302.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,65536,640,145.14,182.17,157.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,131072,320,177.51,223.4,194.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,262144,160,315.31,392.09,341.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,524288,80,771.68,926.29,815.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,1048576,40,1717.9,2050.61,1849.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,2097152,20,3501.26,3707.06,3577.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,4194304,10,6252.05,6617.17,6344.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Alltoall,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,1,1000,46.28,49.82,47.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,2,1000,45.95,49.53,47.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,4,1000,49.47,54.82,52.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,8,1000,54.32,60.62,57.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,16,1000,63.91,74.75,68.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,32,1000,66.32,82.65,74.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,64,1000,99.74,136.21,123.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,128,1000,182.0,240.98,217.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,256,1000,1014.92,1103.26,1068.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,512,1000,857.55,964.79,927.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,1024,1000,1152.09,1251.28,1217.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,2048,1000,2192.19,2292.74,2253.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,4096,1000,4357.87,4378.37,4366.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,8192,1000,8761.55,8855.2,8804.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,16384,1000,15425.41,15478.71,15448.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,32768,1000,33021.81,33151.1,33072.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,65536,640,73162.0,74273.74,73819.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,131072,320,118665.8,118867.04,118730.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,262144,160,245975.29,246860.87,246231.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,524288,72,486244.88,487056.55,486695.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,1048576,40,952787.42,954559.15,953678.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,2097152,20,1907175.4,1910557.91,1908730.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,4194304,10,3821424.85,3839239.76,3828109.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,1,1000,51.66,68.1,62.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,2,1000,47.45,51.45,49.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,4,1000,56.72,63.29,59.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,8,1000,55.71,62.05,58.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,16,1000,61.31,69.95,65.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,32,1000,66.71,82.48,74.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,64,1000,102.28,134.33,121.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,128,1000,183.32,246.95,218.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,256,1000,989.8,1058.01,1036.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,512,1000,786.85,836.76,822.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,1024,1000,1181.66,1230.37,1219.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,2048,1000,2480.32,2784.41,2665.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,4096,1000,4235.76,4295.06,4249.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,8192,1000,8184.86,8280.45,8249.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,16384,1000,15437.1,15487.49,15456.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,32768,1000,32769.92,32905.87,32832.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,65536,57,110764.66,115203.0,113611.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,131072,15,119130.24,119418.34,119231.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,262144,15,234268.72,234574.05,234444.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,524288,15,471836.92,472198.43,472004.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,1048576,15,979838.29,985415.98,982015.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,2097152,15,1890548.87,1893163.56,1891931.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Alltoall,216,4194304,10,3774214.25,3778912.37,3776786.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,144,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,1,1000,2.88,5.83,4.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,2,1000,1.13,4.93,3.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,4,1000,3.14,15.21,5.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,8,1000,3.37,7.02,5.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,16,1000,1.58,6.84,4.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,32,1000,2.64,7.61,4.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,64,1000,5.43,10.99,8.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,128,1000,7.61,15.24,11.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,256,1000,9.63,21.89,16.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,512,1000,10.16,36.32,25.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,1024,1000,14.79,54.63,43.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,2048,1000,24.41,103.56,88.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,4096,1000,30.97,176.77,156.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,8192,1000,52.47,340.56,293.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,16384,1000,92.55,563.36,463.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,32768,1000,42.56,557.57,261.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,65536,640,29.57,418.32,243.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,131072,320,72.71,817.96,436.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,262144,160,234.95,1584.06,1266.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,524288,80,237.25,3150.54,2801.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,1048576,40,330.36,6271.05,5786.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,2097152,20,3445.47,12573.4,11717.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,4194304,10,23662.43,76260.74,48127.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,360,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,1,1000,1.44,6.39,4.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,2,1000,1.52,6.49,5.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,4,1000,1.5,9.86,4.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,8,1000,1.5,10.34,5.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,16,1000,1.39,6.41,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,32,1000,1.41,6.36,4.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,64,1000,1.41,6.41,4.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,128,1000,1.45,6.48,5.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,256,1000,1.54,6.99,5.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,512,1000,1.33,7.17,4.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,1024,1000,0.97,9.13,6.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,2048,1000,1.58,11.32,8.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,4096,1000,2.96,16.54,11.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,8192,1000,5.73,23.67,18.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,16384,1000,8.98,33.17,27.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,32768,1000,19.03,72.23,58.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,65536,640,37.51,86.37,75.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,131072,320,69.69,126.58,110.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,262144,160,149.08,214.18,190.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,524288,80,260.9,386.97,356.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,1048576,40,528.54,742.57,692.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,2097152,20,1051.7,1557.03,1390.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,4194304,10,2283.73,25172.82,7282.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,1,1000,1.19,7.87,4.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,2,1000,1.19,7.74,4.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,4,1000,1.26,7.85,4.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,8,1000,1.35,7.03,4.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,16,1000,2.28,8.2,5.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,32,1000,3.12,8.98,6.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,64,1000,4.66,11.91,8.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,128,1000,7.97,15.18,11.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,256,1000,13.15,21.93,17.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,512,1000,25.46,44.57,33.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,1024,1000,35.1,76.42,58.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,2048,1000,62.09,156.69,114.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,4096,1000,78.75,245.9,187.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,8192,1000,123.48,407.3,297.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,16384,1000,228.77,699.24,511.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,32768,1000,51.18,1567.72,936.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,65536,640,41.1,848.69,455.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,131072,320,98.84,2334.98,1430.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,262144,160,161.58,3126.39,1957.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,524288,80,220.93,6592.35,4059.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,1048576,40,433.78,12394.97,8257.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,2097152,20,3742.93,24809.87,19875.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatter,216,4194304,10,22308.1,49571.71,41246.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,0,1000,2.24,7.93,5.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,1,1000,26.28,146.19,81.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,2,1000,26.44,135.73,80.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,4,1000,25.91,136.13,80.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,8,1000,25.86,140.36,80.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,16,1000,25.95,138.77,80.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,32,1000,26.82,137.02,81.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,64,1000,26.35,143.94,84.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,128,1000,26.14,144.69,84.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,256,1000,27.07,152.21,87.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,512,1000,33.8,164.6,96.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,1024,1000,45.3,207.28,119.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,2048,1000,51.86,243.02,143.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,4096,1000,53.83,261.07,151.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,8192,1000,95.57,791.16,272.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,16384,1000,144.94,723.95,368.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,32768,1000,211.91,1277.23,556.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,65536,640,367.84,1628.9,1101.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,131072,320,641.26,2948.95,2007.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,262144,160,2141.33,5817.97,4388.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,524288,80,4482.7,12248.81,9527.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,1048576,40,11931.04,28682.25,20010.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,2097152,20,24962.25,49299.01,40815.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,4194304,10,34590.93,83225.08,66616.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,144,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,4,1000,7.26,10.99,9.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,8,1000,4.89,8.31,6.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,16,1000,7.89,18.62,16.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,32,1000,6.68,16.51,14.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,64,1000,6.83,13.44,10.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,128,1000,7.87,14.78,10.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,256,1000,8.25,16.44,11.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,512,1000,12.67,27.05,22.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,1024,1000,11.06,19.31,14.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,2048,1000,10.81,17.66,13.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,4096,1000,14.36,27.39,16.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,8192,1000,28.05,41.29,37.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,16384,1000,61.24,69.26,63.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,32768,1000,82.86,92.17,86.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,65536,640,78.35,93.76,83.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,131072,320,143.38,166.92,151.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,262144,160,241.63,286.35,256.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,524288,80,521.96,607.72,541.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,1048576,40,1460.21,1543.94,1495.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,2097152,20,2623.76,2809.21,2707.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,4194304,10,5225.64,5254.8,5242.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,504,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,1,1000,40.43,345.93,202.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,2,1000,60.73,75.59,68.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,4,1000,19.44,27.39,23.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,8,1000,28.1,41.68,34.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,16,1000,33.14,54.5,45.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,32,1000,57.2,95.2,79.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,64,1000,51.42,106.42,91.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,128,1000,81.19,167.08,148.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,256,1000,175.21,274.39,252.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,512,1000,357.52,464.95,440.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,1024,1000,518.73,585.85,566.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,2048,1000,855.19,976.31,950.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,4096,1000,1667.12,1917.21,1833.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,8192,1000,2313.53,2544.83,2431.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,16384,1000,4344.6,4745.15,4554.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,32768,1000,8703.84,9581.65,9147.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,65536,640,17687.96,20644.84,19335.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,131072,320,34558.5,41097.37,37306.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,262144,160,58548.87,76869.9,66244.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,524288,80,106229.91,111913.67,108443.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,1048576,40,260364.06,302483.07,279046.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,2097152,20,626595.11,659371.91,647009.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,4194304,10,1098895.59,1123676.74,1109578.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,360,0,1000,3.02,11.46,6.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,1,1000,40.66,261.59,180.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,2,1000,40.91,262.73,181.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,4,1000,41.11,262.14,180.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,8,1000,41.51,263.11,181.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,16,1000,40.53,263.86,182.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,32,1000,41.01,268.24,185.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,64,1000,41.64,289.82,202.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,128,1000,41.53,281.14,196.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,256,1000,42.76,292.65,205.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,512,1000,53.55,344.08,248.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,1024,1000,68.48,417.91,312.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,2048,1000,74.38,508.64,387.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,4096,1000,74.48,548.42,421.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,8192,1000,92.65,735.25,580.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,16384,1000,135.5,1276.79,1020.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,32768,1000,208.7,2393.46,1893.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,65536,640,258.65,2484.2,1453.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,131072,320,419.61,4638.64,2650.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,262144,160,1248.11,9099.4,5230.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,524288,80,3186.77,18566.9,10930.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,1048576,40,12029.4,36582.34,22153.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,2097152,20,25013.48,74011.34,45227.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,4194304,10,34535.19,132474.23,74935.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,504,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,1,1000,0.5,59.92,2.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,2,1000,0.55,188.92,4.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,4,1000,0.57,90.56,3.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,8,1000,0.56,685.19,13.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,16,1000,0.56,36.62,1.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,32,1000,0.48,48.49,1.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,64,1000,0.52,30.31,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,128,1000,0.51,33.75,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,256,1000,0.59,58.0,2.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,512,1000,0.85,79.7,3.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,1024,1000,1.04,233.95,6.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,2048,1000,1.3,261.29,8.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,4096,1000,2.33,486.47,14.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,8192,1000,3.84,1543.85,33.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,16384,1000,8.3,3237.59,77.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,32768,1000,14.84,6247.13,130.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,65536,640,32.48,3367.46,1889.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,131072,320,85.4,7273.93,3435.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,262144,160,158.63,12199.19,6608.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,524288,80,317.33,24834.13,13621.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,1048576,40,229.7,48937.39,26558.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,2097152,20,2000.91,98280.56,54402.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,4194304,10,12132.75,180122.6,94806.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,288,0,1000,1.25,1.65,1.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,4,1000,1.74,12.71,2.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,8,1000,1.78,14.29,2.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,16,1000,1.81,21.72,3.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,32,1000,1.58,20.04,5.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,64,1000,1.58,21.19,6.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,128,1000,1.62,22.78,6.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,256,1000,2.78,24.25,9.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,512,1000,2.75,26.92,12.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,1024,1000,8.5,26.08,20.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,2048,1000,21.84,34.88,27.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,4096,1000,31.18,43.51,37.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,8192,1000,51.23,65.96,57.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,16384,1000,90.01,107.86,99.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,32768,1000,175.81,200.12,189.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,65536,640,254.87,333.19,288.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,131072,320,306.82,473.13,396.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,262144,160,677.05,774.76,716.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,524288,80,1050.46,1155.45,1094.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,1048576,40,1459.89,1565.02,1505.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,2097152,20,2435.51,2597.73,2489.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,4194304,10,3648.14,4141.8,3885.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,1,1000,0.96,4.7,3.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,2,1000,1.14,5.78,4.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,4,1000,1.11,5.76,4.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,8,1000,1.11,5.8,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,16,1000,1.11,5.76,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,32,1000,1.15,5.79,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,64,1000,1.15,5.83,4.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,128,1000,1.17,5.96,4.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,256,1000,1.24,6.4,5.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,512,1000,1.07,6.3,4.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,1024,1000,1.19,5.4,4.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,2048,1000,2.04,6.47,4.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,4096,1000,4.25,9.88,7.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,8192,1000,7.16,15.97,11.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,16384,1000,12.53,25.76,22.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,32768,1000,19.43,49.03,40.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,65536,640,36.76,63.79,54.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,131072,320,69.73,111.17,96.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,262144,160,148.03,193.67,177.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,524288,80,306.14,334.89,324.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,1048576,40,607.55,644.5,632.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,2097152,20,1150.09,1188.98,1179.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,4194304,10,2359.34,2819.06,2473.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,720,0,1000,2.62,2.9,2.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,4,1000,3.13,18.04,3.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,8,1000,3.21,21.05,3.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,16,1000,3.19,25.36,4.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,32,1000,2.91,26.04,6.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,64,1000,2.94,25.87,7.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,128,1000,2.96,26.96,7.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,256,1000,2.98,28.86,8.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,512,1000,3.22,42.66,12.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,1024,1000,3.68,44.04,18.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,2048,1000,10.6,67.8,46.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,4096,1000,58.02,87.53,67.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,8192,1000,101.38,135.04,113.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,16384,1000,174.55,245.07,197.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,32768,1000,202.64,230.85,220.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,65536,640,403.43,445.24,432.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,131072,320,332.39,671.82,501.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,262144,160,690.39,1047.85,872.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,524288,80,1382.36,1559.21,1467.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,1048576,40,2167.49,2379.75,2282.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,2097152,20,3074.21,3256.8,3180.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce_scatter,720,4194304,10,5008.88,5246.3,5153.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,432,0,1000,0.06,0.09,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,4,1000,0.32,9.46,0.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,8,1000,0.35,9.63,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,16,1000,0.39,9.11,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,32,1000,0.54,14.44,1.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,64,1000,0.36,10.17,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,128,1000,0.35,10.85,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,256,1000,0.56,15.03,1.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,512,1000,0.32,12.23,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,1024,1000,0.35,11.38,0.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,2048,1000,0.41,12.52,1.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,4096,1000,0.74,21.19,1.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,8192,1000,2.71,31.33,4.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,16384,1000,9.12,61.38,15.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,32768,1000,33.3,125.88,76.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,65536,640,70.03,200.53,134.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,131072,320,131.5,353.02,244.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,262144,160,84.91,786.78,389.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,524288,80,130.7,910.8,477.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,1048576,40,213.54,1285.57,700.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,2097152,20,377.75,2109.48,1097.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,432,4194304,10,1137.49,3408.54,2916.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,288,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,1,1000,1.19,8.87,3.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,2,1000,1.2,10.68,4.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,4,1000,1.57,12.81,5.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,8,1000,1.75,11.75,5.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,16,1000,2.75,12.03,6.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,32,1000,3.8,13.84,7.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,64,1000,4.89,18.14,10.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,128,1000,6.54,24.34,15.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,256,1000,9.33,33.54,23.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,512,1000,25.76,78.61,56.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,1024,1000,22.47,102.25,78.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,2048,1000,39.53,175.65,130.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,4096,1000,50.52,254.09,186.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,8192,1000,90.64,481.13,338.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,16384,1000,183.41,828.61,598.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,32768,1000,25.48,1109.86,515.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,65536,640,40.48,1343.15,810.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,131072,320,67.27,3042.52,1826.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,262144,160,131.49,4672.36,2430.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,524288,80,245.31,9310.17,6095.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,1048576,40,443.35,18582.09,12756.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,2097152,20,25135.42,52860.22,39361.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,288,4194304,10,14082.85,74283.96,59774.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,1,1000,59.95,65.97,62.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,2,1000,60.95,68.71,63.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,4,1000,68.25,76.79,71.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,8,1000,73.65,87.73,80.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,16,1000,109.37,141.37,125.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,32,1000,102.33,117.28,112.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,64,1000,171.13,196.77,186.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,128,1000,306.56,354.23,335.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,256,1000,811.74,828.83,819.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,512,1000,1131.19,1148.5,1138.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,1024,1000,1889.87,1909.49,1897.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,2048,1000,3389.65,3436.4,3414.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,4096,1000,5713.06,5725.38,5717.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,8192,1000,12950.4,12983.32,12961.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,16384,1000,24303.11,24373.71,24332.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,32768,1000,48353.38,48461.28,48397.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,65536,622,97180.54,98355.14,97829.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,131072,320,185305.27,185611.12,185430.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,262144,75,377637.06,378741.17,378341.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,524288,48,699616.61,700096.99,699843.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,1048576,29,1419967.16,1424322.42,1421619.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,2097152,15,2770833.95,2773515.91,2772027.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,1,1000,14.15,22.09,17.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,2,1000,18.92,56.61,52.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,4,1000,17.2,26.4,20.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,8,1000,25.65,38.48,31.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,16,1000,24.89,53.17,33.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,32,1000,24.47,35.24,31.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,64,1000,72.52,97.52,88.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,128,1000,55.91,93.48,85.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,256,1000,97.65,164.56,151.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,512,1000,196.36,272.49,253.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,1024,1000,494.42,532.7,526.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,2048,1000,700.03,746.63,732.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,4096,1000,981.91,1011.5,1001.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,8192,1000,1250.25,1382.14,1309.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,16384,1000,2391.44,2673.71,2540.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,32768,1000,4693.33,5319.88,5023.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,65536,640,9652.46,11382.68,10540.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,131072,320,17277.14,21536.48,19199.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,262144,160,32903.9,44486.8,37967.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,524288,80,61294.51,66373.11,63588.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,1048576,40,144965.69,164857.17,155545.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,2097152,20,306159.22,326614.67,313098.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgather,288,4194304,10,621780.83,659346.64,637580.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce,288,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,4,1000,0.35,6.65,0.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,8,1000,0.33,7.44,0.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,16,1000,0.35,8.59,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,32,1000,0.36,9.51,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,64,1000,0.35,9.85,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,128,1000,0.34,10.06,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,256,1000,0.34,11.1,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,512,1000,0.32,12.07,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,1024,1000,0.34,10.63,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,2048,1000,0.42,12.74,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,4096,1000,0.7,15.01,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,8192,1000,2.63,25.16,4.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,16384,1000,7.07,37.09,11.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,32768,1000,38.09,160.12,109.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,65536,640,81.12,186.01,145.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,131072,320,168.39,353.86,274.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,262144,160,87.43,826.76,400.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,524288,80,160.1,1061.79,558.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,1048576,40,227.52,1301.55,731.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,2097152,20,488.01,1896.06,1563.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,4194304,10,695.04,3928.09,2137.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,144,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,1,1000,2.86,6.98,5.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,2,1000,1.1,4.84,3.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,4,1000,3.13,7.62,5.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,8,1000,3.13,7.92,5.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,16,1000,1.7,7.0,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,32,1000,2.63,7.98,4.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,64,1000,5.38,10.85,8.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,128,1000,7.52,15.26,11.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,256,1000,9.78,22.23,17.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,512,1000,9.56,34.3,24.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,1024,1000,13.65,50.61,40.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,2048,1000,23.03,100.38,85.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,4096,1000,31.7,238.18,195.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,8192,1000,52.49,319.69,275.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,16384,1000,92.8,496.5,417.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,32768,1000,35.77,735.95,350.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,65536,640,67.18,1883.18,694.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,131072,320,98.83,1666.22,1138.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,262144,160,246.53,1595.94,931.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,524288,80,369.54,3169.93,1753.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,1048576,40,2330.31,6297.0,6001.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,2097152,20,1027.84,24631.23,7876.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,144,4194304,10,16147.95,25356.61,24738.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,576,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,4,1000,6.89,9.45,8.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,8,1000,8.8,12.22,10.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,16,1000,9.57,12.73,11.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,32,1000,8.85,15.63,10.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,64,1000,10.53,15.9,12.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,128,1000,10.78,17.92,13.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,256,1000,13.43,24.83,20.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,512,1000,14.2,20.22,16.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,1024,1000,16.97,23.19,19.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,2048,1000,42.21,55.85,49.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,4096,1000,33.21,42.91,39.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,8192,1000,49.09,59.29,54.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,16384,1000,100.48,112.58,105.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,32768,1000,333.73,366.57,350.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,65536,640,100.03,132.69,110.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,131072,320,677.4,969.49,701.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,262144,160,1148.19,1258.17,1206.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,524288,80,817.02,1040.95,945.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,1048576,40,1579.04,1899.15,1679.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,2097152,20,3290.03,3358.06,3328.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,4194304,10,5445.84,5526.18,5489.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Gather,144,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,1,1000,0.57,25.77,2.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,2,1000,0.57,26.06,2.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,4,1000,0.57,25.14,3.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,8,1000,0.57,19.79,2.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,16,1000,0.5,13.99,1.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,32,1000,0.47,13.54,1.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,64,1000,0.48,15.79,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,128,1000,0.5,19.96,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,256,1000,0.52,27.54,1.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,512,1000,0.71,41.64,2.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,1024,1000,0.89,76.54,4.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,2048,1000,1.32,139.85,7.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,4096,1000,2.19,255.46,12.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,8192,1000,3.44,300.88,8.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,16384,1000,7.1,467.94,12.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,32768,1000,12.33,807.73,23.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,65536,640,39.69,1062.05,495.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,131072,320,90.75,1575.64,849.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,262144,160,175.48,3087.64,1658.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,524288,80,337.54,6346.09,3396.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,1048576,40,235.39,17983.16,9125.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,2097152,20,1800.52,27087.65,16648.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,4194304,10,12587.87,52521.03,32180.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,288,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,1,1000,12.27,19.06,14.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,2,1000,15.38,22.59,18.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,4,1000,15.98,27.41,20.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,8,1000,19.12,32.85,24.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,16,1000,20.02,36.3,27.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,32,1000,39.93,53.64,49.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,64,1000,232.01,577.04,403.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,128,1000,59.53,99.47,90.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,256,1000,98.06,164.13,152.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,512,1000,195.43,274.63,251.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,1024,1000,277.19,308.67,298.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,2048,1000,507.52,533.0,525.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,4096,1000,976.26,999.05,993.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,8192,1000,1267.66,1401.07,1327.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,16384,1000,2961.61,3398.55,3199.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,32768,1000,4790.39,5604.03,5182.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,65536,640,8816.66,10461.73,9638.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,131072,320,16793.08,20840.23,18627.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,262144,160,30929.02,43326.36,35727.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,524288,80,60512.99,61928.31,61048.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,1048576,40,131124.67,136742.23,133299.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,2097152,20,304105.4,313112.47,308923.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,4194304,10,678864.61,733231.98,701777.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,360,0,1000,1.5,1.67,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,4,1000,2.06,43.56,3.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,8,1000,2.04,14.33,3.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,16,1000,2.07,15.87,3.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,32,1000,2.07,31.64,3.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,64,1000,1.81,25.2,5.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,128,1000,1.84,26.94,6.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,256,1000,1.86,26.86,8.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,512,1000,2.1,29.37,11.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,1024,1000,5.71,32.11,20.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,2048,1000,24.3,37.67,29.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,4096,1000,34.26,45.89,40.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,8192,1000,58.35,78.63,69.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,16384,1000,408.51,699.44,469.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,32768,1000,204.49,258.51,240.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,65536,640,350.19,390.49,373.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,131072,320,1486.54,2288.75,1995.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,262144,160,858.42,971.91,905.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,524288,80,1155.73,1295.9,1221.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,1048576,40,1547.98,1670.58,1605.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,2097152,20,2921.15,3059.96,2986.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,4194304,10,4565.63,4705.64,4646.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,288,0,1000,2.71,11.86,6.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,1,1000,32.09,210.9,141.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,2,1000,32.65,210.54,141.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,4,1000,32.46,210.48,140.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,8,1000,32.7,211.45,141.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,16,1000,32.54,211.81,141.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,32,1000,32.67,214.59,144.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,64,1000,33.34,231.76,156.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,128,1000,33.35,223.79,150.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,256,1000,33.73,229.8,155.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,512,1000,42.18,265.42,184.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,1024,1000,52.79,326.08,234.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,2048,1000,63.04,402.78,293.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,4096,1000,62.01,425.37,311.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,8192,1000,82.32,593.68,448.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,16384,1000,141.31,1837.32,888.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,32768,1000,185.89,1780.24,1356.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,65536,640,252.73,2077.74,1229.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,131072,320,477.82,3878.55,2220.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,262144,160,1899.42,7530.44,4532.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,524288,80,4416.06,15391.74,9491.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,1048576,40,12017.5,30412.41,19208.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,2097152,20,25014.99,61754.81,39377.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,4194304,10,34552.59,107926.24,63185.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,360,0,1000,4.24,12.1,4.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,1,1000,29.72,43.09,33.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,2,1000,25.97,33.92,30.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,4,1000,33.75,42.98,39.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,8,1000,37.79,54.46,45.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,16,1000,37.45,52.81,45.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,32,1000,55.7,76.24,67.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,64,1000,87.45,135.32,121.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,128,1000,196.62,264.5,234.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,256,1000,159.81,259.86,236.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,512,1000,302.92,393.68,367.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,1024,1000,494.97,1039.12,587.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,2048,1000,526.47,695.53,660.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,4096,1000,963.5,1085.71,1020.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,8192,1000,1689.06,1829.05,1763.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,16384,1000,3041.81,3342.06,3196.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,32768,1000,6060.11,6782.2,6421.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,65536,640,10778.92,11942.3,11384.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,131072,320,20964.49,25451.47,23371.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,262144,160,43164.29,50004.54,46362.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,524288,80,87706.95,95073.16,90812.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,1048576,40,176105.16,185447.0,179720.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,2097152,20,384906.15,397590.34,390271.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,4194304,10,778373.89,803085.86,789717.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,1,1000,1.13,9.98,5.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,2,1000,1.16,12.18,6.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,4,1000,1.57,14.12,7.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,8,1000,1.79,12.2,6.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,16,1000,2.92,12.42,7.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,32,1000,4.35,15.62,9.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,64,1000,6.67,19.86,12.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,128,1000,10.56,25.88,17.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,256,1000,17.78,37.25,25.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,512,1000,53.59,201.88,100.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,1024,1000,51.36,133.42,97.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,2048,1000,61.0,200.64,138.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,4096,1000,88.96,335.16,222.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,8192,1000,150.45,582.56,386.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,16384,1000,271.75,909.96,629.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,32768,1000,24.69,1484.22,671.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,65536,640,30.13,1710.79,979.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,131072,320,68.46,3856.25,2582.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,262144,160,185.85,6850.14,3702.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,524288,80,194.39,12465.31,8163.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,1048576,40,492.03,24722.91,17620.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,2097152,20,857.9,49430.13,38735.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatter,360,4194304,10,15107.73,98832.67,81161.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allreduce,720,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,4,1000,10.08,13.97,11.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,8,1000,11.69,15.97,13.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,16,1000,10.3,14.85,12.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,32,1000,17.68,27.95,25.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,64,1000,12.11,17.93,14.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,128,1000,12.98,22.38,16.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,256,1000,20.97,32.25,27.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,512,1000,17.13,27.9,22.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,1024,1000,19.21,29.34,22.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,2048,1000,20.58,27.45,23.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,4096,1000,25.79,31.66,28.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,8192,1000,64.63,76.28,72.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,16384,1000,87.47,115.96,105.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,32768,1000,240.18,306.88,268.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,65536,640,153.51,187.56,166.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,131072,320,174.26,215.45,190.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,262144,160,322.07,388.13,345.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,524288,80,668.73,803.27,714.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,1048576,40,1710.65,2012.6,1862.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,2097152,20,3640.23,3854.13,3740.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,4194304,10,6318.3,6714.78,6474.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Scatterv,504,0,1000,11.43,20.42,15.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,1,1000,11.19,20.81,16.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,2,1000,12.01,22.65,17.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,4,1000,12.31,23.84,18.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,8,1000,11.56,22.16,16.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,16,1000,11.46,21.62,16.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,32,1000,13.51,24.72,19.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,64,1000,16.45,30.39,23.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,128,1000,20.77,38.51,29.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,256,1000,21.27,52.51,38.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,512,1000,48.74,85.86,69.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,1024,1000,42.21,103.26,77.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,2048,1000,27.05,171.34,115.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,4096,1000,19.15,315.54,195.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,8192,1000,46.47,1025.76,381.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,16384,1000,45.42,1173.26,673.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,32768,1000,40.59,2257.79,1286.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,65536,640,56.45,4634.34,2471.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,131072,320,206.1,8745.14,5019.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,262144,160,433.68,28396.6,15126.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,524288,80,688.26,63718.39,35489.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,1048576,40,1222.34,128646.45,68191.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,2097152,20,2057.07,249100.55,140476.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatterv,504,4194304,10,5990.55,496389.95,280388.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,432,0,1000,3.38,11.58,7.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,1,1000,52.57,311.11,222.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,2,1000,51.83,314.22,222.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,4,1000,53.52,314.56,222.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,8,1000,52.82,316.07,223.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,16,1000,52.96,317.74,225.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,32,1000,53.11,325.35,231.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,64,1000,55.06,345.34,248.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,128,1000,55.33,337.29,242.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,256,1000,57.39,347.28,252.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,512,1000,74.43,409.14,304.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,1024,1000,92.4,508.05,389.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,2048,1000,102.13,616.66,480.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,4096,1000,92.37,658.27,520.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,8192,1000,116.48,887.57,722.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,16384,1000,155.52,1522.68,1257.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,32768,1000,244.59,2858.54,2372.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,65536,640,363.65,2962.73,1743.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,131072,320,628.36,5474.22,3115.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,262144,160,1307.9,10789.45,6133.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,524288,80,3114.76,21738.29,12519.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,1048576,40,12271.78,43298.13,25332.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,2097152,20,24951.14,86220.71,51114.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,4194304,10,34589.07,157061.59,86886.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,504,0,1000,3.71,11.71,8.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,1,1000,60.2,363.87,262.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,2,1000,61.11,362.95,262.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,4,1000,60.34,363.73,261.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,8,1000,60.89,364.27,263.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,16,1000,60.18,368.33,265.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,32,1000,61.63,375.69,272.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,64,1000,62.45,431.48,319.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,128,1000,63.99,434.58,324.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,256,1000,65.89,447.95,334.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,512,1000,86.37,516.77,394.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,1024,1000,100.93,632.81,493.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,2048,1000,109.64,734.49,581.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,4096,1000,124.65,1273.28,705.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,8192,1000,140.46,1114.61,928.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,16384,1000,189.39,1853.96,1565.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,32768,1000,307.18,3968.47,3039.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,65536,640,443.12,4220.84,2241.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,131072,320,753.62,8166.62,3948.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,262144,160,1186.84,12691.62,7186.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,524288,80,2775.09,25399.54,13986.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,1048576,40,12087.73,48929.22,28221.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,2097152,20,24905.67,98452.78,57076.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,504,4194304,10,34407.32,181437.92,98726.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gatherv,144,0,1000,1.86,5.56,3.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,1,1000,17.79,111.58,57.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,2,1000,16.69,96.35,57.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,4,1000,16.65,99.47,57.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,8,1000,16.47,97.18,57.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,16,1000,16.7,96.95,57.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,32,1000,17.37,97.46,58.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,64,1000,20.1,101.64,59.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,128,1000,20.44,99.13,58.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,256,1000,19.94,99.22,58.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,512,1000,27.3,112.71,67.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,1024,1000,34.37,136.53,80.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,2048,1000,52.15,184.22,107.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,4096,1000,73.72,233.97,136.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,8192,1000,95.78,312.26,184.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,16384,1000,140.46,505.66,273.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,32768,1000,207.38,837.58,410.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,65536,640,399.43,1376.22,892.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,131072,320,966.5,2221.09,1555.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,262144,160,2337.95,4314.34,3279.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,524288,80,5097.94,9156.65,7191.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,1048576,40,11905.28,17967.31,14815.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,2097152,20,24915.68,37014.1,30863.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,4194304,10,34351.3,58507.26,46302.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,432,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,4,1000,5.37,9.5,7.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,8,1000,6.49,11.4,9.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,16,1000,9.67,13.67,11.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,32,1000,8.82,13.19,10.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,64,1000,11.21,17.52,13.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,128,1000,11.18,18.43,14.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,256,1000,13.5,21.81,17.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,512,1000,13.19,18.89,15.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,1024,1000,17.34,24.13,19.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,2048,1000,18.6,24.94,21.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,4096,1000,26.03,34.19,29.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,8192,1000,46.16,56.92,50.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,16384,1000,97.08,117.27,106.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,32768,1000,84.81,111.19,96.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,65536,640,107.82,135.52,118.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,131072,320,169.74,207.53,184.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,262144,160,299.32,371.25,326.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,524288,80,662.6,799.61,711.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,1048576,40,1691.66,2008.37,1884.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,2097152,20,3501.02,3709.69,3640.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,4194304,10,6073.47,6479.13,6333.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,216,0,1000,1.04,1.12,1.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,4,1000,1.58,14.38,2.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,8,1000,1.57,12.82,2.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,16,1000,1.61,14.82,2.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,32,1000,1.35,15.4,3.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,64,1000,1.36,16.3,3.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,128,1000,1.39,18.35,4.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,256,1000,1.4,18.48,7.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,512,1000,1.49,22.62,12.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,1024,1000,14.21,22.63,17.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,2048,1000,16.4,27.32,21.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,4096,1000,25.02,40.02,32.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,8192,1000,39.46,57.52,49.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,16384,1000,78.31,105.65,91.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,32768,1000,121.59,150.85,139.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,65536,640,239.97,321.9,274.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,131072,320,335.97,508.6,427.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,262144,160,641.28,728.92,675.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,524288,80,2111.5,2919.89,2186.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,1048576,40,3643.75,4149.86,3752.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,2097152,20,2839.6,2948.72,2894.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,4194304,10,5248.6,5906.54,5511.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,720,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,1,1000,2.36,7.1,5.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,2,1000,2.53,6.84,5.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,4,1000,2.72,6.99,5.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,8,1000,2.56,6.84,5.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,16,1000,2.54,6.86,5.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,32,1000,2.61,10.72,5.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,64,1000,2.7,6.92,5.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,128,1000,2.69,7.11,5.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,256,1000,3.45,8.3,6.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,512,1000,3.05,9.17,5.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,1024,1000,3.56,8.7,5.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,2048,1000,4.46,11.87,8.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,4096,1000,7.64,17.34,12.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,8192,1000,10.23,25.55,19.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,16384,1000,17.15,38.55,31.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,32768,1000,35.96,70.8,63.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,65536,640,49.48,109.48,94.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,131072,320,127.49,214.62,190.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,262144,160,191.66,286.56,260.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,524288,80,313.6,423.6,397.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,1048576,40,694.02,733.65,714.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,2097152,20,1293.71,1369.77,1323.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,4194304,10,3907.9,4194.12,4033.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,216,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,4,1000,24.21,42.14,34.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,8,1000,10.1,15.06,13.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,16,1000,6.47,9.5,7.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,32,1000,6.33,9.41,7.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,64,1000,9.59,14.45,12.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,128,1000,8.09,15.31,11.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,256,1000,9.4,16.23,12.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,512,1000,11.29,16.89,13.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,1024,1000,11.23,17.44,13.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,2048,1000,11.17,16.64,13.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,4096,1000,15.76,21.48,17.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,8192,1000,54.67,77.71,63.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,16384,1000,96.02,117.88,103.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,32768,1000,99.49,122.22,107.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,65536,640,96.07,149.7,130.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,131072,320,156.6,219.06,192.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,262144,160,279.14,352.4,307.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,524288,80,598.56,741.27,657.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,1048576,40,1658.22,1715.84,1679.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,2097152,20,3028.76,3074.58,3059.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,4194304,10,5253.38,5311.45,5279.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,504,0,1000,3.77,11.8,8.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,1,1000,56.46,358.29,257.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,2,1000,56.92,358.6,257.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,4,1000,57.63,365.4,263.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,8,1000,56.86,696.48,260.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,16,1000,56.92,364.4,261.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,32,1000,57.67,372.42,269.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,64,1000,59.2,403.11,295.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,128,1000,60.93,400.2,293.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,256,1000,63.97,428.4,318.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,512,1000,79.7,496.48,376.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,1024,1000,92.54,916.34,476.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,2048,1000,93.85,688.44,542.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,4096,1000,96.83,1094.55,646.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,8192,1000,113.75,1049.96,872.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,16384,1000,160.93,2265.03,1631.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,32768,1000,236.72,3894.34,2990.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,65536,640,272.53,3383.38,1965.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,131072,320,481.78,6301.42,3554.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,262144,160,863.36,12418.93,6967.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,524288,80,2049.43,24920.3,14120.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,1048576,40,12160.54,49038.38,28323.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,2097152,20,24885.92,98542.02,57112.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,4194304,10,34630.22,181679.46,98965.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,432,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,4,1000,10.27,45.48,42.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,8,1000,7.08,11.77,9.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,16,1000,10.01,13.11,11.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,32,1000,9.46,12.76,11.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,64,1000,11.39,16.86,13.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,128,1000,14.56,25.54,21.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,256,1000,18.75,33.76,29.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,512,1000,13.62,19.38,15.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,1024,1000,18.24,25.33,20.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,2048,1000,18.64,25.75,21.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,4096,1000,22.42,30.4,25.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,8192,1000,46.73,58.63,52.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,16384,1000,96.83,114.48,104.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,32768,1000,69.84,88.41,77.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,65536,640,99.47,124.38,108.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,131072,320,171.93,210.27,186.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,262144,160,303.35,375.38,330.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,524288,80,650.73,790.59,703.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,1048576,40,1678.23,2007.15,1877.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,2097152,20,3689.56,3904.02,3837.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,432,4194304,10,6113.85,6494.05,6360.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,360,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,4,1000,0.32,7.49,0.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,8,1000,0.35,8.28,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,16,1000,0.4,7.69,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,32,1000,0.53,13.0,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,64,1000,0.36,8.79,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,128,1000,0.35,9.19,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,256,1000,0.55,14.12,1.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,512,1000,0.31,8.61,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,1024,1000,0.34,10.27,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,2048,1000,0.42,11.26,1.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,4096,1000,0.71,14.65,1.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,8192,1000,2.66,28.98,4.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,16384,1000,7.55,44.26,12.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,32768,1000,35.04,125.21,82.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,65536,640,73.92,205.41,140.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,131072,320,150.06,418.55,302.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,262144,160,85.24,769.9,391.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,524288,80,136.39,957.88,493.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,1048576,40,218.52,1271.22,701.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,2097152,20,378.0,2016.07,1095.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,360,4194304,10,1108.76,3247.51,2822.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce,504,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,4,1000,0.32,9.11,0.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,8,1000,0.35,11.23,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,16,1000,0.4,9.36,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,32,1000,0.53,14.52,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,64,1000,0.36,11.01,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,128,1000,0.34,10.97,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,256,1000,0.56,16.02,1.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,512,1000,0.33,12.33,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,1024,1000,0.35,11.96,0.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,2048,1000,0.42,15.27,1.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,4096,1000,0.73,18.63,1.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,8192,1000,2.75,29.43,4.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,16384,1000,8.85,57.88,14.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,32768,1000,34.98,126.18,71.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,65536,640,77.03,219.99,138.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,131072,320,140.42,422.41,264.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,262144,160,87.5,833.42,393.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,524288,80,159.31,1170.07,563.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,1048576,40,228.59,1820.1,800.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,2097152,20,382.36,2159.64,1111.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,4194304,10,1166.52,3581.59,3002.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,720,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,1,1000,2.91,6.85,5.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,2,1000,2.76,6.75,5.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,4,1000,2.88,7.05,5.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,8,1000,2.77,6.76,5.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,16,1000,2.76,6.72,5.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,32,1000,2.83,6.78,5.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,64,1000,2.88,6.87,5.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,128,1000,2.96,7.08,5.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,256,1000,3.62,8.31,6.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,512,1000,3.18,9.5,5.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,1024,1000,3.54,8.66,5.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,2048,1000,4.1,12.08,7.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,4096,1000,7.47,16.9,12.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,8192,1000,10.09,25.04,19.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,16384,1000,16.76,37.52,31.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,32768,1000,35.62,70.01,62.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,65536,640,45.28,97.79,85.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,131072,320,101.76,168.88,151.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,262144,160,148.05,228.25,207.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,524288,80,315.41,431.56,404.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,1048576,40,710.46,747.08,734.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,2097152,20,1318.38,1386.05,1352.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,720,4194304,10,3882.66,4283.71,4038.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Gather,432,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,1,1000,0.5,13.2,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,2,1000,0.55,14.34,1.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,4,1000,0.55,16.13,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,8,1000,0.49,13.01,1.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,16,1000,0.46,13.14,1.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,32,1000,0.46,16.05,1.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,64,1000,0.47,21.01,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,128,1000,0.49,31.79,1.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,256,1000,0.53,56.98,2.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,512,1000,0.86,76.77,3.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,1024,1000,0.98,208.49,5.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,2048,1000,1.24,230.4,8.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,4096,1000,2.29,406.07,14.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,8192,1000,4.13,934.85,30.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,16384,1000,8.08,1504.28,46.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,32768,1000,15.48,3963.54,90.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,65536,640,36.75,3643.94,1867.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,131072,320,82.65,5716.87,3202.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,262144,160,159.66,10951.82,6034.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,524288,80,300.64,21593.19,11829.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,1048576,40,239.26,42765.57,23259.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,2097152,20,1920.45,85932.01,47925.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,432,4194304,10,11378.3,155316.78,82164.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,1,1000,1.17,10.66,5.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,2,1000,1.33,12.97,7.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,4,1000,1.64,13.78,8.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,8,1000,2.27,12.68,7.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,16,1000,3.1,12.55,7.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,32,1000,4.95,16.32,10.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,64,1000,7.28,20.63,14.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,128,1000,11.97,28.13,20.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,256,1000,21.55,47.29,33.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,512,1000,33.94,79.33,55.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,1024,1000,51.08,103.87,79.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,2048,1000,76.31,174.7,131.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,4096,1000,129.03,309.3,228.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,8192,1000,233.57,563.91,408.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,16384,1000,451.13,974.07,747.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,32768,1000,28.8,1505.91,711.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,65536,640,26.8,2080.73,1065.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,131072,320,114.84,4041.83,2193.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,262144,160,184.32,7747.73,4326.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,524288,80,827.31,15457.03,10308.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,1048576,40,348.51,30875.3,23317.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,2097152,20,1056.05,61743.45,49866.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,4194304,10,34481.57,123449.13,105383.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,720,0,1000,0.06,0.09,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,4,1000,0.32,10.7,0.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,8,1000,0.35,32.51,0.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,16,1000,0.36,253.86,1.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,32,1000,0.36,48.93,1.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,64,1000,0.35,17.17,0.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,128,1000,0.34,21.85,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,256,1000,0.34,210.36,2.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,512,1000,0.35,63.83,1.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,1024,1000,0.36,40.83,1.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,2048,1000,0.52,20.6,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,4096,1000,0.83,47.39,2.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,8192,1000,2.73,34.19,4.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,16384,1000,8.13,56.45,13.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,32768,1000,18.01,93.59,25.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,65536,640,72.51,256.48,171.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,131072,320,131.65,379.04,267.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,262144,160,90.25,586.52,299.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,524288,80,149.05,1122.61,534.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,1048576,40,220.42,1383.37,720.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,2097152,20,376.15,2094.28,1092.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,720,4194304,10,804.58,3867.04,2004.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Reduce,144,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,4,1000,0.36,7.85,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,8,1000,0.35,8.38,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,16,1000,0.36,7.87,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,32,1000,0.36,8.19,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,64,1000,0.36,9.28,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,128,1000,0.34,10.29,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,256,1000,0.35,11.74,0.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,512,1000,0.35,11.45,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,1024,1000,0.39,10.26,1.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,2048,1000,0.42,15.29,1.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,4096,1000,0.78,24.12,2.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,8192,1000,2.71,22.4,4.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,16384,1000,7.0,32.22,11.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,32768,1000,16.01,59.11,23.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,65536,640,79.89,182.19,146.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,131072,320,143.5,283.33,236.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,262144,160,84.33,462.57,284.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,524288,80,144.3,692.3,434.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,1048576,40,252.59,1105.73,692.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,2097152,20,330.46,2008.7,1174.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,4194304,10,683.7,3333.41,2011.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,504,0,1000,1.95,2.08,2.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,4,1000,2.49,15.76,3.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,8,1000,2.55,18.52,3.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,16,1000,2.55,18.8,3.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,32,1000,2.53,20.01,3.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,64,1000,2.28,20.2,4.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,128,1000,2.3,20.81,5.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,256,1000,2.31,22.08,6.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,512,1000,2.57,29.67,9.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,1024,1000,3.01,35.67,18.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,2048,1000,25.19,35.5,30.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,4096,1000,28.48,37.28,32.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,8192,1000,50.61,59.79,54.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,16384,1000,72.82,83.57,77.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,32768,1000,134.17,153.05,141.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,65536,640,253.01,273.71,261.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,131072,320,527.5,551.03,538.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,262144,160,793.12,926.79,850.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,524288,80,1170.2,1318.09,1240.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,1048576,40,1633.67,1784.8,1713.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,2097152,20,2697.36,2849.6,2780.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,4194304,10,4589.17,4752.09,4685.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,144,0,1000,2.21,5.74,2.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,1,1000,13.47,18.92,15.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,2,1000,13.78,24.5,16.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,4,1000,15.02,23.44,18.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,8,1000,19.53,26.71,22.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,16,1000,19.68,27.89,23.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,32,1000,19.73,29.78,24.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,64,1000,23.86,43.51,35.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,128,1000,74.93,95.74,90.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,256,1000,89.14,123.1,116.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,512,1000,126.27,181.33,173.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,1024,1000,213.85,268.95,258.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,2048,1000,248.06,271.05,266.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,4096,1000,357.25,417.25,386.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,8192,1000,580.02,657.5,618.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,16384,1000,1084.99,1373.28,1232.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,32768,1000,2036.89,2667.66,2368.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,65536,640,3699.51,4756.58,4261.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,131072,320,8996.7,11531.09,10065.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,262144,160,13412.34,16544.94,15082.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,524288,80,29393.91,30467.29,29889.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,1048576,40,65714.98,68176.78,66874.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,2097152,20,149995.86,156201.68,153349.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,4194304,10,307024.64,323525.11,313518.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,432,0,1000,4.93,13.73,5.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,1,1000,25.63,36.04,29.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,2,1000,26.93,35.4,31.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,4,1000,32.56,42.19,37.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,8,1000,42.24,58.38,50.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,16,1000,41.59,56.55,50.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,32,1000,62.06,90.29,78.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,64,1000,97.52,147.33,132.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,128,1000,218.09,303.24,271.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,256,1000,197.49,285.45,260.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,512,1000,358.41,495.61,442.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,1024,1000,546.13,651.32,603.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,2048,1000,709.44,824.9,785.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,4096,1000,1187.19,1291.75,1242.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,8192,1000,2000.88,2144.11,2078.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,16384,1000,3879.71,4285.02,4073.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,32768,1000,7436.75,8318.68,7843.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,65536,640,13150.34,14416.36,13805.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,131072,320,25969.14,29469.22,28020.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,262144,160,50168.79,59780.3,54593.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,524288,80,99313.06,102761.68,101117.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,1048576,40,197771.97,206187.39,200404.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,2097152,20,459155.65,469837.3,464621.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,4194304,10,1047872.14,1092241.57,1065934.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,648,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,4,1000,0.32,10.15,0.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,8,1000,0.35,11.53,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,16,1000,0.35,12.37,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,32,1000,0.35,11.69,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,64,1000,0.36,11.99,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,128,1000,0.34,13.16,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,256,1000,0.34,14.46,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,512,1000,0.32,14.53,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,1024,1000,0.34,14.64,0.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,2048,1000,0.49,19.01,1.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,4096,1000,0.78,24.65,1.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,8192,1000,2.75,42.44,5.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,16384,1000,9.39,63.88,15.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,32768,1000,18.63,108.75,26.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,65536,640,67.46,259.92,181.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,131072,320,116.45,379.23,281.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,262144,160,89.27,568.97,296.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,524288,80,147.3,1023.12,522.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,1048576,40,216.95,1352.06,721.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,2097152,20,380.16,2068.27,1101.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce,648,4194304,10,806.55,3868.75,2009.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Gatherv,360,0,1000,3.0,11.36,6.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,1,1000,42.37,270.04,188.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,2,1000,42.42,272.03,188.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,4,1000,41.37,270.19,188.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,8,1000,42.49,271.13,188.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,16,1000,42.59,272.99,190.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,32,1000,43.58,276.18,193.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,64,1000,44.3,305.4,216.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,128,1000,46.17,312.6,221.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,256,1000,46.65,316.58,225.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,512,1000,60.9,364.33,265.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,1024,1000,77.93,442.29,331.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,2048,1000,91.55,566.84,432.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,4096,1000,93.66,609.09,470.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,8192,1000,115.13,822.65,652.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,16384,1000,173.22,1853.32,1164.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,32768,1000,217.02,2391.83,1919.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,65536,640,392.61,3466.72,1716.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,131072,320,720.87,5060.78,3033.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,262144,160,1369.81,9619.55,5678.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,524288,80,3206.74,18785.32,11102.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,1048576,40,12026.12,36540.75,22134.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,2097152,20,24897.45,73884.54,45105.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gatherv,360,4194304,10,34456.5,132366.49,74831.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,216,0,1000,7.95,13.94,11.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,1,1000,7.94,14.46,10.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,2,1000,7.99,14.48,10.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,4,1000,8.03,15.13,11.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,8,1000,7.02,13.46,9.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,16,1000,7.64,14.58,10.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,32,1000,8.0,14.97,10.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,64,1000,10.0,17.37,12.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,128,1000,11.32,19.85,14.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,256,1000,13.95,24.77,18.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,512,1000,18.4,33.25,27.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,1024,1000,18.54,46.63,36.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,2048,1000,30.68,73.19,58.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,4096,1000,21.83,137.17,88.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,8192,1000,41.57,333.62,185.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,16384,1000,50.69,607.57,323.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,32768,1000,62.17,1209.28,604.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,65536,640,78.36,1822.45,983.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,131072,320,159.53,4620.52,2458.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,262144,160,364.2,6258.45,3562.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,524288,80,520.94,19204.38,10257.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,1048576,40,707.24,34098.27,19452.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,2097152,20,1463.89,75422.22,43283.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Scatterv,216,4194304,10,4127.01,155145.2,89891.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,360,0,1000,1.48,1.58,1.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,4,1000,1.99,12.88,2.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,8,1000,2.05,15.43,3.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,16,1000,2.06,16.59,3.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,32,1000,2.05,17.51,3.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,64,1000,1.81,18.85,4.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,128,1000,1.83,19.42,5.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,256,1000,1.84,21.08,7.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,512,1000,2.11,29.77,11.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,1024,1000,6.36,34.98,23.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,2048,1000,31.07,45.0,37.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,4096,1000,32.15,45.32,38.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,8192,1000,59.62,81.34,70.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,16384,1000,91.57,110.21,102.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,32768,1000,177.93,207.4,196.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,65536,640,353.25,394.83,375.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,131072,320,741.34,805.45,777.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,262144,160,996.66,1246.08,1042.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,524288,80,1072.7,1193.97,1125.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,1048576,40,1504.3,1601.93,1547.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,2097152,20,2891.6,3015.63,2946.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,360,4194304,10,4548.26,4693.15,4626.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,144,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,1,1000,8.69,16.79,11.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,2,1000,9.81,14.08,11.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,4,1000,17.42,29.64,25.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,8,1000,14.59,19.85,17.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,16,1000,14.3,20.48,17.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,32,1000,13.13,24.96,18.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,64,1000,17.15,27.73,23.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,128,1000,24.69,65.57,46.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,256,1000,46.19,80.13,73.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,512,1000,89.75,153.58,141.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,1024,1000,183.5,254.43,235.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,2048,1000,282.82,314.11,307.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,4096,1000,585.54,621.24,609.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,8192,1000,961.14,1004.36,989.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,16384,1000,1058.47,1355.68,1202.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,32768,1000,2066.76,2663.28,2379.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,65536,640,4278.64,5785.94,5165.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,131072,320,8037.32,10424.73,9393.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,262144,160,14880.15,20489.76,17932.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,524288,80,30137.67,31161.03,30688.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,1048576,40,66197.28,68464.74,67263.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,2097152,20,150669.34,155526.15,153112.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,144,4194304,10,306765.2,317948.41,312096.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,504,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,1,1000,97.42,104.5,100.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,2,1000,99.54,109.19,104.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,4,1000,117.01,129.35,123.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,8,1000,138.41,168.99,150.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,16,1000,136.19,155.53,145.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,32,1000,212.86,260.1,242.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,64,1000,351.17,427.76,396.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,128,1000,707.36,1270.34,812.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,256,1000,2088.33,2146.41,2116.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,512,1000,2332.65,2356.21,2346.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,1024,1000,3937.47,3985.57,3962.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,2048,1000,8844.63,8877.21,8864.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,4096,1000,14329.73,14385.22,14353.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,8192,1000,25285.52,25376.19,25335.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,16384,1000,51713.25,51867.04,51773.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,32768,421,105065.57,105374.54,105201.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,65536,260,220040.65,221128.26,220567.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,131072,10,361119.05,361411.88,361245.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,262144,10,811626.95,814190.96,812411.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,524288,10,1515434.5,1525506.25,1520107.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,1048576,10,2855777.71,2866473.68,2857525.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Alltoall,504,2097152,7,5575741.5,5579370.4,5577302.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,216,0,1000,0.06,0.09,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,4,1000,0.37,8.2,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,8,1000,0.35,7.83,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,16,1000,0.34,8.41,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,32,1000,0.36,8.67,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,64,1000,0.35,12.24,0.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,128,1000,0.35,10.7,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,256,1000,0.34,10.73,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,512,1000,0.31,9.14,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,1024,1000,0.33,10.3,0.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,2048,1000,0.41,11.53,1.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,4096,1000,0.71,14.56,1.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,8192,1000,2.66,25.25,4.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,16384,1000,7.05,33.19,11.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,32768,1000,39.39,141.77,86.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,65536,640,60.85,198.26,135.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,131072,320,109.31,310.18,218.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,262144,160,80.31,717.87,375.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,524288,80,125.74,841.39,460.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,1048576,40,214.52,1225.49,689.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,2097152,20,479.89,1669.9,1410.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,216,4194304,10,685.47,3947.69,2057.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,504,0,1000,5.6,15.98,5.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,1,1000,29.85,35.4,32.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,2,1000,29.7,36.48,33.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,4,1000,39.42,48.55,44.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,8,1000,46.34,62.19,54.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,16,1000,54.03,73.3,65.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,32,1000,65.09,106.23,88.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,64,1000,106.11,161.07,145.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,128,1000,243.31,358.49,314.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,256,1000,223.39,324.91,302.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,512,1000,415.64,527.85,506.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,1024,1000,553.58,620.28,605.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,2048,1000,924.12,1505.27,1017.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,4096,1000,1414.07,1525.74,1465.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,8192,1000,2448.7,3094.23,2751.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,16384,1000,6052.5,6914.98,6487.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,32768,1000,9336.16,10465.08,9904.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,65536,640,15613.29,17074.13,16354.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,131072,320,28905.23,31083.2,30021.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,262144,160,60154.31,70789.56,66216.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,524288,80,131190.63,139647.46,135808.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,1048576,40,234886.88,257784.43,245225.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,2097152,20,536198.9,547496.78,541685.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,4194304,10,1223155.44,1260179.57,1241864.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,576,0,1000,2.17,2.36,2.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,4,1000,2.69,15.37,3.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,8,1000,2.76,19.17,3.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,16,1000,2.77,20.59,3.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,32,1000,2.76,22.02,3.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,64,1000,2.52,30.6,8.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,128,1000,2.55,30.33,8.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,256,1000,2.54,32.18,10.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,512,1000,4.57,41.61,14.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,1024,1000,4.75,69.63,32.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,2048,1000,21.49,69.97,51.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,4096,1000,79.54,106.68,92.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,8192,1000,94.25,127.69,107.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,16384,1000,122.21,136.13,127.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,32768,1000,238.9,255.59,245.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,65536,640,432.54,469.9,455.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,131072,320,914.17,970.53,946.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,262144,160,834.68,966.36,891.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,524288,80,1257.93,1412.1,1337.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,1048576,40,1697.93,1861.32,1789.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,2097152,20,2933.98,3099.69,3029.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce_scatter,576,4194304,10,4606.1,4815.16,4725.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allgatherv,288,0,1000,3.55,9.02,3.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,1,1000,21.06,27.75,24.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,2,1000,22.29,28.59,25.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,4,1000,23.99,31.12,27.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,8,1000,29.16,41.9,35.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,16,1000,34.66,57.98,46.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,32,1000,46.99,62.0,56.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,64,1000,89.79,109.84,106.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,128,1000,101.37,139.93,132.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,256,1000,137.5,199.32,188.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,512,1000,239.53,318.18,297.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,1024,1000,402.01,437.11,430.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,2048,1000,892.87,1314.1,932.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,4096,1000,761.19,839.26,801.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,8192,1000,1257.52,1382.33,1319.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,16384,1000,2594.09,3308.96,2998.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,32768,1000,4867.23,5845.13,5413.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,65536,640,9559.84,11350.89,10533.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,131072,320,15588.51,17720.8,16707.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,262144,160,29312.71,33579.73,31475.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,524288,80,59859.32,60920.63,60411.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,1048576,40,134011.24,148616.66,142780.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,2097152,20,329266.8,345705.81,339980.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,288,4194304,10,684449.6,744790.44,725179.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,144,0,1000,0.79,0.89,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,4,1000,1.09,16.37,3.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,8,1000,1.09,16.95,3.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,16,1000,1.09,14.0,3.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,32,1000,1.11,17.55,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,64,1000,1.15,16.03,5.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,128,1000,1.71,18.36,6.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,256,1000,1.82,48.03,20.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,512,1000,6.58,36.82,29.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,1024,1000,10.78,20.48,15.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,2048,1000,14.53,24.51,19.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,4096,1000,18.35,29.8,23.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,8192,1000,27.81,42.73,34.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,16384,1000,171.15,500.51,248.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,32768,1000,139.58,208.2,167.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,65536,640,213.93,290.98,245.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,131072,320,324.64,455.43,390.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,262144,160,534.2,617.93,568.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,524288,80,829.32,928.12,869.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,1048576,40,1401.4,1541.88,1466.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,2097152,20,1807.99,2039.02,1909.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,4194304,10,33741.34,43299.39,40609.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,288,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,1,1000,0.48,11.97,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,2,1000,0.54,15.2,1.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,4,1000,0.56,15.95,1.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,8,1000,0.5,16.6,1.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,16,1000,0.46,14.82,1.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,32,1000,0.46,17.63,1.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,64,1000,0.47,20.92,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,128,1000,0.5,28.58,1.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,256,1000,0.53,38.1,2.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,512,1000,0.81,59.04,3.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,1024,1000,1.0,106.48,5.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,2048,1000,1.34,251.27,8.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,4096,1000,2.32,311.23,13.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,8192,1000,3.98,552.67,23.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,16384,1000,8.11,1097.98,47.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,32768,1000,18.39,3713.47,109.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,65536,640,38.41,2015.99,1095.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,131072,320,80.26,3760.62,2003.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,262144,160,157.0,7388.39,3935.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,524288,80,332.21,17467.11,8332.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,1048576,40,237.25,31719.94,16419.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,2097152,20,2068.51,60926.83,34294.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,4194304,10,12500.79,105931.12,56762.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,504,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,1,1000,0.49,12.93,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,2,1000,0.56,16.92,1.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,4,1000,0.56,15.68,1.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,8,1000,0.5,14.65,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,16,1000,0.46,15.03,1.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,32,1000,0.46,19.58,1.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,64,1000,0.48,24.89,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,128,1000,0.49,33.79,1.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,256,1000,0.58,92.17,2.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,512,1000,0.78,116.37,3.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,1024,1000,0.99,248.16,6.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,2048,1000,1.27,264.56,8.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,4096,1000,2.32,588.8,16.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,8192,1000,3.85,995.04,26.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,16384,1000,8.6,2163.08,51.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,32768,1000,14.21,5674.67,117.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,65536,640,34.67,4145.73,2119.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,131072,320,75.56,6572.36,3686.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,262144,160,153.74,12451.81,6828.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,524288,80,305.21,24513.66,13349.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,1048576,40,229.87,49425.84,26918.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,2097152,20,2523.38,98229.38,54358.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Gather,504,4194304,10,11394.88,179638.47,94374.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,576,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,4,1000,0.32,10.83,0.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,8,1000,0.35,12.22,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,16,1000,0.39,12.23,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,32,1000,0.55,20.61,1.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,64,1000,0.36,12.96,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,128,1000,0.35,13.93,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,256,1000,0.57,18.26,1.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,512,1000,0.33,17.06,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,1024,1000,0.35,15.65,0.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,2048,1000,0.42,16.11,1.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,4096,1000,0.73,20.95,1.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,8192,1000,2.75,36.58,4.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,16384,1000,9.34,83.56,15.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,32768,1000,37.16,263.19,160.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,65536,640,77.26,229.92,170.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,131072,320,126.3,337.22,263.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,262144,160,88.78,821.56,397.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,524288,80,140.87,994.9,507.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,1048576,40,223.82,1328.6,721.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,2097152,20,384.87,2038.93,1113.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Reduce,576,4194304,10,1136.29,4100.8,3277.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Scatterv,432,0,1000,10.52,18.07,14.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,1,1000,10.4,19.75,15.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,2,1000,11.04,21.89,16.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,4,1000,11.46,22.63,17.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,8,1000,10.58,20.55,15.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,16,1000,10.59,19.41,15.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,32,1000,12.41,22.71,17.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,64,1000,15.26,27.84,20.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,128,1000,18.81,34.82,26.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,256,1000,26.7,60.0,47.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,512,1000,51.28,83.59,67.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,1024,1000,46.62,92.16,73.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,2048,1000,28.48,146.54,98.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,4096,1000,18.5,257.68,158.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,8192,1000,43.89,493.87,294.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,16384,1000,53.97,962.47,558.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,32768,1000,55.35,1879.75,1028.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,65536,640,56.8,3482.67,1906.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,131072,320,205.46,8264.64,4181.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,262144,160,276.26,20559.06,9372.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,524288,80,782.43,48354.08,23197.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,1048576,40,830.6,87119.62,44848.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,2097152,20,2118.12,179951.25,98724.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatterv,432,4194304,10,6016.11,358875.84,198183.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allgather,504,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,1,1000,20.28,26.47,23.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,2,1000,17.44,25.77,21.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,4,1000,19.98,27.83,24.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,8,1000,33.09,48.8,39.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,16,1000,32.73,54.09,45.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,32,1000,66.72,102.77,87.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,64,1000,155.29,565.0,195.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,128,1000,83.41,184.94,152.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,256,1000,198.79,286.45,264.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,512,1000,463.66,1015.77,547.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,1024,1000,727.78,1413.16,939.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,2048,1000,913.96,1033.87,1004.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,4096,1000,1656.87,1857.45,1825.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,8192,1000,2806.89,3594.2,3251.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,16384,1000,4799.4,5653.25,5332.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,32768,1000,9528.88,10847.86,10223.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,65536,640,17246.42,19938.65,18620.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,131072,320,34360.44,40974.9,37943.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,262144,160,62804.49,84348.71,71836.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,524288,80,117270.01,124800.67,120524.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,1048576,40,239626.3,250833.09,246182.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,2097152,20,592305.3,633525.7,608881.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgather,504,4194304,10,1244356.44,1282718.08,1262776.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,576,0,1000,2.17,2.48,2.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,4,1000,2.7,16.56,3.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,8,1000,2.74,19.18,3.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,16,1000,2.78,20.52,3.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,32,1000,2.75,21.55,3.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,64,1000,2.5,34.17,8.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,128,1000,2.51,34.89,9.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,256,1000,2.55,31.56,10.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,512,1000,4.56,39.82,14.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,1024,1000,4.75,71.07,34.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,2048,1000,21.75,66.86,48.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,4096,1000,56.12,79.12,65.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,8192,1000,101.22,133.64,114.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,16384,1000,129.69,145.21,136.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,32768,1000,229.48,250.96,239.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,65536,640,435.95,475.76,460.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,131072,320,917.69,968.32,950.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,262144,160,826.02,957.49,883.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,524288,80,1279.65,1440.03,1358.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,1048576,40,1811.39,1965.63,1890.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,2097152,20,3021.61,3171.38,3102.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,4194304,10,4677.9,4864.73,4776.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Scatter,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,1,1000,1.22,6.96,4.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,2,1000,1.21,7.24,4.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,4,1000,1.26,7.77,4.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,8,1000,1.34,6.66,4.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,16,1000,2.3,8.11,5.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,32,1000,3.19,8.89,6.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,64,1000,4.78,11.9,8.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,128,1000,7.78,15.18,12.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,256,1000,12.51,23.45,18.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,512,1000,24.98,42.76,32.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,1024,1000,34.05,73.1,55.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,2048,1000,50.45,122.1,93.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,4096,1000,71.63,203.71,159.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,8192,1000,121.09,392.46,291.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,16384,1000,223.32,652.34,484.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,32768,1000,56.28,1209.36,759.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,65536,640,41.88,1135.53,598.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,131072,320,103.94,1681.86,979.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,262144,160,117.52,3116.44,2268.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,524288,80,183.52,6213.19,4771.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,1048576,40,4521.16,12403.88,9908.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,2097152,20,5727.72,24812.94,20148.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,4194304,10,5258.96,49559.26,37167.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,504,0,1000,0.06,0.09,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,4,1000,0.32,8.68,0.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,8,1000,0.35,10.82,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,16,1000,0.38,9.75,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,32,1000,0.53,14.9,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,64,1000,0.36,10.7,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,128,1000,0.35,11.74,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,256,1000,0.56,15.88,1.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,512,1000,0.32,13.35,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,1024,1000,0.35,12.38,0.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,2048,1000,0.42,18.07,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,4096,1000,0.72,17.53,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,8192,1000,2.71,29.27,4.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,16384,1000,9.03,52.05,14.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,32768,1000,31.01,137.13,75.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,65536,640,70.38,207.31,128.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,131072,320,137.46,363.6,236.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,262144,160,83.47,3842.88,681.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,524288,80,173.53,4323.12,883.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,1048576,40,228.73,1564.72,817.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,2097152,20,377.76,1970.6,1078.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,504,4194304,10,1138.76,5648.32,4535.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,720,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,4,1000,10.41,13.79,12.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,8,1000,216.62,485.69,377.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,16,1000,15.61,23.8,21.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,32,1000,20.24,30.89,28.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,64,1000,11.72,17.18,14.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,128,1000,12.84,19.69,15.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,256,1000,14.43,22.51,18.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,512,1000,15.41,21.66,18.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,1024,1000,20.06,29.89,23.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,2048,1000,21.05,27.91,23.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,4096,1000,24.62,31.87,27.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,8192,1000,45.08,56.47,51.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,16384,1000,83.54,111.35,100.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,32768,1000,219.01,277.29,243.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,65536,640,134.19,170.28,145.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,131072,320,174.52,213.2,190.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,262144,160,3101.43,4497.28,3431.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,524288,80,709.56,841.42,749.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,1048576,40,1822.75,2322.17,2038.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,2097152,20,4065.21,4464.77,4176.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Allreduce,720,4194304,10,6232.56,6635.15,6397.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,10, 100
+Bcast,216,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,1,1000,0.8,5.63,4.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,2,1000,0.81,5.71,4.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,4,1000,0.81,5.63,4.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,8,1000,0.8,5.59,4.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,16,1000,0.81,5.63,4.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,32,1000,0.81,5.76,4.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,64,1000,0.84,5.8,4.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,128,1000,0.88,5.75,4.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,256,1000,0.97,6.12,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,512,1000,0.87,4.34,3.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,1024,1000,0.99,5.16,4.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,2048,1000,1.63,6.27,4.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,4096,1000,3.75,9.21,6.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,8192,1000,6.32,13.83,11.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,16384,1000,10.36,22.79,18.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,32768,1000,16.79,40.23,34.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,65536,640,37.21,57.31,52.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,131072,320,62.38,110.69,93.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,262144,160,130.67,200.28,176.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,524288,80,259.49,333.11,309.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,1048576,40,523.88,643.47,604.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,2097152,20,1055.14,1262.68,1198.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,4194304,10,2165.54,2561.99,2422.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,144,0,1000,1.85,6.82,4.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,1,1000,18.79,114.91,55.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,2,1000,16.8,95.11,54.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,4,1000,16.13,94.26,54.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,8,1000,16.67,94.08,55.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,16,1000,16.52,95.18,54.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,32,1000,16.43,94.53,55.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,64,1000,18.63,97.38,56.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,128,1000,17.94,104.29,56.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,256,1000,17.86,96.65,56.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,512,1000,20.81,110.8,65.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,1024,1000,27.66,142.1,82.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,2048,1000,39.5,171.33,99.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,4096,1000,49.22,192.53,110.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,8192,1000,82.33,318.7,184.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,16384,1000,131.22,541.68,287.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,32768,1000,213.41,924.19,450.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,65536,640,425.09,1479.03,975.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,131072,320,800.12,2699.56,1782.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,262144,160,2038.33,4891.78,3553.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,524288,80,4955.72,13471.47,7428.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,1048576,40,12114.97,18186.44,15034.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,2097152,20,24993.3,37097.11,30929.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,144,4194304,10,34310.89,58497.74,46293.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatter,432,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,1,1000,1.17,10.11,5.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,2,1000,1.32,12.65,7.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,4,1000,1.81,17.53,7.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,8,1000,2.18,12.59,7.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,16,1000,3.1,13.25,7.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,32,1000,4.85,16.28,10.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,64,1000,7.89,21.45,14.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,128,1000,13.1,28.63,20.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,256,1000,36.49,61.59,48.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,512,1000,58.63,125.0,90.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,1024,1000,65.85,134.96,102.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,2048,1000,82.98,201.3,145.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,4096,1000,131.47,324.32,235.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,8192,1000,244.23,639.4,439.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,16384,1000,440.2,1074.96,757.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,32768,1000,23.39,1810.83,830.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,65536,640,29.02,4138.62,1286.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,131072,320,68.67,4636.46,3265.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,262144,160,146.9,7750.63,4195.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,524288,80,311.05,20271.5,9916.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,1048576,40,2431.79,30869.7,23268.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,2097152,20,4864.24,61731.1,49913.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Scatter,432,4194304,10,17286.06,123421.52,103240.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce,144,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,4,1000,0.35,8.14,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,8,1000,0.35,8.29,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,16,1000,0.34,8.05,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,32,1000,0.36,18.89,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,64,1000,0.37,12.57,0.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,128,1000,0.34,9.9,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,256,1000,0.35,11.43,0.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,512,1000,0.36,8.63,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,1024,1000,0.38,12.0,0.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,2048,1000,0.41,25.88,1.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,4096,1000,0.77,15.03,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,8192,1000,2.64,21.66,4.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,16384,1000,7.11,32.03,11.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,32768,1000,14.67,49.68,20.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,65536,640,77.25,174.97,140.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,131072,320,111.06,240.02,196.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,262144,160,74.54,407.66,256.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,524288,80,129.74,659.2,409.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,1048576,40,237.97,1046.64,663.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,2097152,20,325.96,1985.68,1152.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,144,4194304,10,707.87,3311.59,2004.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce,360,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,4,1000,0.31,8.35,0.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,8,1000,0.34,8.87,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,16,1000,0.39,8.24,0.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,32,1000,0.53,13.39,1.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,64,1000,0.36,9.94,0.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,128,1000,0.35,10.53,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,256,1000,0.56,14.63,1.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,512,1000,0.33,11.3,0.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,1024,1000,0.34,13.63,0.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,2048,1000,0.4,12.36,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,4096,1000,0.73,18.65,1.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,8192,1000,2.67,27.51,4.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,16384,1000,7.88,64.67,13.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,32768,1000,39.81,142.76,94.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,65536,640,79.06,204.81,149.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,131072,320,155.89,364.56,270.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,262144,160,87.86,782.95,394.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,524288,80,148.26,988.6,531.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,1048576,40,234.33,1325.93,736.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,2097152,20,382.33,2048.88,1110.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,4194304,10,1158.42,3272.17,2825.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,144,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,1,1000,2.24,5.44,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,2,1000,0.61,5.29,4.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,4,1000,0.63,5.3,4.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,8,1000,0.63,5.41,4.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,16,1000,0.63,5.42,4.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,32,1000,0.64,5.44,4.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,64,1000,0.63,5.42,4.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,128,1000,0.66,5.54,4.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,256,1000,0.75,5.94,4.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,512,1000,0.79,5.99,4.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,1024,1000,0.79,4.66,3.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,2048,1000,1.49,6.24,4.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,4096,1000,2.47,8.56,5.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,8192,1000,4.79,12.64,9.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,16384,1000,7.95,19.84,16.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,32768,1000,12.52,30.81,26.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,65536,640,29.88,49.82,44.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,131072,320,61.44,89.77,82.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,262144,160,127.35,152.49,146.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,524288,80,280.78,334.91,300.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,1048576,40,614.57,2296.08,1459.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,2097152,20,1061.0,2709.15,1893.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Bcast,144,4194304,10,3549.88,5198.37,4381.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,360,0,1000,8.57,15.76,11.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,1,1000,9.49,18.31,13.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,2,1000,10.1,18.35,14.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,4,1000,10.34,19.89,15.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,8,1000,9.37,17.59,13.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,16,1000,9.3,17.23,13.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,32,1000,11.17,19.08,15.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,64,1000,13.17,22.39,17.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,128,1000,14.97,27.64,22.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,256,1000,20.44,36.8,30.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,512,1000,22.95,55.26,42.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,1024,1000,15.84,66.88,48.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,2048,1000,15.19,107.44,81.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,4096,1000,16.31,181.66,123.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,8192,1000,42.14,367.48,230.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,16384,1000,52.27,1221.08,427.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,32768,1000,52.65,1371.83,911.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,65536,640,47.4,2858.91,1543.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,131072,320,237.19,5629.31,3185.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,262144,160,372.56,11488.06,5739.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,524288,80,616.48,26628.68,16242.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,1048576,40,1139.93,60152.38,34756.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,2097152,20,1946.32,126837.82,71473.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,4194304,10,3262.58,261429.33,147013.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,576,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,4,1000,0.32,11.21,0.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,8,1000,0.35,13.21,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,16,1000,0.39,12.91,0.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,32,1000,0.54,17.15,1.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,64,1000,0.36,13.36,0.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,128,1000,0.35,13.82,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,256,1000,0.59,24.85,2.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,512,1000,0.33,22.56,0.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,1024,1000,0.35,27.09,1.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,2048,1000,0.41,19.48,1.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,4096,1000,0.73,21.25,1.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,8192,1000,2.81,34.71,5.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,16384,1000,9.01,55.6,14.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,32768,1000,38.81,257.11,151.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,65536,640,78.56,238.69,176.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,131072,320,141.46,385.43,301.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,262144,160,87.19,822.49,397.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,524288,80,157.76,1055.92,547.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,1048576,40,228.78,1424.61,755.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,2097152,20,386.88,2070.87,1124.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,4194304,10,1165.61,3761.88,3133.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allgatherv,504,0,1000,5.59,15.67,5.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,1,1000,28.91,35.09,32.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,2,1000,73.27,489.73,191.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,4,1000,44.0,89.85,54.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,8,1000,44.3,66.5,54.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,16,1000,42.8,61.41,54.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,32,1000,67.92,105.64,90.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,64,1000,102.67,158.16,142.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,128,1000,247.96,361.62,318.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,256,1000,219.61,326.83,301.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,512,1000,413.14,532.47,508.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,1024,1000,641.65,728.93,711.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,2048,1000,925.78,1045.73,1022.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,4096,1000,1390.19,1488.96,1441.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,8192,1000,2575.83,3169.45,2831.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,16384,1000,4601.83,5394.82,4996.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,32768,1000,9827.46,11321.97,10493.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,65536,640,17433.86,20211.76,18876.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,131072,320,31630.56,35560.61,33715.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,262144,160,57686.01,64548.97,61243.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,524288,80,121141.2,128486.44,125602.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,1048576,40,271682.42,286519.3,279349.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,2097152,20,576818.96,600811.56,592813.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allgatherv,504,4194304,10,1139946.32,1165075.74,1155185.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,648,0,1000,2.39,2.61,2.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,4,1000,2.91,16.27,3.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,8,1000,2.96,19.62,3.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,16,1000,2.98,23.65,3.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,32,1000,2.72,30.42,7.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,64,1000,2.72,26.08,7.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,128,1000,2.75,27.75,7.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,256,1000,2.76,35.64,10.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,512,1000,3.01,44.25,13.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,1024,1000,3.63,85.37,36.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,2048,1000,10.39,61.6,42.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,4096,1000,53.96,71.16,63.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,8192,1000,103.18,138.83,124.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,16384,1000,130.02,164.63,150.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,32768,1000,223.89,251.13,238.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,65536,640,426.2,492.01,473.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,131072,320,340.33,654.6,499.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,262144,160,672.14,1002.24,842.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,524288,80,1322.0,1486.55,1406.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,1048576,40,2149.42,2358.61,2264.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,2097152,20,3003.06,3170.95,3105.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Reduce_scatter,648,4194304,10,4901.45,5114.58,5024.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Scatterv,144,0,1000,5.5,10.62,7.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,1,1000,6.56,20.32,10.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,2,1000,6.61,20.59,11.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,4,1000,6.69,19.56,10.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,8,1000,6.72,19.85,9.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,16,1000,6.76,20.05,9.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,32,1000,7.0,13.16,9.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,64,1000,7.53,20.06,10.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,128,1000,7.83,15.0,11.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,256,1000,9.26,18.71,13.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,512,1000,10.41,28.6,20.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,1024,1000,13.11,41.64,28.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,2048,1000,17.36,74.88,52.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,4096,1000,13.54,189.27,118.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,8192,1000,40.79,343.83,208.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,16384,1000,49.68,637.11,383.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,32768,1000,60.26,1146.31,681.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,65536,640,83.94,2293.31,1381.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,131072,320,110.32,4254.6,2695.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,262144,160,380.48,6864.85,4363.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,524288,80,669.89,19355.33,10624.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,1048576,40,1060.27,37118.48,19756.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,2097152,20,1918.4,76161.31,40597.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Scatterv,144,4194304,10,4173.54,154735.61,82120.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,360,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,1,1000,0.56,52.09,2.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,2,1000,0.56,14.12,1.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,4,1000,0.56,25.85,1.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,8,1000,0.5,13.95,1.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,16,1000,0.46,14.12,1.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,32,1000,0.48,17.51,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,64,1000,0.48,21.3,1.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,128,1000,0.49,26.32,1.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,256,1000,0.52,40.14,1.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,512,1000,0.86,72.22,3.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,1024,1000,0.93,177.65,5.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,2048,1000,1.25,208.68,8.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,4096,1000,2.39,383.67,14.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,8192,1000,4.25,870.87,31.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,16384,1000,8.08,1235.17,44.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,32768,1000,14.57,3243.75,86.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,65536,640,35.82,2639.24,1491.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,131072,320,82.1,5000.93,2801.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,262144,160,152.84,9402.0,5181.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,524288,80,313.03,18559.56,10196.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,1048576,40,238.49,36532.1,19817.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,2097152,20,1668.17,75660.4,41932.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Gather,360,4194304,10,12311.64,130417.65,69348.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,432,0,1000,10.59,18.28,14.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,1,1000,10.2,20.02,14.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,2,1000,11.29,21.6,16.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,4,1000,11.61,22.44,17.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,8,1000,10.91,21.44,15.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,16,1000,10.69,19.94,15.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,32,1000,12.34,22.74,17.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,64,1000,15.02,27.61,20.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,128,1000,17.23,38.64,26.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,256,1000,18.17,47.9,33.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,512,1000,24.49,65.05,46.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,1024,1000,17.15,88.78,61.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,2048,1000,16.74,151.15,96.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,4096,1000,17.66,258.71,156.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,8192,1000,42.6,502.09,299.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,16384,1000,49.74,988.75,562.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,32768,1000,50.34,1834.57,1033.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,65536,640,58.4,3650.69,1994.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,131072,320,255.8,9227.81,4367.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,262144,160,380.23,21918.42,9748.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,524288,80,569.58,47793.13,23188.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,1048576,40,1196.7,89297.93,45917.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,2097152,20,1994.88,181660.99,99550.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,4194304,10,6076.54,374124.33,204799.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,504,0,1000,11.19,19.91,15.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,1,1000,11.08,21.17,15.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,2,1000,11.81,22.46,17.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,4,1000,12.22,23.78,18.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,8,1000,11.15,21.9,16.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,16,1000,11.41,21.75,16.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,32,1000,13.44,25.1,19.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,64,1000,16.32,30.47,23.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,128,1000,19.89,38.55,28.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,256,1000,18.95,54.97,38.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,512,1000,24.16,77.95,55.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,1024,1000,17.75,105.9,69.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,2048,1000,17.17,171.19,115.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,4096,1000,17.54,320.29,195.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,8192,1000,44.59,758.95,369.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,16384,1000,57.24,1186.74,699.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,32768,1000,48.19,2361.09,1330.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,65536,640,60.96,4774.35,2554.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,131072,320,265.47,10452.69,5346.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,262144,160,373.71,27519.19,14212.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,524288,80,654.46,61088.16,31816.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,1048576,40,1224.05,119180.25,66330.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,2097152,20,2243.81,238797.53,136476.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,4194304,10,6343.15,486620.23,276120.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,360,0,1000,8.4,15.14,11.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,1,1000,9.08,17.03,13.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,2,1000,9.77,18.39,14.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,4,1000,10.17,20.19,15.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,8,1000,8.74,17.26,13.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,16,1000,9.26,17.42,13.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,32,1000,10.85,19.22,15.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,64,1000,13.16,23.11,17.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,128,1000,16.0,27.25,22.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,256,1000,21.1,36.56,29.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,512,1000,28.08,47.94,39.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,1024,1000,49.36,83.44,64.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,2048,1000,30.82,102.31,82.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,4096,1000,20.74,176.18,121.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,8192,1000,36.8,338.63,220.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,16384,1000,52.88,691.65,430.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,32768,1000,44.81,1436.25,798.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,65536,640,55.47,2814.34,1636.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,131072,320,209.9,5253.83,3054.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,262144,160,243.86,9421.18,5855.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,524288,80,421.59,26446.83,16131.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,1048576,40,1019.14,59470.67,32389.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,2097152,20,1874.65,126494.08,70555.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Scatterv,360,4194304,10,4647.93,259160.4,147034.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Reduce_scatter,648,0,1000,2.38,2.53,2.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,4,1000,2.91,17.18,3.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,8,1000,2.96,19.31,3.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,16,1000,2.98,20.08,3.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,32,1000,2.69,26.0,7.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,64,1000,2.71,29.95,7.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,128,1000,2.75,34.79,8.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,256,1000,2.75,28.43,9.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,512,1000,3.0,45.45,14.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,1024,1000,3.58,44.84,21.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,2048,1000,10.13,54.81,40.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,4096,1000,57.42,71.42,63.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,8192,1000,106.22,138.14,119.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,16384,1000,116.98,140.31,128.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,32768,1000,227.58,253.79,241.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,65536,640,436.06,481.46,468.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,131072,320,325.16,639.27,483.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,262144,160,664.93,997.44,836.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,524288,80,1329.45,1495.61,1407.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,1048576,40,1886.12,2090.62,1997.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,2097152,20,3034.19,3199.09,3128.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,4194304,10,4851.55,5071.95,4979.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Alltoall,288,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,1,1000,58.62,64.33,60.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,2,1000,61.36,67.37,63.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,4,1000,67.54,74.37,69.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,8,1000,73.67,89.04,80.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,16,1000,114.54,143.17,128.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,32,1000,102.88,117.76,112.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,64,1000,171.55,192.16,184.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,128,1000,309.64,356.37,337.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,256,1000,818.14,835.68,825.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,512,1000,1129.11,1145.43,1136.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,1024,1000,1896.47,1915.64,1904.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,2048,1000,3858.37,4127.12,3982.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,4096,1000,6308.25,6345.04,6320.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,8192,1000,11862.76,11887.57,11872.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,16384,1000,23651.42,23708.12,23673.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,32768,1000,46782.2,46895.34,46829.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,65536,528,97390.62,98452.62,97883.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,131072,175,187213.13,187742.51,187528.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,262144,149,361585.6,362085.25,361736.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,524288,27,701636.86,702078.49,701864.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,1048576,27,1414477.5,1419906.99,1417331.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,288,2097152,14,2778401.37,2783654.2,2781209.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Alltoall,360,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,1,1000,69.85,76.9,73.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,2,1000,73.84,81.77,77.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,4,1000,168.83,659.64,220.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,8,1000,103.35,123.06,115.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,16,1000,393.83,610.37,451.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,32,1000,161.83,178.21,170.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,64,1000,224.61,260.25,245.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,128,1000,405.07,481.99,452.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,256,1000,2423.89,2815.88,2615.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,512,1000,1532.7,1564.4,1545.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,1024,1000,2917.88,3155.22,3052.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,2048,1000,4096.67,4120.63,4103.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,4096,1000,7697.65,7712.5,7703.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,8192,1000,15584.46,15652.95,15624.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,16384,1000,33214.42,33296.18,33247.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,32768,993,63759.26,63950.28,63841.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,65536,40,138030.27,139433.09,138865.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,131072,24,248722.48,248915.62,248801.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,262144,24,512821.38,513393.0,513106.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,524288,24,935587.13,936183.52,935877.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,1048576,21,1895102.5,1896549.47,1895930.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,2097152,12,3752665.15,3763329.68,3757240.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,4194304,9,7337733.19,7342046.62,7340335.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,288,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,1,1000,0.49,12.28,1.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,2,1000,0.54,14.5,1.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,4,1000,0.55,15.59,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,8,1000,0.49,13.33,1.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,16,1000,0.46,15.0,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,32,1000,0.46,16.52,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,64,1000,0.48,21.31,1.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,128,1000,0.5,28.44,1.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,256,1000,0.51,37.25,1.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,512,1000,0.85,101.85,4.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,1024,1000,0.87,122.79,5.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,2048,1000,1.24,259.41,8.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,4096,1000,2.26,319.68,14.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,8192,1000,4.09,577.44,25.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,16384,1000,8.64,1307.24,60.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,32768,1000,18.17,3319.79,92.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,65536,640,38.86,2468.08,1279.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,131072,320,80.02,4109.0,2265.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,262144,160,153.13,7858.18,4215.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,524288,80,297.13,15376.04,8354.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,1048576,40,229.5,30358.38,16276.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,2097152,20,2730.29,60836.38,34206.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gather,288,4194304,10,12009.33,106291.89,57021.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allgatherv,216,0,1000,2.9,7.15,2.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,1,1000,17.66,23.61,20.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,2,1000,17.15,23.63,19.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,4,1000,20.04,26.52,22.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,8,1000,22.28,29.72,25.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,16,1000,28.77,38.07,33.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,32,1000,28.77,43.73,36.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,64,1000,79.61,96.23,92.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,128,1000,95.85,122.67,117.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,256,1000,113.87,161.68,154.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,512,1000,205.6,254.39,240.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,1024,1000,311.17,417.14,386.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,2048,1000,360.7,425.81,403.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,4096,1000,556.11,621.81,590.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,8192,1000,941.37,1048.28,995.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,16384,1000,1740.64,2038.69,1892.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,32768,1000,3380.74,4054.13,3734.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,65536,640,5986.68,7118.87,6574.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,131072,320,11171.42,12979.0,12098.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,262144,160,22474.91,28061.11,25108.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,524288,80,48848.87,53666.02,51193.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,1048576,40,122612.27,130652.92,126031.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,2097152,20,226919.15,234500.43,230520.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,4194304,10,462761.85,481961.28,470094.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,1,1000,12.49,32.43,22.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,2,1000,11.18,23.4,13.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,4,1000,15.73,27.32,23.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,8,1000,16.49,25.3,19.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,16,1000,16.19,28.55,20.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,32,1000,16.06,25.21,21.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,64,1000,41.83,73.15,59.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,128,1000,38.25,60.5,56.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,256,1000,73.31,120.26,114.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,512,1000,158.62,202.02,195.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,1024,1000,320.12,416.96,388.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,2048,1000,520.32,600.26,577.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,4096,1000,712.51,834.44,794.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,8192,1000,913.09,1023.05,964.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,16384,1000,1932.22,2500.26,2247.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,32768,1000,3382.24,4044.4,3717.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,65536,640,6648.55,8330.12,7567.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,131072,320,11557.46,16845.69,14275.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,262144,160,23551.73,34811.9,28191.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,524288,80,48907.8,53512.93,51164.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,1048576,40,98279.81,101470.69,99710.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,2097152,20,229157.25,235175.46,232287.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgather,216,4194304,10,463213.54,477291.01,470729.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,648,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,4,1000,0.33,11.06,0.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,8,1000,0.36,12.38,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,16,1000,0.34,52.38,1.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,32,1000,0.36,19.46,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,64,1000,0.36,23.88,0.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,128,1000,0.34,37.93,1.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,256,1000,0.34,45.54,1.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,512,1000,0.33,23.86,0.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,1024,1000,0.33,16.59,0.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,2048,1000,0.48,16.67,1.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,4096,1000,0.8,20.77,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,8192,1000,2.69,32.36,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,16384,1000,8.19,58.11,13.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,32768,1000,19.08,97.43,27.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,65536,640,67.4,2075.97,1063.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,131072,320,127.27,442.17,329.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,262144,160,95.38,604.69,316.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,524288,80,162.92,1112.45,569.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,1048576,40,221.09,1397.35,743.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,2097152,20,386.79,2066.71,1118.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,4194304,10,810.43,3915.51,2018.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Gather,144,0,1000,0.04,0.49,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,1,1000,0.57,18.64,1.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,2,1000,0.57,14.0,1.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,4,1000,0.57,14.94,1.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,8,1000,0.57,26.88,2.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,16,1000,0.57,28.95,2.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,32,1000,0.5,14.63,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,64,1000,0.48,15.7,1.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,128,1000,0.5,20.26,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,256,1000,0.51,29.36,2.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,512,1000,0.68,40.3,2.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,1024,1000,0.8,75.46,4.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,2048,1000,1.31,159.34,7.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,4096,1000,2.12,276.35,11.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,8192,1000,3.58,301.46,8.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,16384,1000,6.95,534.4,13.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,32768,1000,13.35,929.72,24.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,65536,640,39.01,1245.51,643.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,131072,320,96.44,2921.75,1468.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,262144,160,179.02,3641.95,1940.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,524288,80,337.38,6714.49,3582.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,1048576,40,237.56,18147.05,9199.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,2097152,20,1969.15,27927.37,16794.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gather,144,4194304,10,12014.96,52650.3,32224.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Gatherv,216,0,1000,2.19,7.58,5.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,1,1000,26.2,150.91,85.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,2,1000,26.87,136.56,83.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,4,1000,26.28,136.8,83.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,8,1000,28.14,139.89,83.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,16,1000,28.94,137.53,83.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,32,1000,27.99,140.36,84.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,64,1000,28.52,145.61,87.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,128,1000,27.43,149.57,88.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,256,1000,29.21,159.83,92.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,512,1000,38.05,215.18,103.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,1024,1000,51.48,217.67,129.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,2048,1000,64.84,287.28,168.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,4096,1000,64.38,279.99,161.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,8192,1000,91.06,464.08,260.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,16384,1000,135.17,765.69,388.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,32768,1000,219.02,1365.25,600.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,65536,640,573.35,2039.34,1419.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,131072,320,765.38,3314.3,2281.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,262144,160,1841.98,6470.9,4798.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,524288,80,4885.44,12505.99,9847.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,1048576,40,11945.99,24122.7,19727.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,2097152,20,24712.45,49032.83,40557.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gatherv,216,4194304,10,34445.3,83062.75,66452.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allreduce,504,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,4,1000,6.27,10.08,8.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,8,1000,8.22,13.1,11.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,16,1000,9.6,12.87,11.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,32,1000,9.52,13.05,11.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,64,1000,11.48,17.05,13.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,128,1000,12.21,22.65,15.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,256,1000,14.27,22.3,17.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,512,1000,14.73,22.26,18.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,1024,1000,20.41,34.98,26.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,2048,1000,22.55,30.38,25.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,4096,1000,30.22,40.02,33.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,8192,1000,48.97,59.2,53.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,16384,1000,125.19,204.83,134.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,32768,1000,101.14,121.86,109.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,65536,640,123.41,156.8,136.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,131072,320,169.16,209.58,187.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,262144,160,327.56,400.48,358.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,524288,80,668.9,803.96,726.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,1048576,40,1727.93,2006.1,1940.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,2097152,20,4037.71,4512.52,4231.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,4194304,10,6304.3,6648.52,6589.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,144,0,1000,2.19,5.63,2.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,1,1000,13.19,19.69,16.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,2,1000,13.95,20.37,16.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,4,1000,24.49,40.02,28.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,8,1000,17.7,24.58,20.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,16,1000,27.47,35.88,30.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,32,1000,26.9,38.41,33.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,64,1000,23.83,43.39,35.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,128,1000,75.79,96.98,91.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,256,1000,88.98,122.62,116.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,512,1000,126.54,183.84,174.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,1024,1000,228.98,285.23,272.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,2048,1000,490.85,640.96,560.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,4096,1000,364.69,420.35,390.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,8192,1000,583.78,662.41,622.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,16384,1000,1069.12,1342.31,1208.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,32768,1000,2043.66,2699.19,2384.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,65536,640,4201.8,5726.5,4986.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,131072,320,7197.69,9180.67,8253.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,262144,160,13399.67,16434.64,14960.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,524288,80,30501.6,31255.49,30892.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,1048576,40,65058.41,66333.84,65667.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,2097152,20,150402.23,156198.68,153262.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgatherv,144,4194304,10,306226.9,317398.01,311749.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,576,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,1,1000,114.2,119.94,116.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,2,1000,115.92,130.59,121.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,4,1000,134.35,151.89,141.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,8,1000,199.2,230.61,215.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,16,1000,163.86,181.25,173.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,32,1000,249.27,279.14,270.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,64,1000,435.52,497.14,476.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,128,1000,827.21,936.44,897.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,256,1000,3067.48,3247.89,3135.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,512,1000,4269.58,4560.09,4437.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,1024,1000,6071.38,6400.34,6253.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,2048,1000,8771.31,8806.34,8791.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,4096,1000,13855.9,13870.21,13861.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,8192,1000,33068.35,33166.62,33121.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,16384,1000,60102.67,60265.97,60180.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,32768,570,117699.65,117891.88,117785.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,65536,237,259377.11,260900.82,260163.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,131072,45,496551.11,498463.74,497702.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,262144,31,846476.88,846780.17,846621.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,524288,20,1777372.97,1781611.81,1778889.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,1048576,12,3375909.78,3385058.32,3378235.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Gather,216,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,1,1000,0.54,11.73,1.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,2,1000,0.56,12.74,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,4,1000,0.56,14.2,1.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,8,1000,0.49,14.15,1.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,16,1000,0.46,12.59,1.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,32,1000,0.46,12.48,1.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,64,1000,0.47,16.35,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,128,1000,0.5,27.03,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,256,1000,0.52,29.68,1.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,512,1000,0.72,48.49,2.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,1024,1000,0.87,82.33,4.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,2048,1000,1.32,206.24,8.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,4096,1000,2.26,252.3,12.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,8192,1000,3.74,435.73,21.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,16384,1000,7.85,847.12,41.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,32768,1000,17.46,2942.8,106.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,65536,640,39.74,1202.87,691.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,131072,320,84.46,2206.06,1244.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,262144,160,159.5,6847.67,2551.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,524288,80,320.46,9198.97,5268.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,1048576,40,223.96,24058.05,15865.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,2097152,20,2074.41,40808.81,25553.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,4194304,10,13069.06,77657.88,52739.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,144,0,1000,0.03,0.04,0.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,1,1000,2.35,6.54,4.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,2,1000,0.62,5.83,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,4,1000,0.61,5.91,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,8,1000,0.62,5.87,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,16,1000,0.61,5.77,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,32,1000,0.61,6.23,4.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,64,1000,0.63,5.91,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,128,1000,0.64,6.03,4.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,256,1000,0.73,6.34,4.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,512,1000,0.67,6.8,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,1024,1000,0.8,7.34,5.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,2048,1000,1.27,5.57,3.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,4096,1000,2.52,8.64,5.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,8192,1000,4.8,12.76,9.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,16384,1000,8.08,20.0,16.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,32768,1000,12.95,31.59,26.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,65536,640,30.29,50.63,45.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,131072,320,61.7,92.0,82.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,262144,160,125.59,151.79,144.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,524288,80,257.89,287.25,278.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,1048576,40,523.87,559.21,546.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,2097152,20,1051.18,1110.36,1086.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,4194304,10,3440.61,3772.76,3613.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,576,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,1,1000,2.11,5.24,4.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,2,1000,2.35,6.4,4.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,4,1000,2.3,6.34,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,8,1000,2.35,6.39,4.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,16,1000,2.14,6.29,4.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,32,1000,2.18,6.27,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,64,1000,2.27,6.27,4.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,128,1000,2.32,6.8,5.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,256,1000,2.35,6.99,5.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,512,1000,1.88,6.85,4.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,1024,1000,1.2,8.77,6.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,2048,1000,2.09,10.69,7.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,4096,1000,3.87,19.42,13.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,8192,1000,7.08,21.81,17.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,16384,1000,10.56,31.69,26.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,32768,1000,25.74,71.03,56.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,65536,640,50.94,91.66,79.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,131072,320,101.27,142.18,128.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,262144,160,150.17,226.35,205.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,524288,80,356.81,402.91,377.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,1048576,40,624.74,752.3,646.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,2097152,20,1207.04,1258.42,1239.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,4194304,10,2436.12,2508.45,2470.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,504,0,1000,1.96,3.27,2.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,4,1000,2.55,17.45,3.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,8,1000,2.54,18.02,3.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,16,1000,2.54,19.07,3.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,32,1000,2.56,451.44,15.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,64,1000,2.27,37.29,5.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,128,1000,2.29,60.9,7.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,256,1000,2.31,22.02,6.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,512,1000,2.56,30.17,9.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,1024,1000,2.89,47.9,16.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,2048,1000,22.27,33.79,28.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,4096,1000,29.91,38.89,34.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,8192,1000,49.67,59.86,54.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,16384,1000,68.79,79.51,73.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,32768,1000,138.23,149.45,143.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,65536,640,358.59,1048.97,397.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,131072,320,775.82,838.82,790.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,262144,160,901.89,1032.81,955.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,524288,80,1182.84,1329.0,1252.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,1048576,40,1550.63,1699.11,1630.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,2097152,20,2629.15,2776.92,2711.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce_scatter,504,4194304,10,4534.39,4682.19,4620.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Reduce,720,0,1000,0.06,0.09,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,4,1000,0.32,10.34,0.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,8,1000,0.35,12.39,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,16,1000,0.35,12.01,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,32,1000,0.35,12.77,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,64,1000,0.36,12.42,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,128,1000,0.33,13.94,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,256,1000,0.34,14.38,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,512,1000,0.32,19.15,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,1024,1000,0.34,15.27,0.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,2048,1000,0.45,17.05,1.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,4096,1000,0.78,23.75,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,8192,1000,2.98,65.9,5.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,16384,1000,8.5,61.19,13.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,32768,1000,19.15,110.36,28.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,65536,640,72.48,2075.7,915.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,131072,320,137.99,400.73,280.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,262144,160,102.18,658.17,330.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,524288,80,164.51,1210.2,578.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,1048576,40,212.52,1426.93,739.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,2097152,20,389.8,2427.44,1131.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,4194304,10,877.15,28545.28,3367.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,216,0,1000,1.04,1.14,1.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,4,1000,1.59,12.37,2.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,8,1000,1.57,13.03,2.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,16,1000,1.6,15.43,2.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,32,1000,1.35,15.54,3.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,64,1000,1.36,16.32,4.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,128,1000,1.38,18.34,4.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,256,1000,1.4,25.62,8.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,512,1000,1.52,23.82,12.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,1024,1000,14.01,21.92,17.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,2048,1000,16.95,24.47,20.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,4096,1000,20.83,34.92,28.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,8192,1000,38.25,56.65,48.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,16384,1000,81.76,109.6,96.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,32768,1000,125.9,155.44,143.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,65536,640,236.34,318.22,270.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,131072,320,324.44,491.72,414.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,262144,160,608.88,692.73,641.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,524288,80,854.14,945.13,890.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,1048576,40,1308.61,1411.51,1352.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,2097152,20,2460.24,2565.92,2517.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce_scatter,216,4194304,10,3208.93,3844.25,3474.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,0,1000,2.9,7.29,2.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,1,1000,17.36,22.27,19.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,2,1000,18.3,24.47,21.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,4,1000,21.0,27.29,23.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,8,1000,21.68,28.75,24.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,16,1000,27.75,36.51,31.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,32,1000,28.78,43.91,36.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,64,1000,76.96,93.26,89.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,128,1000,92.02,119.05,114.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,256,1000,116.05,163.27,156.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,512,1000,203.72,246.13,238.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,1024,1000,311.78,415.05,386.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,2048,1000,548.37,636.79,608.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,4096,1000,570.15,630.05,601.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,8192,1000,934.11,1030.67,981.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,16384,1000,1763.82,2064.76,1915.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,32768,1000,3564.83,4613.66,4186.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,65536,640,6001.84,7124.37,6596.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,131072,320,11964.63,14914.53,13598.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,262144,160,21126.56,24782.11,22923.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,524288,80,46296.34,47212.71,46761.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,1048576,40,99386.05,105163.45,101699.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,2097152,20,256946.48,266772.36,261100.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Allgatherv,216,4194304,10,468557.78,534174.28,489254.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Reduce,432,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,4,1000,0.32,9.67,0.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,8,1000,0.35,9.49,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,16,1000,0.39,8.78,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,32,1000,0.53,13.83,1.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,64,1000,0.36,55.41,1.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,128,1000,0.34,10.29,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,256,1000,0.56,16.08,1.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,512,1000,0.32,13.63,0.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,1024,1000,0.37,26.63,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,2048,1000,0.42,13.97,1.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,4096,1000,0.73,16.87,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,8192,1000,3.0,38.95,5.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,16384,1000,7.57,49.54,12.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,32768,1000,34.11,133.24,81.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,65536,640,79.77,274.63,179.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,131072,320,144.72,365.61,256.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,262144,160,86.07,792.34,394.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,524288,80,149.04,1006.52,531.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,1048576,40,219.13,1327.87,724.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,2097152,20,382.41,2034.74,1096.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,4194304,10,1190.96,3379.71,2892.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,1,1000,1.94,6.88,5.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,2,1000,1.92,6.78,5.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,4,1000,1.87,6.77,5.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,8,1000,1.94,6.69,5.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,16,1000,1.66,6.65,5.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,32,1000,2.03,6.79,5.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,64,1000,1.68,6.79,5.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,128,1000,1.73,7.01,5.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,256,1000,1.81,7.45,5.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,512,1000,1.45,7.23,4.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,1024,1000,1.17,9.84,6.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,2048,1000,2.23,12.5,8.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,4096,1000,3.88,17.28,11.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,8192,1000,6.75,22.42,16.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,16384,1000,10.52,33.33,26.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,32768,1000,21.45,69.6,55.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,65536,640,42.35,90.72,74.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,131072,320,74.65,126.34,109.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,262144,160,147.99,212.4,193.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,524288,80,310.09,389.16,362.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,1048576,40,628.66,762.4,716.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,2097152,20,1233.49,1467.3,1384.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Bcast,432,4194304,10,2532.57,2951.38,2801.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Gather,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,1,1000,0.55,23.43,1.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,2,1000,0.55,30.37,1.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,4,1000,0.56,14.62,1.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,8,1000,0.56,13.93,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,16,1000,0.48,14.7,1.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,32,1000,0.47,13.94,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,64,1000,0.47,15.71,1.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,128,1000,0.5,24.16,1.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,256,1000,0.51,27.57,1.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,512,1000,0.72,59.77,3.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,1024,1000,0.85,103.26,4.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,2048,1000,1.17,203.82,8.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,4096,1000,2.22,262.62,12.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,8192,1000,3.65,455.59,21.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,16384,1000,8.36,958.56,45.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,32768,1000,17.72,3241.2,121.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,65536,640,52.05,2449.7,1139.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,131072,320,81.1,2919.74,1684.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,262144,160,156.49,4861.8,2795.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,524288,80,318.47,9483.27,5446.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,1048576,40,234.72,24208.09,15977.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,2097152,20,1686.53,41317.98,25039.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Gather,216,4194304,10,12460.14,76952.18,52753.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,3, 100
+Bcast,648,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,1,1000,2.08,6.93,5.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,2,1000,2.37,6.83,5.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,4,1000,2.45,6.81,5.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,8,1000,2.37,6.77,5.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,16,1000,2.36,6.72,5.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,32,1000,2.49,6.76,5.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,64,1000,2.49,6.87,5.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,128,1000,2.52,7.01,5.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,256,1000,2.55,7.53,6.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,512,1000,2.23,7.57,6.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,1024,1000,2.25,7.22,5.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,2048,1000,4.49,11.07,8.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,4096,1000,8.02,18.06,13.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,8192,1000,9.87,25.12,19.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,16384,1000,16.57,37.54,30.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,32768,1000,34.28,67.13,59.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,65536,640,46.25,101.33,86.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,131072,320,84.51,138.72,124.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,262144,160,151.71,228.83,208.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,524288,80,311.56,452.16,396.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,1048576,40,703.68,753.73,724.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,2097152,20,1299.51,1357.76,1338.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Bcast,648,4194304,10,3869.28,4077.54,3965.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,9, 100
+Alltoall,144,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,1,1000,32.61,37.92,35.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,2,1000,33.32,38.0,35.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,4,1000,35.27,43.07,39.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,8,1000,49.69,59.24,54.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,16,1000,39.61,48.87,44.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,32,1000,49.55,61.94,56.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,64,1000,56.26,79.44,70.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,128,1000,98.72,129.65,118.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,256,1000,161.88,239.97,214.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,512,1000,340.94,369.48,359.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,1024,1000,473.29,512.55,502.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,2048,1000,894.11,940.28,928.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,4096,1000,1938.29,2368.57,2126.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,8192,1000,3641.34,3671.93,3653.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,16384,1000,7741.57,7824.64,7776.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,32768,1000,14899.51,15003.26,14942.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,65536,640,28196.47,28277.52,28238.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,131072,19,80989.15,86392.58,82898.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,262144,19,111419.66,111635.78,111533.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,524288,19,222550.06,223000.41,222835.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,1048576,19,444484.16,445342.6,444940.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,2097152,19,907058.88,908870.37,907973.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Alltoall,144,4194304,10,1781171.19,1786008.81,1783761.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allreduce,576,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,4,1000,6.97,9.67,8.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,8,1000,13.23,20.67,18.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,16,1000,9.17,16.93,15.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,32,1000,8.88,12.04,10.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,64,1000,11.6,19.53,15.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,128,1000,10.7,18.37,13.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,256,1000,12.81,20.28,16.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,512,1000,15.61,23.45,18.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,1024,1000,17.95,26.16,22.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,2048,1000,32.55,42.35,35.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,4096,1000,22.0,26.97,23.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,8192,1000,43.55,52.68,46.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,16384,1000,101.0,114.12,106.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,32768,1000,325.36,356.23,336.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,65536,640,96.01,128.53,106.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,131072,320,175.46,218.37,189.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,262144,160,301.11,370.94,323.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,524288,80,687.84,838.75,727.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,1048576,40,1594.05,1926.08,1701.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,2097152,20,3233.09,3281.02,3263.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Allreduce,576,4194304,10,5586.27,5655.79,5636.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Scatterv,144,0,1000,6.09,11.96,8.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,1,1000,6.62,20.39,9.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,2,1000,6.6,19.39,9.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,4,1000,6.7,13.02,9.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,8,1000,6.87,19.03,10.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,16,1000,7.53,14.95,11.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,32,1000,7.08,12.7,9.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,64,1000,7.93,13.87,10.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,128,1000,7.9,15.21,11.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,256,1000,9.3,17.7,13.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,512,1000,10.54,34.8,21.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,1024,1000,13.13,35.42,26.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,2048,1000,16.11,57.15,44.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,4096,1000,12.82,154.54,100.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,8192,1000,37.99,287.84,179.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,16384,1000,46.7,501.83,313.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,32768,1000,59.63,871.95,534.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,65536,640,82.95,1384.82,798.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,131072,320,122.91,2515.98,1440.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,262144,160,647.21,9297.87,5805.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,524288,80,919.77,24062.98,13080.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,1048576,40,1280.05,36306.85,19518.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,2097152,20,1872.12,78197.59,41250.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,4194304,10,4413.37,160060.62,84675.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,1,1000,39.85,51.27,48.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,2,1000,44.1,63.95,54.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,4,1000,35.5,43.83,39.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,8,1000,42.69,50.53,46.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,16,1000,39.64,51.08,45.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,32,1000,48.56,68.61,57.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,64,1000,56.91,78.07,70.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,128,1000,100.02,135.91,123.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,256,1000,158.75,235.65,209.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,512,1000,354.19,381.4,373.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,1024,1000,476.57,516.52,506.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,2048,1000,901.48,940.79,929.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,4096,1000,1707.94,1840.06,1795.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,8192,1000,3644.42,3672.81,3655.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,16384,1000,7807.15,7879.51,7837.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,32768,1000,14975.18,15101.79,15034.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,65536,640,28276.29,28378.53,28324.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,131072,320,57271.58,57423.26,57348.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,262144,160,113832.9,114143.9,113967.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,524288,80,223052.62,223726.12,223380.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,1048576,40,448019.38,449450.9,448923.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,2097152,20,894854.29,897525.84,896271.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,4194304,10,1775373.88,1780387.35,1778300.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,360,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,1,1000,1.47,6.02,4.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,2,1000,1.5,6.79,5.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,4,1000,1.51,6.19,4.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,8,1000,1.49,6.22,4.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,16,1000,1.4,6.09,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,32,1000,1.41,6.08,4.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,64,1000,1.41,6.15,4.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,128,1000,1.45,6.24,5.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,256,1000,1.55,11.5,5.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,512,1000,1.31,6.8,5.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,1024,1000,0.93,9.38,6.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,2048,1000,1.61,11.5,7.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,4096,1000,2.97,16.57,11.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,8192,1000,6.17,24.24,18.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,16384,1000,9.2,32.58,26.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,32768,1000,16.72,64.65,51.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,65536,640,35.58,83.57,71.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,131072,320,65.91,126.83,109.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,262144,160,147.44,212.28,190.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,524288,80,260.66,388.86,360.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,1048576,40,539.33,889.24,709.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,2097152,20,1049.67,1459.72,1370.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,360,4194304,10,2196.31,2939.88,2776.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Bcast,576,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,1,1000,2.11,5.53,4.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,2,1000,2.31,6.42,4.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,4,1000,2.32,6.42,4.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,8,1000,2.31,6.45,4.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,16,1000,2.22,6.39,4.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,32,1000,2.23,6.41,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,64,1000,2.25,6.32,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,128,1000,2.31,6.56,5.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,256,1000,2.35,7.08,5.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,512,1000,1.95,6.62,4.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,1024,1000,1.19,8.66,6.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,2048,1000,2.06,10.49,7.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,4096,1000,5.22,115.06,15.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,8192,1000,9.22,29.68,23.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,16384,1000,14.25,43.18,36.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,32768,1000,23.27,64.48,50.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,65536,640,48.67,88.91,73.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,131072,320,87.26,126.21,111.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,262144,160,148.07,219.17,202.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,524288,80,357.36,392.1,378.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,1048576,40,640.09,674.24,660.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,2097152,20,1216.98,1264.81,1249.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Bcast,576,4194304,10,2475.42,2536.23,2503.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,8, 100
+Gatherv,288,0,1000,2.69,9.75,5.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,1,1000,34.57,211.05,142.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,2,1000,34.87,210.31,141.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,4,1000,33.57,211.43,142.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,8,1000,34.36,212.25,142.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,16,1000,34.44,212.63,142.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,32,1000,34.68,215.08,144.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,64,1000,35.15,233.69,158.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,128,1000,35.65,240.04,163.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,256,1000,36.5,244.13,166.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,512,1000,47.88,683.91,199.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,1024,1000,60.0,342.29,245.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,2048,1000,69.24,437.67,320.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,4096,1000,76.15,486.72,358.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,8192,1000,104.14,651.2,490.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,16384,1000,168.64,1470.15,895.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,32768,1000,243.96,2386.23,1540.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,65536,640,391.79,2305.69,1429.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,131072,320,732.02,4159.62,2509.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,262144,160,1351.27,7933.8,4725.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,524288,80,3699.9,15624.11,9527.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,1048576,40,12005.51,30387.01,19198.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,2097152,20,24968.04,61683.69,39309.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Gatherv,288,4194304,10,34376.45,107795.71,63064.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Scatter,504,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,1,1000,1.2,11.68,7.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,2,1000,1.29,12.16,7.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,4,1000,1.55,13.03,8.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,8,1000,1.94,11.52,7.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,16,1000,3.02,13.92,8.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,32,1000,5.37,17.4,12.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,64,1000,8.78,25.04,17.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,128,1000,13.94,32.07,23.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,256,1000,42.66,71.41,57.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,512,1000,64.61,117.46,87.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,1024,1000,88.58,137.29,107.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,2048,1000,137.77,225.81,171.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,4096,1000,220.78,333.37,264.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,8192,1000,407.66,1012.97,494.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,16384,1000,786.77,1448.15,906.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,32768,1000,19.54,2068.53,963.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,65536,640,28.13,2583.72,1500.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,131072,320,83.83,5630.54,3937.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,262144,160,184.22,14977.42,5117.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,524288,80,277.92,18526.41,12119.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,1048576,40,338.84,37010.18,29249.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,2097152,20,2307.07,74014.43,60262.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Scatter,504,4194304,10,3855.58,149836.67,124795.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,7, 100
+Allreduce,360,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,4,1000,5.49,10.05,8.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,8,1000,6.03,10.57,8.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,16,1000,8.16,11.3,9.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,32,1000,8.35,11.62,10.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,64,1000,9.86,15.28,12.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,128,1000,13.33,21.99,18.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,256,1000,12.3,20.04,15.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,512,1000,12.14,21.7,14.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,1024,1000,15.81,22.12,18.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,2048,1000,17.45,23.12,19.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,4096,1000,27.58,36.33,30.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,8192,1000,42.4,51.19,45.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,16384,1000,90.36,115.75,99.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,32768,1000,91.02,109.15,100.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,65536,640,127.93,153.14,136.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,131072,320,209.53,268.56,233.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,262144,160,296.45,365.12,322.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,524288,80,628.7,776.94,684.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,1048576,40,1598.28,1957.83,1783.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,2097152,20,3553.33,3764.23,3651.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,4194304,10,6121.1,6525.17,6298.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,648,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,1,1000,2.2,6.21,4.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,2,1000,2.48,6.84,5.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,4,1000,2.55,6.82,5.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,8,1000,2.48,6.69,5.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,16,1000,2.48,6.65,5.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,32,1000,2.48,6.76,5.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,64,1000,2.51,6.69,5.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,128,1000,2.58,6.97,5.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,256,1000,2.67,7.47,6.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,512,1000,2.06,6.28,4.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,1024,1000,2.12,7.48,5.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,2048,1000,4.62,11.31,8.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,4096,1000,8.41,18.33,13.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,8192,1000,7.29,23.23,18.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,16384,1000,18.85,42.28,35.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,32768,1000,36.01,71.35,63.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,65536,640,49.93,110.35,95.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,131072,320,88.25,147.62,133.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,262144,160,154.12,234.26,211.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,524288,80,316.41,423.41,399.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,1048576,40,685.42,713.31,705.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,2097152,20,1302.34,1347.69,1332.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,4194304,10,3819.19,4364.27,3974.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,216,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,4,1000,0.39,34.0,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,8,1000,0.36,15.78,0.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,16,1000,0.35,18.76,0.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,32,1000,0.35,46.03,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,64,1000,0.36,11.4,0.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,128,1000,0.34,12.18,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,256,1000,0.35,11.46,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,512,1000,0.36,11.35,0.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,1024,1000,0.33,10.03,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,2048,1000,0.4,11.54,1.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,4096,1000,0.75,31.44,2.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,8192,1000,2.71,26.74,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,16384,1000,7.03,33.19,11.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,32768,1000,40.47,134.92,82.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,65536,640,64.69,204.64,140.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,131072,320,124.11,332.33,236.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,262144,160,84.67,745.57,385.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,524288,80,144.73,941.97,511.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,1048576,40,228.32,1266.6,717.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,2097152,20,494.24,1695.59,1430.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,4194304,10,681.46,3878.86,2060.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,432,0,1000,1.73,1.86,1.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,4,1000,2.28,15.59,3.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,8,1000,2.31,16.31,3.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,16,1000,2.31,19.39,3.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,32,1000,2.31,19.51,3.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,64,1000,2.07,19.33,4.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,128,1000,2.07,21.11,5.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,256,1000,2.06,21.64,6.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,512,1000,2.32,30.84,10.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,1024,1000,2.64,35.9,19.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,2048,1000,37.09,49.62,42.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,4096,1000,27.1,43.01,36.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,8192,1000,56.03,72.23,65.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,16384,1000,104.34,131.08,117.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,32768,1000,155.12,200.58,183.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,65536,640,269.18,385.54,345.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,131072,320,699.52,790.2,751.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,262144,160,774.78,899.38,825.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,524288,80,1175.6,1311.61,1241.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,1048576,40,1608.87,1734.62,1670.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,2097152,20,2762.82,2894.64,2827.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Reduce_scatter,432,4194304,10,4686.47,4925.22,4773.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,6, 100
+Allreduce,288,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,4,1000,4.87,7.21,6.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,8,1000,5.47,8.63,7.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,16,1000,6.73,10.2,8.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,32,1000,6.07,9.32,7.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,64,1000,7.4,12.79,9.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,128,1000,8.42,15.82,11.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,256,1000,10.13,17.72,13.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,512,1000,11.88,18.9,15.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,1024,1000,12.78,18.04,14.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,2048,1000,12.85,17.62,14.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,4096,1000,16.75,21.24,18.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,8192,1000,33.62,39.09,35.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,16384,1000,90.5,101.41,94.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,32768,1000,62.89,73.94,67.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,65536,640,91.95,113.06,100.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,131072,320,152.05,188.33,165.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,262144,160,280.65,342.56,300.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,524288,80,587.26,723.82,626.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,1048576,40,1979.06,2460.62,2229.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,2097152,20,3222.4,3259.8,3246.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Allreduce,288,4194304,10,5338.59,5376.39,5361.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,4, 100
+Reduce_scatter,144,0,1000,0.79,0.88,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,4,1000,1.09,23.47,4.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,8,1000,1.08,17.23,4.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,16,1000,1.09,31.31,5.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,32,1000,1.09,14.15,4.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,64,1000,1.12,15.86,5.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,128,1000,1.7,17.19,6.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,256,1000,1.8,19.12,9.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,512,1000,5.52,18.12,13.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,1024,1000,10.94,20.74,15.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,2048,1000,13.2,23.27,17.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,4096,1000,18.66,29.16,23.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,8192,1000,29.9,43.44,36.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,16384,1000,57.93,96.09,73.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,32768,1000,144.34,212.7,172.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,65536,640,202.38,278.66,233.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,131072,320,347.14,477.62,413.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,262144,160,495.99,575.38,528.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,524288,80,758.64,845.57,794.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,1048576,40,1235.04,1356.76,1289.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,2097152,20,1767.77,1994.9,1867.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Reduce_scatter,144,4194304,10,2791.22,3281.73,3008.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,2, 100
+Allgather,360,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,1,1000,16.42,24.02,20.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,2,1000,16.05,25.03,20.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,4,1000,16.13,26.29,21.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,8,1000,25.8,37.58,31.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,16,1000,29.31,42.02,36.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,32,1000,52.57,73.45,62.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,64,1000,43.58,91.16,77.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,128,1000,58.03,132.39,114.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,256,1000,109.76,212.56,190.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,512,1000,250.23,341.94,314.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,1024,1000,502.24,653.07,623.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,2048,1000,647.84,937.25,844.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,4096,1000,1086.85,1381.03,1315.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,8192,1000,1619.43,1778.26,1686.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,16384,1000,3025.2,3313.71,3173.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,32768,1000,6176.77,7235.39,6707.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,65536,640,13009.43,15357.83,14115.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,131072,320,21620.77,26387.44,23557.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,262144,160,41273.9,57231.99,47813.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,524288,80,75355.88,76910.61,76041.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,1048576,40,165245.66,170802.02,167346.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,2097152,20,384871.29,420913.47,398220.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,360,4194304,10,816091.21,892388.5,864850.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_27_02-42-36,5, 100
+Allgather,432,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,1,1000,18.68,26.76,23.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,2,1000,15.54,25.33,20.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,4,1000,17.7,27.94,22.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,8,1000,26.47,37.82,32.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,16,1000,32.59,48.72,41.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,32,1000,55.58,84.28,71.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,64,1000,56.05,106.0,90.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,128,1000,71.76,147.87,130.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,256,1000,151.85,240.83,217.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,512,1000,357.64,932.41,500.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,1024,1000,477.25,555.98,530.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,2048,1000,777.76,916.29,857.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,4096,1000,1563.21,1953.25,1691.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,8192,1000,1933.81,2119.86,2037.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,16384,1000,4080.39,4769.16,4427.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,32768,1000,7266.21,8417.69,7883.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,65536,640,13625.6,15734.0,14737.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,131072,320,25963.22,33237.2,29373.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,262144,160,56859.47,75422.9,65373.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,524288,80,97818.56,101850.33,99964.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,1048576,40,197938.98,209374.39,202984.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,2097152,20,459779.14,482690.92,468506.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,4194304,10,941958.91,1045540.92,997641.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
diff --git a/results-and-plotting/data/data-multinode-defcflag-nompiopt.csv b/results-and-plotting/data/data-multinode-defcflag-nompiopt.csv
new file mode 100644
index 0000000..b9df91b
--- /dev/null
+++ b/results-and-plotting/data/data-multinode-defcflag-nompiopt.csv
@@ -0,0 +1,1838 @@
+benchmark_type,proc_num,msg_size_bytes,repetitions,t_min_usec,t_max_usec,t_avg_usec,mpi_datatype,mpi_red_datatype,mpi_red_op,creation_time,n_nodes,off_cache_flag
+Allgather,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,1,1000,10.57,16.73,13.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,2,1000,10.88,16.99,13.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,4,1000,15.87,21.35,18.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,8,1000,15.41,23.46,18.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,16,1000,19.03,32.5,24.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,32,1000,17.33,25.9,22.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,64,1000,41.97,73.53,60.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,128,1000,37.96,59.65,55.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,256,1000,73.91,122.28,115.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,512,1000,156.82,204.4,195.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,1024,1000,283.96,392.22,362.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,2048,1000,361.54,422.5,402.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,4096,1000,662.02,765.06,733.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,8192,1000,921.0,1019.96,966.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,16384,1000,1725.57,1999.2,1865.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,32768,1000,3348.54,4028.13,3714.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,65536,640,6109.06,7840.18,7055.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,131072,320,11323.31,15691.65,13379.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,262144,160,24153.56,34082.06,29876.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,524288,80,45574.32,46673.77,46103.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,1048576,40,114311.24,123854.17,118628.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,2097152,20,227370.84,235668.47,231962.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,216,4194304,10,463107.31,479481.28,472209.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,288,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,1,1000,0.98,8.79,3.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,2,1000,1.06,10.23,4.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,4,1000,1.32,12.56,5.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,8,1000,1.51,10.59,5.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,16,1000,2.37,14.17,5.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,32,1000,3.67,13.47,7.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,64,1000,4.79,17.66,10.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,128,1000,6.5,23.26,14.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,256,1000,9.32,32.73,22.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,512,1000,15.25,59.24,42.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,1024,1000,25.34,88.55,68.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,2048,1000,31.57,156.34,114.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,4096,1000,49.42,240.98,183.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,8192,1000,88.75,453.22,331.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,16384,1000,164.91,798.1,579.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,32768,1000,17.99,897.57,413.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,65536,640,26.37,1235.34,600.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,131072,320,89.38,2377.65,1226.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,262144,160,197.45,4787.58,2729.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,524288,80,185.82,9309.36,6161.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,1048576,40,348.13,18588.13,13870.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,2097152,20,10404.14,37183.36,29353.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatter,288,4194304,10,23610.38,74335.8,60676.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,504,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,1,1000,96.67,105.67,100.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,2,1000,99.8,108.43,103.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,4,1000,116.39,130.36,123.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,8,1000,135.0,157.19,145.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,16,1000,140.99,161.29,151.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,32,1000,205.45,242.53,225.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,64,1000,356.65,429.02,397.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,128,1000,664.22,807.72,753.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,256,1000,4585.32,4938.58,4769.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,512,1000,3535.25,3783.66,3643.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,1024,1000,5866.61,6108.32,5972.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,2048,1000,6763.5,6773.76,6767.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,4096,1000,11784.65,11801.76,11791.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,8192,1000,26613.05,26726.5,26683.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,16384,1000,48585.12,48650.12,48610.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,32768,419,93168.83,93404.7,93263.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,65536,282,219448.69,220923.58,220171.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,131072,133,373249.58,374068.3,373691.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,262144,33,764856.87,766397.64,765511.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,524288,24,1461043.85,1464006.24,1462611.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,1048576,13,2816470.48,2817955.54,2817233.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,504,2097152,7,5561989.43,5566037.38,5564097.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,360,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,1,1000,1.13,10.14,5.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,2,1000,1.23,12.25,6.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,4,1000,1.48,14.19,7.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,8,1000,1.82,12.25,6.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,16,1000,2.87,12.39,7.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,32,1000,4.43,15.77,9.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,64,1000,6.45,19.6,12.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,128,1000,10.26,26.44,17.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,256,1000,18.68,38.01,26.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,512,1000,28.37,72.51,52.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,1024,1000,43.99,98.95,75.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,2048,1000,52.53,158.73,116.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,4096,1000,84.01,269.7,194.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,8192,1000,148.6,506.52,354.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,16384,1000,271.91,901.26,632.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,32768,1000,32.16,1268.99,613.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,65536,640,47.38,2389.03,970.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,131072,320,89.65,3204.45,1672.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,262144,160,195.47,6208.03,3481.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,524288,80,245.76,12387.93,8173.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,1048576,40,5343.85,24788.75,18554.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,2097152,20,5718.99,49723.72,39721.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,360,4194304,10,14888.06,98882.01,81608.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,216,0,1000,6.81,12.37,9.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,1,1000,7.7,14.33,10.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,2,1000,7.78,14.45,10.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,4,1000,7.86,15.01,11.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,8,1000,6.9,13.18,9.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,16,1000,7.63,14.62,10.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,32,1000,7.93,14.76,10.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,64,1000,9.52,17.16,12.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,128,1000,10.94,19.7,14.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,256,1000,12.96,24.68,17.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,512,1000,19.8,46.59,29.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,1024,1000,18.2,47.31,36.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,2048,1000,22.52,74.08,56.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,4096,1000,14.3,158.92,94.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,8192,1000,40.32,293.16,170.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,16384,1000,50.56,512.46,293.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,32768,1000,58.75,955.95,513.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,65536,640,53.89,1019.31,646.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,131072,320,71.71,1991.49,1206.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,262144,160,357.69,5781.97,3616.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,524288,80,572.66,17852.62,10242.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,1048576,40,1141.43,36863.99,20677.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,2097152,20,1845.85,74600.57,43593.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatterv,216,4194304,10,4259.22,155513.71,89297.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,288,0,1000,3.54,9.14,3.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,1,1000,20.95,27.39,24.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,2,1000,22.98,29.21,26.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,4,1000,23.97,33.02,28.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,8,1000,27.29,39.3,33.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,16,1000,29.44,39.6,35.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,32,1000,43.66,59.57,53.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,64,1000,87.37,107.77,103.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,128,1000,107.84,151.89,138.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,256,1000,139.94,204.35,191.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,512,1000,241.95,320.36,299.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,1024,1000,387.19,422.06,416.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,2048,1000,494.3,523.08,514.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,4096,1000,768.11,862.42,812.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,8192,1000,1592.49,2012.27,1797.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,16384,1000,2403.85,2725.12,2574.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,32768,1000,5084.1,5918.33,5572.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,65536,640,8272.72,9381.7,8864.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,131072,320,15765.1,17667.6,16790.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,262144,160,29713.78,33490.6,31608.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,524288,80,60174.37,61321.17,60720.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,1048576,40,130692.34,135512.74,132434.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,2097152,20,306921.18,316159.26,311175.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,288,4194304,10,731431.84,757103.4,744569.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,432,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,1,1000,1.72,6.54,5.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,2,1000,1.77,6.66,5.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,4,1000,1.75,6.57,5.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,8,1000,1.75,6.52,5.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,16,1000,1.65,6.49,5.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,32,1000,1.66,6.54,5.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,64,1000,1.67,6.55,5.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,128,1000,1.72,6.76,5.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,256,1000,1.82,7.46,5.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,512,1000,1.46,7.28,4.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,1024,1000,1.15,9.94,6.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,2048,1000,2.1,12.22,7.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,4096,1000,3.79,17.03,11.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,8192,1000,7.21,23.74,17.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,16384,1000,11.36,35.84,28.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,32768,1000,23.03,72.94,58.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,65536,640,55.43,182.91,97.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,131072,320,128.21,320.3,182.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,262144,160,149.81,213.75,194.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,524288,80,308.8,387.87,360.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,1048576,40,615.18,745.94,699.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,2097152,20,1221.82,1451.78,1372.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Bcast,432,4194304,10,2487.21,2952.62,2766.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,144,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,1,1000,9.26,12.36,10.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,2,1000,11.81,17.19,14.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,4,1000,12.12,18.04,14.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,8,1000,38.51,83.04,65.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,16,1000,15.88,33.16,24.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,32,1000,20.72,35.14,28.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,64,1000,16.97,27.56,23.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,128,1000,24.71,65.5,47.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,256,1000,82.02,117.79,107.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,512,1000,89.82,153.35,140.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,1024,1000,187.46,254.41,237.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,2048,1000,246.71,280.16,270.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,4096,1000,460.53,487.15,479.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,8192,1000,906.49,933.17,925.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,16384,1000,1065.67,1350.08,1210.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,32768,1000,2049.88,2658.17,2370.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,65536,640,3934.58,5068.27,4539.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,131072,320,8763.18,11684.88,10190.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,262144,160,15793.14,21271.18,18524.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,524288,80,29828.24,31021.35,30321.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,1048576,40,66274.39,67470.55,66904.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,2097152,20,152919.25,160346.29,156313.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,144,4194304,10,306392.56,315129.92,310290.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,360,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,1,1000,16.97,24.01,20.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,2,1000,15.32,23.48,19.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,4,1000,15.48,26.33,21.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,8,1000,36.74,47.22,42.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,16,1000,41.2,123.11,117.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,32,1000,61.78,83.64,75.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,64,1000,38.94,86.87,72.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,128,1000,57.83,129.07,113.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,256,1000,116.66,218.48,195.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,512,1000,251.93,341.5,313.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,1024,1000,366.97,469.35,448.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,2048,1000,544.12,708.87,676.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,4096,1000,1417.2,2062.98,1643.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,8192,1000,1604.21,1751.74,1679.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,16384,1000,3055.81,3360.38,3208.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,32768,1000,6037.96,6858.48,6421.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,65536,640,11168.82,13141.89,12066.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,131072,320,20916.24,25917.18,22679.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,262144,160,41080.41,59282.3,49319.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,524288,80,89755.41,93460.99,91510.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,1048576,40,174125.64,180537.11,176406.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,2097152,20,382006.11,394057.29,387057.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgather,360,4194304,10,778495.96,801549.8,789961.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,1,1000,0.5,11.78,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,2,1000,0.55,14.65,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,4,1000,0.55,14.54,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,8,1000,0.49,12.61,1.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,16,1000,0.46,13.88,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,32,1000,0.46,15.61,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,64,1000,0.47,20.33,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,128,1000,0.49,31.92,1.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,256,1000,0.56,45.01,2.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,512,1000,0.89,92.17,4.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,1024,1000,0.99,177.13,6.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,2048,1000,1.29,209.63,8.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,4096,1000,2.16,333.88,12.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,8192,1000,3.83,638.7,23.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,16384,1000,8.03,1200.78,43.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,32768,1000,14.23,3012.16,86.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,65536,640,32.83,2455.66,1362.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,131072,320,81.68,4595.0,2492.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,262144,160,164.12,9123.55,4961.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,524288,80,314.45,18311.76,10001.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,1048576,40,233.94,36747.9,19914.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,2097152,20,2401.14,73200.28,41005.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,360,4194304,10,11913.15,130965.02,69796.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatter,504,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,1,1000,1.23,13.66,6.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,2,1000,1.42,13.14,8.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,4,1000,1.7,13.2,8.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,8,1000,2.1,12.05,7.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,16,1000,3.37,27.7,9.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,32,1000,5.72,18.82,12.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,64,1000,8.48,25.07,17.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,128,1000,13.81,32.9,24.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,256,1000,26.36,52.61,39.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,512,1000,48.29,80.16,61.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,1024,1000,78.04,110.48,91.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,2048,1000,121.84,528.95,150.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,4096,1000,218.83,321.5,261.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,8192,1000,403.3,607.27,481.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,16384,1000,775.69,1104.7,899.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,32768,1000,33.12,1829.57,861.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,65536,640,25.02,2466.57,1237.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,131072,320,94.12,4877.4,2686.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,262144,160,184.56,9297.66,5192.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,524288,80,277.42,18562.05,12454.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,1048576,40,4431.12,37015.58,28247.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,2097152,20,3228.8,74041.41,59807.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,504,4194304,10,7007.2,148022.41,124614.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,0,1000,0.03,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,1,1000,2.04,7.17,5.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,2,1000,2.03,7.03,5.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,4,1000,2.04,6.97,5.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,8,1000,2.03,6.98,5.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,16,1000,1.93,6.8,5.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,32,1000,1.93,6.87,5.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,64,1000,1.93,6.93,5.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,128,1000,2.01,7.09,5.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,256,1000,2.09,7.83,6.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,512,1000,1.65,7.51,4.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,1024,1000,1.32,10.74,7.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,2048,1000,2.08,11.69,8.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,4096,1000,3.78,15.94,12.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,8192,1000,6.82,21.84,17.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,16384,1000,14.65,44.11,37.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,32768,1000,24.03,76.51,61.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,65536,640,60.46,159.69,106.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,131072,320,93.72,141.19,125.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,262144,160,151.28,215.91,200.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,524288,80,314.69,388.68,373.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,1048576,40,618.85,740.01,716.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,2097152,20,1220.81,1448.33,1404.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Bcast,504,4194304,10,2509.66,2945.06,2832.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,720,0,1000,2.62,3.15,2.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,4,1000,3.19,26.44,4.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,8,1000,3.21,21.59,3.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,16,1000,3.23,44.96,4.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,32,1000,2.95,27.84,6.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,64,1000,2.93,27.51,7.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,128,1000,2.96,26.51,7.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,256,1000,2.99,32.21,9.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,512,1000,3.26,52.51,14.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,1024,1000,3.67,45.68,19.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,2048,1000,11.6,52.46,38.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,4096,1000,47.95,62.96,55.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,8192,1000,90.08,114.35,99.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,16384,1000,145.43,171.96,162.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,32768,1000,229.27,249.88,240.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,65536,640,402.68,445.81,432.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,131072,320,324.81,664.95,494.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,262144,160,665.32,1025.41,851.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,524288,80,1398.56,1575.96,1484.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,1048576,40,9702.47,15742.67,10220.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,2097152,20,4050.88,4990.16,4167.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce_scatter,720,4194304,10,4959.18,5201.77,5105.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Gather,432,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,1,1000,0.49,12.48,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,2,1000,0.55,14.54,1.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,4,1000,0.55,15.69,1.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,8,1000,0.49,13.0,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,16,1000,0.46,13.88,1.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,32,1000,0.46,16.25,1.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,64,1000,0.47,21.94,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,128,1000,0.49,28.73,1.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,256,1000,0.53,46.62,2.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,512,1000,0.87,92.22,3.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,1024,1000,1.04,195.0,5.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,2048,1000,1.3,221.16,9.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,4096,1000,2.32,365.27,13.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,8192,1000,4.03,708.91,24.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,16384,1000,8.0,1364.87,45.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,32768,1000,14.24,3564.19,88.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,65536,640,33.16,2950.05,1639.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,131072,320,85.42,5435.55,2969.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,262144,160,160.39,12616.47,5788.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,524288,80,316.19,21500.91,11765.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,1048576,40,232.5,42935.8,23389.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,2097152,20,1541.23,85835.56,47844.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gather,432,4194304,10,11427.24,155717.72,82565.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,1,1000,83.68,91.84,87.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,2,1000,86.56,96.24,90.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,4,1000,94.17,111.15,101.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,8,1000,119.84,146.6,132.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,16,1000,115.37,129.84,123.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,32,1000,168.7,194.7,182.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,64,1000,294.62,347.0,320.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,128,1000,521.24,630.04,585.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,256,1000,1495.01,1528.79,1513.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,512,1000,1935.64,1967.86,1953.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,1024,1000,3288.84,3329.13,3311.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,2048,1000,5259.44,5268.7,5263.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,4096,1000,9614.34,9629.98,9620.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,8192,1000,22302.73,22362.94,22328.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,16384,1000,37790.21,37859.18,37820.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,32768,799,82389.02,82530.65,82452.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,65536,30,184717.65,187188.48,185466.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,131072,19,297612.79,297796.71,297710.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,262144,19,590295.88,590643.91,590434.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,524288,19,1222252.97,1227975.87,1225304.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,1048576,16,2325104.72,2326458.69,2325839.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Alltoall,432,2097152,9,4629037.42,4631918.19,4630475.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,0,1000,1.71,1.87,1.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,4,1000,2.25,14.3,3.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,8,1000,2.29,16.29,3.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,16,1000,2.3,17.0,3.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,32,1000,2.29,19.01,3.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,64,1000,2.05,18.52,4.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,128,1000,2.07,20.15,5.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,256,1000,2.07,21.88,6.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,512,1000,2.33,30.91,10.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,1024,1000,2.64,31.43,17.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,2048,1000,26.18,38.63,32.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,4096,1000,33.9,49.21,42.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,8192,1000,48.01,67.74,60.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,16384,1000,99.95,125.29,113.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,32768,1000,183.0,215.5,203.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,65536,640,272.42,383.6,344.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,131072,320,713.82,801.7,763.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,262144,160,726.18,852.46,777.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,524288,80,1161.75,1308.35,1230.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,1048576,40,1643.13,1787.68,1716.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,2097152,20,2870.8,3021.22,2947.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,432,4194304,10,4594.57,4742.44,4677.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,288,0,1000,7.69,13.37,9.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,1,1000,8.2,15.03,10.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,2,1000,9.19,17.41,12.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,4,1000,9.47,17.93,12.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,8,1000,8.4,15.62,11.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,16,1000,8.73,15.63,11.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,32,1000,9.43,16.82,12.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,64,1000,10.33,19.65,14.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,128,1000,12.45,22.78,16.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,256,1000,15.3,29.65,22.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,512,1000,22.56,46.94,35.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,1024,1000,21.78,56.3,44.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,2048,1000,14.56,90.04,63.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,4096,1000,15.4,148.46,95.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,8192,1000,40.6,284.43,181.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,16384,1000,49.09,516.09,328.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,32768,1000,39.39,807.93,542.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,65536,640,55.88,1707.63,1085.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,131072,320,239.75,2725.96,2097.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,262144,160,348.12,5761.92,4170.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,524288,80,629.92,17461.57,11342.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,1048576,40,1095.57,36339.8,24069.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,2097152,20,1839.48,74472.38,50098.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Scatterv,288,4194304,10,4082.84,154891.11,101934.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,0,1000,0.05,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,4,1000,5.22,8.03,6.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,8,1000,6.3,9.67,7.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,16,1000,6.59,10.22,8.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,32,1000,6.45,9.8,7.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,64,1000,8.26,13.48,10.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,128,1000,8.95,15.86,11.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,256,1000,10.04,17.51,13.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,512,1000,8.8,13.02,10.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,1024,1000,12.35,17.57,14.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,2048,1000,12.58,17.19,14.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,4096,1000,16.9,21.28,18.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,8192,1000,35.62,43.25,39.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,16384,1000,86.75,101.86,89.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,32768,1000,79.23,98.53,87.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,65536,640,95.44,116.24,103.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,131072,320,154.91,192.16,168.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,262144,160,289.36,352.32,309.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,524288,80,641.81,780.29,681.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,1048576,40,1891.25,2459.95,2185.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,2097152,20,3184.88,3223.94,3213.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,288,4194304,10,5331.63,5385.72,5361.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,648,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,4,1000,8.81,12.06,10.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,8,1000,10.63,13.86,12.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,16,1000,9.9,12.94,11.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,32,1000,10.4,13.45,11.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,64,1000,11.54,17.38,14.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,128,1000,11.79,19.16,15.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,256,1000,14.39,22.57,17.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,512,1000,18.48,25.4,21.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,1024,1000,18.32,30.01,21.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,2048,1000,22.56,30.88,26.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,4096,1000,24.15,29.97,27.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,8192,1000,43.74,54.58,50.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,16384,1000,82.69,112.62,99.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,32768,1000,283.2,323.23,302.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,65536,640,145.14,182.17,157.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,131072,320,177.51,223.4,194.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,262144,160,315.31,392.09,341.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,524288,80,771.68,926.29,815.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,1048576,40,1717.9,2050.61,1849.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,2097152,20,3501.26,3707.06,3577.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,648,4194304,10,6252.05,6617.17,6344.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Alltoall,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,1,1000,46.28,49.82,47.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,2,1000,45.95,49.53,47.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,4,1000,49.47,54.82,52.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,8,1000,54.32,60.62,57.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,16,1000,63.91,74.75,68.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,32,1000,66.32,82.65,74.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,64,1000,99.74,136.21,123.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,128,1000,182.0,240.98,217.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,256,1000,1014.92,1103.26,1068.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,512,1000,857.55,964.79,927.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,1024,1000,1152.09,1251.28,1217.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,2048,1000,2192.19,2292.74,2253.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,4096,1000,4357.87,4378.37,4366.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,8192,1000,8761.55,8855.2,8804.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,16384,1000,15425.41,15478.71,15448.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,32768,1000,33021.81,33151.1,33072.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,65536,640,73162.0,74273.74,73819.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,131072,320,118665.8,118867.04,118730.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,262144,160,245975.29,246860.87,246231.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,524288,72,486244.88,487056.55,486695.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,1048576,40,952787.42,954559.15,953678.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,2097152,20,1907175.4,1910557.91,1908730.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Alltoall,216,4194304,10,3821424.85,3839239.76,3828109.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,144,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,1,1000,2.88,5.83,4.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,2,1000,1.13,4.93,3.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,4,1000,3.14,15.21,5.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,8,1000,3.37,7.02,5.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,16,1000,1.58,6.84,4.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,32,1000,2.64,7.61,4.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,64,1000,5.43,10.99,8.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,128,1000,7.61,15.24,11.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,256,1000,9.63,21.89,16.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,512,1000,10.16,36.32,25.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,1024,1000,14.79,54.63,43.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,2048,1000,24.41,103.56,88.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,4096,1000,30.97,176.77,156.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,8192,1000,52.47,340.56,293.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,16384,1000,92.55,563.36,463.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,32768,1000,42.56,557.57,261.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,65536,640,29.57,418.32,243.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,131072,320,72.71,817.96,436.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,262144,160,234.95,1584.06,1266.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,524288,80,237.25,3150.54,2801.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,1048576,40,330.36,6271.05,5786.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,2097152,20,3445.47,12573.4,11717.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatter,144,4194304,10,23662.43,76260.74,48127.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,360,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,1,1000,1.44,6.39,4.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,2,1000,1.52,6.49,5.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,4,1000,1.5,9.86,4.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,8,1000,1.5,10.34,5.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,16,1000,1.39,6.41,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,32,1000,1.41,6.36,4.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,64,1000,1.41,6.41,4.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,128,1000,1.45,6.48,5.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,256,1000,1.54,6.99,5.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,512,1000,1.33,7.17,4.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,1024,1000,0.97,9.13,6.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,2048,1000,1.58,11.32,8.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,4096,1000,2.96,16.54,11.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,8192,1000,5.73,23.67,18.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,16384,1000,8.98,33.17,27.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,32768,1000,19.03,72.23,58.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,65536,640,37.51,86.37,75.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,131072,320,69.69,126.58,110.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,262144,160,149.08,214.18,190.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,524288,80,260.9,386.97,356.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,1048576,40,528.54,742.57,692.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,2097152,20,1051.7,1557.03,1390.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,360,4194304,10,2283.73,25172.82,7282.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,216,0,1000,2.24,7.93,5.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,1,1000,26.28,146.19,81.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,2,1000,26.44,135.73,80.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,4,1000,25.91,136.13,80.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,8,1000,25.86,140.36,80.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,16,1000,25.95,138.77,80.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,32,1000,26.82,137.02,81.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,64,1000,26.35,143.94,84.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,128,1000,26.14,144.69,84.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,256,1000,27.07,152.21,87.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,512,1000,33.8,164.6,96.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,1024,1000,45.3,207.28,119.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,2048,1000,51.86,243.02,143.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,4096,1000,53.83,261.07,151.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,8192,1000,95.57,791.16,272.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,16384,1000,144.94,723.95,368.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,32768,1000,211.91,1277.23,556.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,65536,640,367.84,1628.9,1101.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,131072,320,641.26,2948.95,2007.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,262144,160,2141.33,5817.97,4388.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,524288,80,4482.7,12248.81,9527.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,1048576,40,11931.04,28682.25,20010.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,2097152,20,24962.25,49299.01,40815.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,216,4194304,10,34590.93,83225.08,66616.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,144,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,4,1000,7.26,10.99,9.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,8,1000,4.89,8.31,6.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,16,1000,7.89,18.62,16.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,32,1000,6.68,16.51,14.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,64,1000,6.83,13.44,10.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,128,1000,7.87,14.78,10.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,256,1000,8.25,16.44,11.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,512,1000,12.67,27.05,22.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,1024,1000,11.06,19.31,14.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,2048,1000,10.81,17.66,13.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,4096,1000,14.36,27.39,16.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,8192,1000,28.05,41.29,37.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,16384,1000,61.24,69.26,63.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,32768,1000,82.86,92.17,86.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,65536,640,78.35,93.76,83.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,131072,320,143.38,166.92,151.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,262144,160,241.63,286.35,256.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,524288,80,521.96,607.72,541.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,1048576,40,1460.21,1543.94,1495.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,2097152,20,2623.76,2809.21,2707.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,144,4194304,10,5225.64,5254.8,5242.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,504,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,1,1000,40.43,345.93,202.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,2,1000,60.73,75.59,68.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,4,1000,19.44,27.39,23.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,8,1000,28.1,41.68,34.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,16,1000,33.14,54.5,45.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,32,1000,57.2,95.2,79.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,64,1000,51.42,106.42,91.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,128,1000,81.19,167.08,148.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,256,1000,175.21,274.39,252.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,512,1000,357.52,464.95,440.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,1024,1000,518.73,585.85,566.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,2048,1000,855.19,976.31,950.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,4096,1000,1667.12,1917.21,1833.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,8192,1000,2313.53,2544.83,2431.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,16384,1000,4344.6,4745.15,4554.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,32768,1000,8703.84,9581.65,9147.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,65536,640,17687.96,20644.84,19335.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,131072,320,34558.5,41097.37,37306.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,262144,160,58548.87,76869.9,66244.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,524288,80,106229.91,111913.67,108443.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,1048576,40,260364.06,302483.07,279046.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,2097152,20,626595.11,659371.91,647009.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgather,504,4194304,10,1098895.59,1123676.74,1109578.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,360,0,1000,3.02,11.46,6.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,1,1000,40.66,261.59,180.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,2,1000,40.91,262.73,181.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,4,1000,41.11,262.14,180.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,8,1000,41.51,263.11,181.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,16,1000,40.53,263.86,182.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,32,1000,41.01,268.24,185.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,64,1000,41.64,289.82,202.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,128,1000,41.53,281.14,196.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,256,1000,42.76,292.65,205.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,512,1000,53.55,344.08,248.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,1024,1000,68.48,417.91,312.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,2048,1000,74.38,508.64,387.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,4096,1000,74.48,548.42,421.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,8192,1000,92.65,735.25,580.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,16384,1000,135.5,1276.79,1020.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,32768,1000,208.7,2393.46,1893.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,65536,640,258.65,2484.2,1453.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,131072,320,419.61,4638.64,2650.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,262144,160,1248.11,9099.4,5230.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,524288,80,3186.77,18566.9,10930.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,1048576,40,12029.4,36582.34,22153.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,2097152,20,25013.48,74011.34,45227.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,360,4194304,10,34535.19,132474.23,74935.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gather,504,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,1,1000,0.5,59.92,2.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,2,1000,0.55,188.92,4.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,4,1000,0.57,90.56,3.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,8,1000,0.56,685.19,13.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,16,1000,0.56,36.62,1.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,32,1000,0.48,48.49,1.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,64,1000,0.52,30.31,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,128,1000,0.51,33.75,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,256,1000,0.59,58.0,2.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,512,1000,0.85,79.7,3.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,1024,1000,1.04,233.95,6.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,2048,1000,1.3,261.29,8.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,4096,1000,2.33,486.47,14.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,8192,1000,3.84,1543.85,33.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,16384,1000,8.3,3237.59,77.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,32768,1000,14.84,6247.13,130.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,65536,640,32.48,3367.46,1889.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,131072,320,85.4,7273.93,3435.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,262144,160,158.63,12199.19,6608.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,524288,80,317.33,24834.13,13621.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,1048576,40,229.7,48937.39,26558.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,2097152,20,2000.91,98280.56,54402.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gather,504,4194304,10,12132.75,180122.6,94806.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,288,0,1000,1.25,1.65,1.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,4,1000,1.74,12.71,2.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,8,1000,1.78,14.29,2.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,16,1000,1.81,21.72,3.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,32,1000,1.58,20.04,5.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,64,1000,1.58,21.19,6.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,128,1000,1.62,22.78,6.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,256,1000,2.78,24.25,9.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,512,1000,2.75,26.92,12.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,1024,1000,8.5,26.08,20.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,2048,1000,21.84,34.88,27.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,4096,1000,31.18,43.51,37.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,8192,1000,51.23,65.96,57.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,16384,1000,90.01,107.86,99.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,32768,1000,175.81,200.12,189.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,65536,640,254.87,333.19,288.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,131072,320,306.82,473.13,396.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,262144,160,677.05,774.76,716.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,524288,80,1050.46,1155.45,1094.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,1048576,40,1459.89,1565.02,1505.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,2097152,20,2435.51,2597.73,2489.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,288,4194304,10,3648.14,4141.8,3885.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,1,1000,0.96,4.7,3.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,2,1000,1.14,5.78,4.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,4,1000,1.11,5.76,4.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,8,1000,1.11,5.8,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,16,1000,1.11,5.76,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,32,1000,1.15,5.79,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,64,1000,1.15,5.83,4.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,128,1000,1.17,5.96,4.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,256,1000,1.24,6.4,5.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,512,1000,1.07,6.3,4.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,1024,1000,1.19,5.4,4.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,2048,1000,2.04,6.47,4.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,4096,1000,4.25,9.88,7.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,8192,1000,7.16,15.97,11.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,16384,1000,12.53,25.76,22.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,32768,1000,19.43,49.03,40.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,65536,640,36.76,63.79,54.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,131072,320,69.73,111.17,96.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,262144,160,148.03,193.67,177.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,524288,80,306.14,334.89,324.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,1048576,40,607.55,644.5,632.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,2097152,20,1150.09,1188.98,1179.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Bcast,288,4194304,10,2359.34,2819.06,2473.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,1,1000,59.95,65.97,62.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,2,1000,60.95,68.71,63.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,4,1000,68.25,76.79,71.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,8,1000,73.65,87.73,80.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,16,1000,109.37,141.37,125.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,32,1000,102.33,117.28,112.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,64,1000,171.13,196.77,186.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,128,1000,306.56,354.23,335.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,256,1000,811.74,828.83,819.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,512,1000,1131.19,1148.5,1138.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,1024,1000,1889.87,1909.49,1897.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,2048,1000,3389.65,3436.4,3414.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,4096,1000,5713.06,5725.38,5717.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,8192,1000,12950.4,12983.32,12961.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,16384,1000,24303.11,24373.71,24332.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,32768,1000,48353.38,48461.28,48397.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,65536,622,97180.54,98355.14,97829.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,131072,320,185305.27,185611.12,185430.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,262144,75,377637.06,378741.17,378341.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,524288,48,699616.61,700096.99,699843.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,1048576,29,1419967.16,1424322.42,1421619.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Alltoall,288,2097152,15,2770833.95,2773515.91,2772027.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,4,1000,0.35,6.65,0.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,8,1000,0.33,7.44,0.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,16,1000,0.35,8.59,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,32,1000,0.36,9.51,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,64,1000,0.35,9.85,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,128,1000,0.34,10.06,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,256,1000,0.34,11.1,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,512,1000,0.32,12.07,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,1024,1000,0.34,10.63,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,2048,1000,0.42,12.74,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,4096,1000,0.7,15.01,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,8192,1000,2.63,25.16,4.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,16384,1000,7.07,37.09,11.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,32768,1000,38.09,160.12,109.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,65536,640,81.12,186.01,145.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,131072,320,168.39,353.86,274.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,262144,160,87.43,826.76,400.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,524288,80,160.1,1061.79,558.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,1048576,40,227.52,1301.55,731.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,2097152,20,488.01,1896.06,1563.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce,288,4194304,10,695.04,3928.09,2137.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allreduce,576,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,4,1000,6.89,9.45,8.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,8,1000,8.8,12.22,10.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,16,1000,9.57,12.73,11.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,32,1000,8.85,15.63,10.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,64,1000,10.53,15.9,12.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,128,1000,10.78,17.92,13.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,256,1000,13.43,24.83,20.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,512,1000,14.2,20.22,16.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,1024,1000,16.97,23.19,19.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,2048,1000,42.21,55.85,49.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,4096,1000,33.21,42.91,39.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,8192,1000,49.09,59.29,54.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,16384,1000,100.48,112.58,105.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,32768,1000,333.73,366.57,350.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,65536,640,100.03,132.69,110.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,131072,320,677.4,969.49,701.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,262144,160,1148.19,1258.17,1206.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,524288,80,817.02,1040.95,945.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,1048576,40,1579.04,1899.15,1679.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,2097152,20,3290.03,3358.06,3328.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Allreduce,576,4194304,10,5445.84,5526.18,5489.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Gather,144,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,1,1000,0.57,25.77,2.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,2,1000,0.57,26.06,2.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,4,1000,0.57,25.14,3.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,8,1000,0.57,19.79,2.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,16,1000,0.5,13.99,1.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,32,1000,0.47,13.54,1.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,64,1000,0.48,15.79,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,128,1000,0.5,19.96,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,256,1000,0.52,27.54,1.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,512,1000,0.71,41.64,2.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,1024,1000,0.89,76.54,4.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,2048,1000,1.32,139.85,7.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,4096,1000,2.19,255.46,12.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,8192,1000,3.44,300.88,8.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,16384,1000,7.1,467.94,12.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,32768,1000,12.33,807.73,23.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,65536,640,39.69,1062.05,495.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,131072,320,90.75,1575.64,849.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,262144,160,175.48,3087.64,1658.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,524288,80,337.54,6346.09,3396.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,1048576,40,235.39,17983.16,9125.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,2097152,20,1800.52,27087.65,16648.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,144,4194304,10,12587.87,52521.03,32180.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgather,288,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,1,1000,12.27,19.06,14.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,2,1000,15.38,22.59,18.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,4,1000,15.98,27.41,20.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,8,1000,19.12,32.85,24.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,16,1000,20.02,36.3,27.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,32,1000,39.93,53.64,49.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,64,1000,232.01,577.04,403.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,128,1000,59.53,99.47,90.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,256,1000,98.06,164.13,152.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,512,1000,195.43,274.63,251.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,1024,1000,277.19,308.67,298.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,2048,1000,507.52,533.0,525.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,4096,1000,976.26,999.05,993.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,8192,1000,1267.66,1401.07,1327.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,16384,1000,2961.61,3398.55,3199.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,32768,1000,4790.39,5604.03,5182.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,65536,640,8816.66,10461.73,9638.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,131072,320,16793.08,20840.23,18627.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,262144,160,30929.02,43326.36,35727.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,524288,80,60512.99,61928.31,61048.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,1048576,40,131124.67,136742.23,133299.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,2097152,20,304105.4,313112.47,308923.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgather,288,4194304,10,678864.61,733231.98,701777.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,360,0,1000,1.5,1.67,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,4,1000,2.06,43.56,3.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,8,1000,2.04,14.33,3.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,16,1000,2.07,15.87,3.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,32,1000,2.07,31.64,3.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,64,1000,1.81,25.2,5.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,128,1000,1.84,26.94,6.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,256,1000,1.86,26.86,8.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,512,1000,2.1,29.37,11.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,1024,1000,5.71,32.11,20.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,2048,1000,24.3,37.67,29.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,4096,1000,34.26,45.89,40.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,8192,1000,58.35,78.63,69.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,16384,1000,408.51,699.44,469.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,32768,1000,204.49,258.51,240.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,65536,640,350.19,390.49,373.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,131072,320,1486.54,2288.75,1995.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,262144,160,858.42,971.91,905.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,524288,80,1155.73,1295.9,1221.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,1048576,40,1547.98,1670.58,1605.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,2097152,20,2921.15,3059.96,2986.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce_scatter,360,4194304,10,4565.63,4705.64,4646.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Gatherv,288,0,1000,2.71,11.86,6.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,1,1000,32.09,210.9,141.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,2,1000,32.65,210.54,141.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,4,1000,32.46,210.48,140.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,8,1000,32.7,211.45,141.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,16,1000,32.54,211.81,141.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,32,1000,32.67,214.59,144.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,64,1000,33.34,231.76,156.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,128,1000,33.35,223.79,150.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,256,1000,33.73,229.8,155.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,512,1000,42.18,265.42,184.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,1024,1000,52.79,326.08,234.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,2048,1000,63.04,402.78,293.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,4096,1000,62.01,425.37,311.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,8192,1000,82.32,593.68,448.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,16384,1000,141.31,1837.32,888.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,32768,1000,185.89,1780.24,1356.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,65536,640,252.73,2077.74,1229.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,131072,320,477.82,3878.55,2220.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,262144,160,1899.42,7530.44,4532.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,524288,80,4416.06,15391.74,9491.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,1048576,40,12017.5,30412.41,19208.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,2097152,20,25014.99,61754.81,39377.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gatherv,288,4194304,10,34552.59,107926.24,63185.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Allgatherv,360,0,1000,4.24,12.1,4.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,1,1000,29.72,43.09,33.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,2,1000,25.97,33.92,30.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,4,1000,33.75,42.98,39.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,8,1000,37.79,54.46,45.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,16,1000,37.45,52.81,45.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,32,1000,55.7,76.24,67.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,64,1000,87.45,135.32,121.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,128,1000,196.62,264.5,234.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,256,1000,159.81,259.86,236.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,512,1000,302.92,393.68,367.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,1024,1000,494.97,1039.12,587.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,2048,1000,526.47,695.53,660.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,4096,1000,963.5,1085.71,1020.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,8192,1000,1689.06,1829.05,1763.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,16384,1000,3041.81,3342.06,3196.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,32768,1000,6060.11,6782.2,6421.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,65536,640,10778.92,11942.3,11384.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,131072,320,20964.49,25451.47,23371.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,262144,160,43164.29,50004.54,46362.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,524288,80,87706.95,95073.16,90812.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,1048576,40,176105.16,185447.0,179720.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,2097152,20,384906.15,397590.34,390271.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,360,4194304,10,778373.89,803085.86,789717.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,720,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,4,1000,10.08,13.97,11.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,8,1000,11.69,15.97,13.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,16,1000,10.3,14.85,12.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,32,1000,17.68,27.95,25.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,64,1000,12.11,17.93,14.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,128,1000,12.98,22.38,16.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,256,1000,20.97,32.25,27.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,512,1000,17.13,27.9,22.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,1024,1000,19.21,29.34,22.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,2048,1000,20.58,27.45,23.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,4096,1000,25.79,31.66,28.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,8192,1000,64.63,76.28,72.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,16384,1000,87.47,115.96,105.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,32768,1000,240.18,306.88,268.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,65536,640,153.51,187.56,166.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,131072,320,174.26,215.45,190.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,262144,160,322.07,388.13,345.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,524288,80,668.73,803.27,714.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,1048576,40,1710.65,2012.6,1862.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,2097152,20,3640.23,3854.13,3740.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,720,4194304,10,6318.3,6714.78,6474.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Gatherv,432,0,1000,3.38,11.58,7.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,1,1000,52.57,311.11,222.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,2,1000,51.83,314.22,222.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,4,1000,53.52,314.56,222.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,8,1000,52.82,316.07,223.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,16,1000,52.96,317.74,225.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,32,1000,53.11,325.35,231.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,64,1000,55.06,345.34,248.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,128,1000,55.33,337.29,242.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,256,1000,57.39,347.28,252.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,512,1000,74.43,409.14,304.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,1024,1000,92.4,508.05,389.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,2048,1000,102.13,616.66,480.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,4096,1000,92.37,658.27,520.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,8192,1000,116.48,887.57,722.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,16384,1000,155.52,1522.68,1257.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,32768,1000,244.59,2858.54,2372.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,65536,640,363.65,2962.73,1743.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,131072,320,628.36,5474.22,3115.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,262144,160,1307.9,10789.45,6133.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,524288,80,3114.76,21738.29,12519.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,1048576,40,12271.78,43298.13,25332.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,2097152,20,24951.14,86220.71,51114.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,432,4194304,10,34589.07,157061.59,86886.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Gatherv,144,0,1000,1.86,5.56,3.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,1,1000,17.79,111.58,57.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,2,1000,16.69,96.35,57.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,4,1000,16.65,99.47,57.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,8,1000,16.47,97.18,57.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,16,1000,16.7,96.95,57.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,32,1000,17.37,97.46,58.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,64,1000,20.1,101.64,59.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,128,1000,20.44,99.13,58.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,256,1000,19.94,99.22,58.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,512,1000,27.3,112.71,67.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,1024,1000,34.37,136.53,80.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,2048,1000,52.15,184.22,107.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,4096,1000,73.72,233.97,136.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,8192,1000,95.78,312.26,184.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,16384,1000,140.46,505.66,273.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,32768,1000,207.38,837.58,410.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,65536,640,399.43,1376.22,892.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,131072,320,966.5,2221.09,1555.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,262144,160,2337.95,4314.34,3279.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,524288,80,5097.94,9156.65,7191.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,1048576,40,11905.28,17967.31,14815.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,2097152,20,24915.68,37014.1,30863.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gatherv,144,4194304,10,34351.3,58507.26,46302.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,432,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,4,1000,5.37,9.5,7.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,8,1000,6.49,11.4,9.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,16,1000,9.67,13.67,11.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,32,1000,8.82,13.19,10.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,64,1000,11.21,17.52,13.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,128,1000,11.18,18.43,14.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,256,1000,13.5,21.81,17.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,512,1000,13.19,18.89,15.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,1024,1000,17.34,24.13,19.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,2048,1000,18.6,24.94,21.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,4096,1000,26.03,34.19,29.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,8192,1000,46.16,56.92,50.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,16384,1000,97.08,117.27,106.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,32768,1000,84.81,111.19,96.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,65536,640,107.82,135.52,118.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,131072,320,169.74,207.53,184.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,262144,160,299.32,371.25,326.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,524288,80,662.6,799.61,711.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,1048576,40,1691.66,2008.37,1884.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,2097152,20,3501.02,3709.69,3640.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allreduce,432,4194304,10,6073.47,6479.13,6333.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce_scatter,216,0,1000,1.04,1.12,1.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,4,1000,1.58,14.38,2.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,8,1000,1.57,12.82,2.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,16,1000,1.61,14.82,2.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,32,1000,1.35,15.4,3.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,64,1000,1.36,16.3,3.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,128,1000,1.39,18.35,4.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,256,1000,1.4,18.48,7.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,512,1000,1.49,22.62,12.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,1024,1000,14.21,22.63,17.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,2048,1000,16.4,27.32,21.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,4096,1000,25.02,40.02,32.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,8192,1000,39.46,57.52,49.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,16384,1000,78.31,105.65,91.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,32768,1000,121.59,150.85,139.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,65536,640,239.97,321.9,274.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,131072,320,335.97,508.6,427.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,262144,160,641.28,728.92,675.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,524288,80,2111.5,2919.89,2186.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,1048576,40,3643.75,4149.86,3752.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,2097152,20,2839.6,2948.72,2894.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce_scatter,216,4194304,10,5248.6,5906.54,5511.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,720,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,1,1000,2.36,7.1,5.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,2,1000,2.53,6.84,5.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,4,1000,2.72,6.99,5.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,8,1000,2.56,6.84,5.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,16,1000,2.54,6.86,5.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,32,1000,2.61,10.72,5.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,64,1000,2.7,6.92,5.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,128,1000,2.69,7.11,5.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,256,1000,3.45,8.3,6.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,512,1000,3.05,9.17,5.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,1024,1000,3.56,8.7,5.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,2048,1000,4.46,11.87,8.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,4096,1000,7.64,17.34,12.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,8192,1000,10.23,25.55,19.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,16384,1000,17.15,38.55,31.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,32768,1000,35.96,70.8,63.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,65536,640,49.48,109.48,94.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,131072,320,127.49,214.62,190.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,262144,160,191.66,286.56,260.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,524288,80,313.6,423.6,397.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,1048576,40,694.02,733.65,714.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,2097152,20,1293.71,1369.77,1323.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Bcast,720,4194304,10,3907.9,4194.12,4033.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Allreduce,216,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,4,1000,24.21,42.14,34.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,8,1000,10.1,15.06,13.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,16,1000,6.47,9.5,7.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,32,1000,6.33,9.41,7.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,64,1000,9.59,14.45,12.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,128,1000,8.09,15.31,11.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,256,1000,9.4,16.23,12.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,512,1000,11.29,16.89,13.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,1024,1000,11.23,17.44,13.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,2048,1000,11.17,16.64,13.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,4096,1000,15.76,21.48,17.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,8192,1000,54.67,77.71,63.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,16384,1000,96.02,117.88,103.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,32768,1000,99.49,122.22,107.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,65536,640,96.07,149.7,130.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,131072,320,156.6,219.06,192.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,262144,160,279.14,352.4,307.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,524288,80,598.56,741.27,657.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,1048576,40,1658.22,1715.84,1679.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,2097152,20,3028.76,3074.58,3059.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allreduce,216,4194304,10,5253.38,5311.45,5279.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gatherv,504,0,1000,3.77,11.8,8.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,1,1000,56.46,358.29,257.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,2,1000,56.92,358.6,257.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,4,1000,57.63,365.4,263.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,8,1000,56.86,696.48,260.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,16,1000,56.92,364.4,261.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,32,1000,57.67,372.42,269.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,64,1000,59.2,403.11,295.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,128,1000,60.93,400.2,293.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,256,1000,63.97,428.4,318.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,512,1000,79.7,496.48,376.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,1024,1000,92.54,916.34,476.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,2048,1000,93.85,688.44,542.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,4096,1000,96.83,1094.55,646.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,8192,1000,113.75,1049.96,872.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,16384,1000,160.93,2265.03,1631.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,32768,1000,236.72,3894.34,2990.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,65536,640,272.53,3383.38,1965.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,131072,320,481.78,6301.42,3554.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,262144,160,863.36,12418.93,6967.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,524288,80,2049.43,24920.3,14120.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,1048576,40,12160.54,49038.38,28323.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,2097152,20,24885.92,98542.02,57112.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Gatherv,504,4194304,10,34630.22,181679.46,98965.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,4,1000,0.32,9.11,0.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,8,1000,0.35,11.23,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,16,1000,0.4,9.36,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,32,1000,0.53,14.52,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,64,1000,0.36,11.01,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,128,1000,0.34,10.97,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,256,1000,0.56,16.02,1.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,512,1000,0.33,12.33,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,1024,1000,0.35,11.96,0.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,2048,1000,0.42,15.27,1.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,4096,1000,0.73,18.63,1.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,8192,1000,2.75,29.43,4.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,16384,1000,8.85,57.88,14.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,32768,1000,34.98,126.18,71.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,65536,640,77.03,219.99,138.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,131072,320,140.42,422.41,264.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,262144,160,87.5,833.42,393.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,524288,80,159.31,1170.07,563.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,1048576,40,228.59,1820.1,800.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,2097152,20,382.36,2159.64,1111.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce,504,4194304,10,1166.52,3581.59,3002.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatter,432,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,1,1000,1.17,10.66,5.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,2,1000,1.33,12.97,7.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,4,1000,1.64,13.78,8.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,8,1000,2.27,12.68,7.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,16,1000,3.1,12.55,7.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,32,1000,4.95,16.32,10.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,64,1000,7.28,20.63,14.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,128,1000,11.97,28.13,20.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,256,1000,21.55,47.29,33.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,512,1000,33.94,79.33,55.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,1024,1000,51.08,103.87,79.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,2048,1000,76.31,174.7,131.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,4096,1000,129.03,309.3,228.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,8192,1000,233.57,563.91,408.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,16384,1000,451.13,974.07,747.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,32768,1000,28.8,1505.91,711.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,65536,640,26.8,2080.73,1065.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,131072,320,114.84,4041.83,2193.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,262144,160,184.32,7747.73,4326.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,524288,80,827.31,15457.03,10308.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,1048576,40,348.51,30875.3,23317.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,2097152,20,1056.05,61743.45,49866.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatter,432,4194304,10,34481.57,123449.13,105383.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,144,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,4,1000,0.36,7.85,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,8,1000,0.35,8.38,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,16,1000,0.36,7.87,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,32,1000,0.36,8.19,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,64,1000,0.36,9.28,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,128,1000,0.34,10.29,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,256,1000,0.35,11.74,0.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,512,1000,0.35,11.45,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,1024,1000,0.39,10.26,1.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,2048,1000,0.42,15.29,1.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,4096,1000,0.78,24.12,2.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,8192,1000,2.71,22.4,4.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,16384,1000,7.0,32.22,11.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,32768,1000,16.01,59.11,23.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,65536,640,79.89,182.19,146.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,131072,320,143.5,283.33,236.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,262144,160,84.33,462.57,284.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,524288,80,144.3,692.3,434.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,1048576,40,252.59,1105.73,692.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,2097152,20,330.46,2008.7,1174.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce,144,4194304,10,683.7,3333.41,2011.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,504,0,1000,1.95,2.08,2.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,4,1000,2.49,15.76,3.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,8,1000,2.55,18.52,3.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,16,1000,2.55,18.8,3.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,32,1000,2.53,20.01,3.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,64,1000,2.28,20.2,4.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,128,1000,2.3,20.81,5.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,256,1000,2.31,22.08,6.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,512,1000,2.57,29.67,9.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,1024,1000,3.01,35.67,18.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,2048,1000,25.19,35.5,30.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,4096,1000,28.48,37.28,32.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,8192,1000,50.61,59.79,54.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,16384,1000,72.82,83.57,77.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,32768,1000,134.17,153.05,141.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,65536,640,253.01,273.71,261.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,131072,320,527.5,551.03,538.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,262144,160,793.12,926.79,850.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,524288,80,1170.2,1318.09,1240.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,1048576,40,1633.67,1784.8,1713.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,2097152,20,2697.36,2849.6,2780.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,504,4194304,10,4589.17,4752.09,4685.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,144,0,1000,2.21,5.74,2.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,1,1000,13.47,18.92,15.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,2,1000,13.78,24.5,16.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,4,1000,15.02,23.44,18.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,8,1000,19.53,26.71,22.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,16,1000,19.68,27.89,23.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,32,1000,19.73,29.78,24.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,64,1000,23.86,43.51,35.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,128,1000,74.93,95.74,90.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,256,1000,89.14,123.1,116.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,512,1000,126.27,181.33,173.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,1024,1000,213.85,268.95,258.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,2048,1000,248.06,271.05,266.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,4096,1000,357.25,417.25,386.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,8192,1000,580.02,657.5,618.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,16384,1000,1084.99,1373.28,1232.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,32768,1000,2036.89,2667.66,2368.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,65536,640,3699.51,4756.58,4261.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,131072,320,8996.7,11531.09,10065.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,262144,160,13412.34,16544.94,15082.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,524288,80,29393.91,30467.29,29889.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,1048576,40,65714.98,68176.78,66874.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,2097152,20,149995.86,156201.68,153349.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,144,4194304,10,307024.64,323525.11,313518.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allgatherv,432,0,1000,4.93,13.73,5.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,1,1000,25.63,36.04,29.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,2,1000,26.93,35.4,31.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,4,1000,32.56,42.19,37.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,8,1000,42.24,58.38,50.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,16,1000,41.59,56.55,50.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,32,1000,62.06,90.29,78.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,64,1000,97.52,147.33,132.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,128,1000,218.09,303.24,271.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,256,1000,197.49,285.45,260.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,512,1000,358.41,495.61,442.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,1024,1000,546.13,651.32,603.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,2048,1000,709.44,824.9,785.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,4096,1000,1187.19,1291.75,1242.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,8192,1000,2000.88,2144.11,2078.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,16384,1000,3879.71,4285.02,4073.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,32768,1000,7436.75,8318.68,7843.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,65536,640,13150.34,14416.36,13805.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,131072,320,25969.14,29469.22,28020.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,262144,160,50168.79,59780.3,54593.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,524288,80,99313.06,102761.68,101117.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,1048576,40,197771.97,206187.39,200404.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,2097152,20,459155.65,469837.3,464621.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,432,4194304,10,1047872.14,1092241.57,1065934.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgatherv,504,0,1000,5.6,15.98,5.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,1,1000,29.85,35.4,32.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,2,1000,29.7,36.48,33.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,4,1000,39.42,48.55,44.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,8,1000,46.34,62.19,54.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,16,1000,54.03,73.3,65.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,32,1000,65.09,106.23,88.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,64,1000,106.11,161.07,145.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,128,1000,243.31,358.49,314.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,256,1000,223.39,324.91,302.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,512,1000,415.64,527.85,506.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,1024,1000,553.58,620.28,605.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,2048,1000,924.12,1505.27,1017.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,4096,1000,1414.07,1525.74,1465.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,8192,1000,2448.7,3094.23,2751.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,16384,1000,6052.5,6914.98,6487.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,32768,1000,9336.16,10465.08,9904.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,65536,640,15613.29,17074.13,16354.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,131072,320,28905.23,31083.2,30021.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,262144,160,60154.31,70789.56,66216.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,524288,80,131190.63,139647.46,135808.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,1048576,40,234886.88,257784.43,245225.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,2097152,20,536198.9,547496.78,541685.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allgatherv,504,4194304,10,1223155.44,1260179.57,1241864.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,144,0,1000,0.79,0.89,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,4,1000,1.09,16.37,3.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,8,1000,1.09,16.95,3.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,16,1000,1.09,14.0,3.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,32,1000,1.11,17.55,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,64,1000,1.15,16.03,5.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,128,1000,1.71,18.36,6.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,256,1000,1.82,48.03,20.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,512,1000,6.58,36.82,29.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,1024,1000,10.78,20.48,15.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,2048,1000,14.53,24.51,19.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,4096,1000,18.35,29.8,23.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,8192,1000,27.81,42.73,34.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,16384,1000,171.15,500.51,248.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,32768,1000,139.58,208.2,167.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,65536,640,213.93,290.98,245.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,131072,320,324.64,455.43,390.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,262144,160,534.2,617.93,568.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,524288,80,829.32,928.12,869.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,1048576,40,1401.4,1541.88,1466.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,2097152,20,1807.99,2039.02,1909.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Reduce_scatter,144,4194304,10,33741.34,43299.39,40609.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Gather,288,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,1,1000,0.48,11.97,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,2,1000,0.54,15.2,1.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,4,1000,0.56,15.95,1.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,8,1000,0.5,16.6,1.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,16,1000,0.46,14.82,1.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,32,1000,0.46,17.63,1.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,64,1000,0.47,20.92,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,128,1000,0.5,28.58,1.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,256,1000,0.53,38.1,2.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,512,1000,0.81,59.04,3.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,1024,1000,1.0,106.48,5.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,2048,1000,1.34,251.27,8.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,4096,1000,2.32,311.23,13.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,8192,1000,3.98,552.67,23.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,16384,1000,8.11,1097.98,47.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,32768,1000,18.39,3713.47,109.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,65536,640,38.41,2015.99,1095.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,131072,320,80.26,3760.62,2003.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,262144,160,157.0,7388.39,3935.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,524288,80,332.21,17467.11,8332.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,1048576,40,237.25,31719.94,16419.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,2097152,20,2068.51,60926.83,34294.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Gather,288,4194304,10,12500.79,105931.12,56762.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,4, -1
+Reduce_scatter,576,0,1000,2.17,2.48,2.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,4,1000,2.7,16.56,3.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,8,1000,2.74,19.18,3.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,16,1000,2.78,20.52,3.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,32,1000,2.75,21.55,3.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,64,1000,2.5,34.17,8.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,128,1000,2.51,34.89,9.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,256,1000,2.55,31.56,10.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,512,1000,4.56,39.82,14.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,1024,1000,4.75,71.07,34.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,2048,1000,21.75,66.86,48.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,4096,1000,56.12,79.12,65.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,8192,1000,101.22,133.64,114.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,16384,1000,129.69,145.21,136.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,32768,1000,229.48,250.96,239.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,65536,640,435.95,475.76,460.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,131072,320,917.69,968.32,950.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,262144,160,826.02,957.49,883.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,524288,80,1279.65,1440.03,1358.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,1048576,40,1811.39,1965.63,1890.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,2097152,20,3021.61,3171.38,3102.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce_scatter,576,4194304,10,4677.9,4864.73,4776.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Scatter,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,1,1000,1.22,6.96,4.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,2,1000,1.21,7.24,4.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,4,1000,1.26,7.77,4.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,8,1000,1.34,6.66,4.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,16,1000,2.3,8.11,5.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,32,1000,3.19,8.89,6.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,64,1000,4.78,11.9,8.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,128,1000,7.78,15.18,12.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,256,1000,12.51,23.45,18.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,512,1000,24.98,42.76,32.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,1024,1000,34.05,73.1,55.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,2048,1000,50.45,122.1,93.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,4096,1000,71.63,203.71,159.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,8192,1000,121.09,392.46,291.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,16384,1000,223.32,652.34,484.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,32768,1000,56.28,1209.36,759.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,65536,640,41.88,1135.53,598.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,131072,320,103.94,1681.86,979.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,262144,160,117.52,3116.44,2268.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,524288,80,183.52,6213.19,4771.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,1048576,40,4521.16,12403.88,9908.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,2097152,20,5727.72,24812.94,20148.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Scatter,216,4194304,10,5258.96,49559.26,37167.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,1,1000,0.8,5.63,4.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,2,1000,0.81,5.71,4.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,4,1000,0.81,5.63,4.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,8,1000,0.8,5.59,4.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,16,1000,0.81,5.63,4.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,32,1000,0.81,5.76,4.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,64,1000,0.84,5.8,4.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,128,1000,0.88,5.75,4.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,256,1000,0.97,6.12,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,512,1000,0.87,4.34,3.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,1024,1000,0.99,5.16,4.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,2048,1000,1.63,6.27,4.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,4096,1000,3.75,9.21,6.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,8192,1000,6.32,13.83,11.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,16384,1000,10.36,22.79,18.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,32768,1000,16.79,40.23,34.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,65536,640,37.21,57.31,52.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,131072,320,62.38,110.69,93.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,262144,160,130.67,200.28,176.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,524288,80,259.49,333.11,309.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,1048576,40,523.88,643.47,604.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,2097152,20,1055.14,1262.68,1198.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,216,4194304,10,2165.54,2561.99,2422.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,360,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,4,1000,0.31,8.35,0.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,8,1000,0.34,8.87,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,16,1000,0.39,8.24,0.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,32,1000,0.53,13.39,1.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,64,1000,0.36,9.94,0.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,128,1000,0.35,10.53,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,256,1000,0.56,14.63,1.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,512,1000,0.33,11.3,0.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,1024,1000,0.34,13.63,0.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,2048,1000,0.4,12.36,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,4096,1000,0.73,18.65,1.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,8192,1000,2.67,27.51,4.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,16384,1000,7.88,64.67,13.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,32768,1000,39.81,142.76,94.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,65536,640,79.06,204.81,149.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,131072,320,155.89,364.56,270.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,262144,160,87.86,782.95,394.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,524288,80,148.26,988.6,531.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,1048576,40,234.33,1325.93,736.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,2097152,20,382.33,2048.88,1110.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,360,4194304,10,1158.42,3272.17,2825.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,0,1000,8.57,15.76,11.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,1,1000,9.49,18.31,13.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,2,1000,10.1,18.35,14.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,4,1000,10.34,19.89,15.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,8,1000,9.37,17.59,13.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,16,1000,9.3,17.23,13.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,32,1000,11.17,19.08,15.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,64,1000,13.17,22.39,17.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,128,1000,14.97,27.64,22.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,256,1000,20.44,36.8,30.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,512,1000,22.95,55.26,42.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,1024,1000,15.84,66.88,48.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,2048,1000,15.19,107.44,81.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,4096,1000,16.31,181.66,123.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,8192,1000,42.14,367.48,230.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,16384,1000,52.27,1221.08,427.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,32768,1000,52.65,1371.83,911.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,65536,640,47.4,2858.91,1543.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,131072,320,237.19,5629.31,3185.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,262144,160,372.56,11488.06,5739.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,524288,80,616.48,26628.68,16242.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,1048576,40,1139.93,60152.38,34756.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,2097152,20,1946.32,126837.82,71473.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Scatterv,360,4194304,10,3262.58,261429.33,147013.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Reduce,576,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,4,1000,0.32,11.21,0.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,8,1000,0.35,13.21,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,16,1000,0.39,12.91,0.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,32,1000,0.54,17.15,1.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,64,1000,0.36,13.36,0.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,128,1000,0.35,13.82,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,256,1000,0.59,24.85,2.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,512,1000,0.33,22.56,0.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,1024,1000,0.35,27.09,1.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,2048,1000,0.41,19.48,1.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,4096,1000,0.73,21.25,1.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,8192,1000,2.81,34.71,5.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,16384,1000,9.01,55.6,14.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,32768,1000,38.81,257.11,151.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,65536,640,78.56,238.69,176.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,131072,320,141.46,385.43,301.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,262144,160,87.19,822.49,397.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,524288,80,157.76,1055.92,547.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,1048576,40,228.78,1424.61,755.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,2097152,20,386.88,2070.87,1124.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,576,4194304,10,1165.61,3761.88,3133.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Scatterv,432,0,1000,10.59,18.28,14.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,1,1000,10.2,20.02,14.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,2,1000,11.29,21.6,16.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,4,1000,11.61,22.44,17.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,8,1000,10.91,21.44,15.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,16,1000,10.69,19.94,15.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,32,1000,12.34,22.74,17.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,64,1000,15.02,27.61,20.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,128,1000,17.23,38.64,26.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,256,1000,18.17,47.9,33.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,512,1000,24.49,65.05,46.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,1024,1000,17.15,88.78,61.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,2048,1000,16.74,151.15,96.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,4096,1000,17.66,258.71,156.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,8192,1000,42.6,502.09,299.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,16384,1000,49.74,988.75,562.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,32768,1000,50.34,1834.57,1033.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,65536,640,58.4,3650.69,1994.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,131072,320,255.8,9227.81,4367.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,262144,160,380.23,21918.42,9748.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,524288,80,569.58,47793.13,23188.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,1048576,40,1196.7,89297.93,45917.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,2097152,20,1994.88,181660.99,99550.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,432,4194304,10,6076.54,374124.33,204799.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,504,0,1000,11.19,19.91,15.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,1,1000,11.08,21.17,15.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,2,1000,11.81,22.46,17.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,4,1000,12.22,23.78,18.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,8,1000,11.15,21.9,16.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,16,1000,11.41,21.75,16.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,32,1000,13.44,25.1,19.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,64,1000,16.32,30.47,23.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,128,1000,19.89,38.55,28.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,256,1000,18.95,54.97,38.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,512,1000,24.16,77.95,55.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,1024,1000,17.75,105.9,69.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,2048,1000,17.17,171.19,115.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,4096,1000,17.54,320.29,195.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,8192,1000,44.59,758.95,369.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,16384,1000,57.24,1186.74,699.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,32768,1000,48.19,2361.09,1330.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,65536,640,60.96,4774.35,2554.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,131072,320,265.47,10452.69,5346.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,262144,160,373.71,27519.19,14212.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,524288,80,654.46,61088.16,31816.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,1048576,40,1224.05,119180.25,66330.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,2097152,20,2243.81,238797.53,136476.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Scatterv,504,4194304,10,6343.15,486620.23,276120.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Reduce_scatter,648,0,1000,2.38,2.53,2.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,4,1000,2.91,17.18,3.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,8,1000,2.96,19.31,3.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,16,1000,2.98,20.08,3.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,32,1000,2.69,26.0,7.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,64,1000,2.71,29.95,7.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,128,1000,2.75,34.79,8.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,256,1000,2.75,28.43,9.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,512,1000,3.0,45.45,14.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,1024,1000,3.58,44.84,21.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,2048,1000,10.13,54.81,40.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,4096,1000,57.42,71.42,63.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,8192,1000,106.22,138.14,119.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,16384,1000,116.98,140.31,128.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,32768,1000,227.58,253.79,241.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,65536,640,436.06,481.46,468.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,131072,320,325.16,639.27,483.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,262144,160,664.93,997.44,836.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,524288,80,1329.45,1495.61,1407.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,1048576,40,1886.12,2090.62,1997.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,2097152,20,3034.19,3199.09,3128.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce_scatter,648,4194304,10,4851.55,5071.95,4979.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Alltoall,360,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,1,1000,69.85,76.9,73.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,2,1000,73.84,81.77,77.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,4,1000,168.83,659.64,220.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,8,1000,103.35,123.06,115.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,16,1000,393.83,610.37,451.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,32,1000,161.83,178.21,170.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,64,1000,224.61,260.25,245.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,128,1000,405.07,481.99,452.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,256,1000,2423.89,2815.88,2615.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,512,1000,1532.7,1564.4,1545.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,1024,1000,2917.88,3155.22,3052.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,2048,1000,4096.67,4120.63,4103.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,4096,1000,7697.65,7712.5,7703.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,8192,1000,15584.46,15652.95,15624.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,16384,1000,33214.42,33296.18,33247.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,32768,993,63759.26,63950.28,63841.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,65536,40,138030.27,139433.09,138865.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,131072,24,248722.48,248915.62,248801.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,262144,24,512821.38,513393.0,513106.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,524288,24,935587.13,936183.52,935877.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,1048576,21,1895102.5,1896549.47,1895930.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,2097152,12,3752665.15,3763329.68,3757240.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Alltoall,360,4194304,9,7337733.19,7342046.62,7340335.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allgatherv,216,0,1000,2.9,7.15,2.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,1,1000,17.66,23.61,20.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,2,1000,17.15,23.63,19.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,4,1000,20.04,26.52,22.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,8,1000,22.28,29.72,25.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,16,1000,28.77,38.07,33.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,32,1000,28.77,43.73,36.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,64,1000,79.61,96.23,92.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,128,1000,95.85,122.67,117.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,256,1000,113.87,161.68,154.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,512,1000,205.6,254.39,240.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,1024,1000,311.17,417.14,386.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,2048,1000,360.7,425.81,403.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,4096,1000,556.11,621.81,590.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,8192,1000,941.37,1048.28,995.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,16384,1000,1740.64,2038.69,1892.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,32768,1000,3380.74,4054.13,3734.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,65536,640,5986.68,7118.87,6574.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,131072,320,11171.42,12979.0,12098.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,262144,160,22474.91,28061.11,25108.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,524288,80,48848.87,53666.02,51193.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,1048576,40,122612.27,130652.92,126031.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,2097152,20,226919.15,234500.43,230520.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgatherv,216,4194304,10,462761.85,481961.28,470094.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,648,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,4,1000,0.33,11.06,0.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,8,1000,0.36,12.38,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,16,1000,0.34,52.38,1.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,32,1000,0.36,19.46,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,64,1000,0.36,23.88,0.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,128,1000,0.34,37.93,1.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,256,1000,0.34,45.54,1.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,512,1000,0.33,23.86,0.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,1024,1000,0.33,16.59,0.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,2048,1000,0.48,16.67,1.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,4096,1000,0.8,20.77,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,8192,1000,2.69,32.36,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,16384,1000,8.19,58.11,13.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,32768,1000,19.08,97.43,27.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,65536,640,67.4,2075.97,1063.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,131072,320,127.27,442.17,329.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,262144,160,95.38,604.69,316.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,524288,80,162.92,1112.45,569.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,1048576,40,221.09,1397.35,743.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,2097152,20,386.79,2066.71,1118.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,648,4194304,10,810.43,3915.51,2018.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Allreduce,504,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,4,1000,6.27,10.08,8.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,8,1000,8.22,13.1,11.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,16,1000,9.6,12.87,11.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,32,1000,9.52,13.05,11.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,64,1000,11.48,17.05,13.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,128,1000,12.21,22.65,15.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,256,1000,14.27,22.3,17.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,512,1000,14.73,22.26,18.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,1024,1000,20.41,34.98,26.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,2048,1000,22.55,30.38,25.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,4096,1000,30.22,40.02,33.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,8192,1000,48.97,59.2,53.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,16384,1000,125.19,204.83,134.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,32768,1000,101.14,121.86,109.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,65536,640,123.41,156.8,136.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,131072,320,169.16,209.58,187.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,262144,160,327.56,400.48,358.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,524288,80,668.9,803.96,726.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,1048576,40,1727.93,2006.1,1940.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,2097152,20,4037.71,4512.52,4231.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Allreduce,504,4194304,10,6304.3,6648.52,6589.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,7, -1
+Alltoall,576,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,1,1000,114.2,119.94,116.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,2,1000,115.92,130.59,121.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,4,1000,134.35,151.89,141.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,8,1000,199.2,230.61,215.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,16,1000,163.86,181.25,173.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,32,1000,249.27,279.14,270.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,64,1000,435.52,497.14,476.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,128,1000,827.21,936.44,897.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,256,1000,3067.48,3247.89,3135.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,512,1000,4269.58,4560.09,4437.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,1024,1000,6071.38,6400.34,6253.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,2048,1000,8771.31,8806.34,8791.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,4096,1000,13855.9,13870.21,13861.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,8192,1000,33068.35,33166.62,33121.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,16384,1000,60102.67,60265.97,60180.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,32768,570,117699.65,117891.88,117785.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,65536,237,259377.11,260900.82,260163.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,131072,45,496551.11,498463.74,497702.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,262144,31,846476.88,846780.17,846621.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,524288,20,1777372.97,1781611.81,1778889.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Alltoall,576,1048576,12,3375909.78,3385058.32,3378235.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Gather,216,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,1,1000,0.54,11.73,1.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,2,1000,0.56,12.74,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,4,1000,0.56,14.2,1.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,8,1000,0.49,14.15,1.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,16,1000,0.46,12.59,1.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,32,1000,0.46,12.48,1.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,64,1000,0.47,16.35,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,128,1000,0.5,27.03,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,256,1000,0.52,29.68,1.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,512,1000,0.72,48.49,2.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,1024,1000,0.87,82.33,4.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,2048,1000,1.32,206.24,8.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,4096,1000,2.26,252.3,12.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,8192,1000,3.74,435.73,21.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,16384,1000,7.85,847.12,41.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,32768,1000,17.46,2942.8,106.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,65536,640,39.74,1202.87,691.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,131072,320,84.46,2206.06,1244.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,262144,160,159.5,6847.67,2551.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,524288,80,320.46,9198.97,5268.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,1048576,40,223.96,24058.05,15865.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,2097152,20,2074.41,40808.81,25553.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Gather,216,4194304,10,13069.06,77657.88,52739.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Bcast,144,0,1000,0.03,0.04,0.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,1,1000,2.35,6.54,4.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,2,1000,0.62,5.83,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,4,1000,0.61,5.91,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,8,1000,0.62,5.87,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,16,1000,0.61,5.77,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,32,1000,0.61,6.23,4.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,64,1000,0.63,5.91,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,128,1000,0.64,6.03,4.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,256,1000,0.73,6.34,4.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,512,1000,0.67,6.8,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,1024,1000,0.8,7.34,5.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,2048,1000,1.27,5.57,3.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,4096,1000,2.52,8.64,5.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,8192,1000,4.8,12.76,9.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,16384,1000,8.08,20.0,16.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,32768,1000,12.95,31.59,26.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,65536,640,30.29,50.63,45.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,131072,320,61.7,92.0,82.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,262144,160,125.59,151.79,144.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,524288,80,257.89,287.25,278.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,1048576,40,523.87,559.21,546.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,2097152,20,1051.18,1110.36,1086.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,144,4194304,10,3440.61,3772.76,3613.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Bcast,576,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,1,1000,2.11,5.24,4.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,2,1000,2.35,6.4,4.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,4,1000,2.3,6.34,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,8,1000,2.35,6.39,4.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,16,1000,2.14,6.29,4.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,32,1000,2.18,6.27,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,64,1000,2.27,6.27,4.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,128,1000,2.32,6.8,5.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,256,1000,2.35,6.99,5.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,512,1000,1.88,6.85,4.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,1024,1000,1.2,8.77,6.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,2048,1000,2.09,10.69,7.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,4096,1000,3.87,19.42,13.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,8192,1000,7.08,21.81,17.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,16384,1000,10.56,31.69,26.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,32768,1000,25.74,71.03,56.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,65536,640,50.94,91.66,79.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,131072,320,101.27,142.18,128.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,262144,160,150.17,226.35,205.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,524288,80,356.81,402.91,377.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,1048576,40,624.74,752.3,646.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,2097152,20,1207.04,1258.42,1239.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Bcast,576,4194304,10,2436.12,2508.45,2470.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,8, -1
+Reduce,720,0,1000,0.06,0.09,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,4,1000,0.32,10.34,0.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,8,1000,0.35,12.39,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,16,1000,0.35,12.01,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,32,1000,0.35,12.77,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,64,1000,0.36,12.42,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,128,1000,0.33,13.94,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,256,1000,0.34,14.38,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,512,1000,0.32,19.15,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,1024,1000,0.34,15.27,0.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,2048,1000,0.45,17.05,1.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,4096,1000,0.78,23.75,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,8192,1000,2.98,65.9,5.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,16384,1000,8.5,61.19,13.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,32768,1000,19.15,110.36,28.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,65536,640,72.48,2075.7,915.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,131072,320,137.99,400.73,280.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,262144,160,102.18,658.17,330.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,524288,80,164.51,1210.2,578.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,1048576,40,212.52,1426.93,739.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,2097152,20,389.8,2427.44,1131.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,720,4194304,10,877.15,28545.28,3367.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,10, -1
+Reduce,432,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,4,1000,0.32,9.67,0.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,8,1000,0.35,9.49,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,16,1000,0.39,8.78,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,32,1000,0.53,13.83,1.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,64,1000,0.36,55.41,1.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,128,1000,0.34,10.29,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,256,1000,0.56,16.08,1.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,512,1000,0.32,13.63,0.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,1024,1000,0.37,26.63,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,2048,1000,0.42,13.97,1.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,4096,1000,0.73,16.87,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,8192,1000,3.0,38.95,5.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,16384,1000,7.57,49.54,12.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,32768,1000,34.11,133.24,81.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,65536,640,79.77,274.63,179.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,131072,320,144.72,365.61,256.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,262144,160,86.07,792.34,394.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,524288,80,149.04,1006.52,531.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,1048576,40,219.13,1327.87,724.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,2097152,20,382.41,2034.74,1096.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Reduce,432,4194304,10,1190.96,3379.71,2892.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Scatterv,144,0,1000,6.09,11.96,8.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,1,1000,6.62,20.39,9.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,2,1000,6.6,19.39,9.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,4,1000,6.7,13.02,9.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,8,1000,6.87,19.03,10.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,16,1000,7.53,14.95,11.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,32,1000,7.08,12.7,9.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,64,1000,7.93,13.87,10.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,128,1000,7.9,15.21,11.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,256,1000,9.3,17.7,13.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,512,1000,10.54,34.8,21.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,1024,1000,13.13,35.42,26.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,2048,1000,16.11,57.15,44.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,4096,1000,12.82,154.54,100.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,8192,1000,37.99,287.84,179.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,16384,1000,46.7,501.83,313.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,32768,1000,59.63,871.95,534.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,65536,640,82.95,1384.82,798.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,131072,320,122.91,2515.98,1440.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,262144,160,647.21,9297.87,5805.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,524288,80,919.77,24062.98,13080.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,1048576,40,1280.05,36306.85,19518.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,2097152,20,1872.12,78197.59,41250.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Scatterv,144,4194304,10,4413.37,160060.62,84675.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,1,1000,39.85,51.27,48.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,2,1000,44.1,63.95,54.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,4,1000,35.5,43.83,39.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,8,1000,42.69,50.53,46.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,16,1000,39.64,51.08,45.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,32,1000,48.56,68.61,57.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,64,1000,56.91,78.07,70.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,128,1000,100.02,135.91,123.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,256,1000,158.75,235.65,209.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,512,1000,354.19,381.4,373.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,1024,1000,476.57,516.52,506.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,2048,1000,901.48,940.79,929.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,4096,1000,1707.94,1840.06,1795.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,8192,1000,3644.42,3672.81,3655.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,16384,1000,7807.15,7879.51,7837.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,32768,1000,14975.18,15101.79,15034.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,65536,640,28276.29,28378.53,28324.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,131072,320,57271.58,57423.26,57348.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,262144,160,113832.9,114143.9,113967.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,524288,80,223052.62,223726.12,223380.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,1048576,40,448019.38,449450.9,448923.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,2097152,20,894854.29,897525.84,896271.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Alltoall,144,4194304,10,1775373.88,1780387.35,1778300.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,2, -1
+Allreduce,360,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,4,1000,5.49,10.05,8.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,8,1000,6.03,10.57,8.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,16,1000,8.16,11.3,9.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,32,1000,8.35,11.62,10.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,64,1000,9.86,15.28,12.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,128,1000,13.33,21.99,18.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,256,1000,12.3,20.04,15.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,512,1000,12.14,21.7,14.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,1024,1000,15.81,22.12,18.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,2048,1000,17.45,23.12,19.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,4096,1000,27.58,36.33,30.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,8192,1000,42.4,51.19,45.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,16384,1000,90.36,115.75,99.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,32768,1000,91.02,109.15,100.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,65536,640,127.93,153.14,136.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,131072,320,209.53,268.56,233.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,262144,160,296.45,365.12,322.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,524288,80,628.7,776.94,684.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,1048576,40,1598.28,1957.83,1783.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,2097152,20,3553.33,3764.23,3651.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Allreduce,360,4194304,10,6121.1,6525.17,6298.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,5, -1
+Bcast,648,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,1,1000,2.2,6.21,4.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,2,1000,2.48,6.84,5.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,4,1000,2.55,6.82,5.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,8,1000,2.48,6.69,5.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,16,1000,2.48,6.65,5.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,32,1000,2.48,6.76,5.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,64,1000,2.51,6.69,5.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,128,1000,2.58,6.97,5.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,256,1000,2.67,7.47,6.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,512,1000,2.06,6.28,4.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,1024,1000,2.12,7.48,5.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,2048,1000,4.62,11.31,8.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,4096,1000,8.41,18.33,13.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,8192,1000,7.29,23.23,18.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,16384,1000,18.85,42.28,35.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,32768,1000,36.01,71.35,63.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,65536,640,49.93,110.35,95.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,131072,320,88.25,147.62,133.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,262144,160,154.12,234.26,211.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,524288,80,316.41,423.41,399.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,1048576,40,685.42,713.31,705.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,2097152,20,1302.34,1347.69,1332.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Bcast,648,4194304,10,3819.19,4364.27,3974.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,9, -1
+Reduce,216,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,4,1000,0.39,34.0,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,8,1000,0.36,15.78,0.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,16,1000,0.35,18.76,0.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,32,1000,0.35,46.03,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,64,1000,0.36,11.4,0.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,128,1000,0.34,12.18,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,256,1000,0.35,11.46,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,512,1000,0.36,11.35,0.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,1024,1000,0.33,10.03,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,2048,1000,0.4,11.54,1.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,4096,1000,0.75,31.44,2.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,8192,1000,2.71,26.74,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,16384,1000,7.03,33.19,11.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,32768,1000,40.47,134.92,82.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,65536,640,64.69,204.64,140.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,131072,320,124.11,332.33,236.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,262144,160,84.67,745.57,385.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,524288,80,144.73,941.97,511.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,1048576,40,228.32,1266.6,717.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,2097152,20,494.24,1695.59,1430.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Reduce,216,4194304,10,681.46,3878.86,2060.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,3, -1
+Allgather,432,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,1,1000,18.68,26.76,23.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,2,1000,15.54,25.33,20.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,4,1000,17.7,27.94,22.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,8,1000,26.47,37.82,32.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,16,1000,32.59,48.72,41.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,32,1000,55.58,84.28,71.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,64,1000,56.05,106.0,90.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,128,1000,71.76,147.87,130.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,256,1000,151.85,240.83,217.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,512,1000,357.64,932.41,500.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,1024,1000,477.25,555.98,530.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,2048,1000,777.76,916.29,857.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,4096,1000,1563.21,1953.25,1691.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,8192,1000,1933.81,2119.86,2037.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,16384,1000,4080.39,4769.16,4427.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,32768,1000,7266.21,8417.69,7883.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,65536,640,13625.6,15734.0,14737.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,131072,320,25963.22,33237.2,29373.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,262144,160,56859.47,75422.9,65373.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,524288,80,97818.56,101850.33,99964.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,1048576,40,197938.98,209374.39,202984.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,2097152,20,459779.14,482690.92,468506.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
+Allgather,432,4194304,10,941958.91,1045540.92,997641.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_07_26_05-44-37,6, -1
diff --git a/results-and-plotting/data/data-single-multi-original.csv b/results-and-plotting/data/data-single-multi-original.csv
new file mode 100644
index 0000000..f8edb56
--- /dev/null
+++ b/results-and-plotting/data/data-single-multi-original.csv
@@ -0,0 +1,5416 @@
+benchmark_type,proc_num,msg_size_bytes,repetitions,t_min_usec,t_max_usec,t_avg_usec,mpi_datatype,mpi_red_datatype,mpi_red_op,creation_time,n_nodes,off_cache_flag
+Allreduce,216,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,4,1000,15.04,17.96,16.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,8,1000,6.24,9.23,7.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,16,1000,6.48,9.7,8.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,32,1000,6.31,9.91,7.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,64,1000,11.41,17.29,13.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,128,1000,10.56,17.33,13.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,256,1000,9.61,17.03,12.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,512,1000,11.8,17.39,14.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,1024,1000,12.91,18.67,14.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,2048,1000,11.24,15.67,13.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,4096,1000,15.3,19.88,16.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,8192,1000,31.44,36.56,33.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,16384,1000,74.75,88.13,80.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,32768,1000,55.0,72.92,61.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,65536,640,89.16,114.75,98.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,131072,320,153.71,192.05,167.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,262144,160,278.36,349.62,306.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,524288,80,640.9,780.47,697.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,1048576,40,1769.21,1830.19,1798.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,2097152,20,3039.84,3080.13,3069.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allreduce,216,4194304,10,5188.43,5248.92,5212.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,0,1000,8.14,15.57,11.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,1,1000,7.89,16.15,11.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,2,1000,7.91,16.34,11.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,4,1000,8.21,16.69,11.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,8,1000,8.23,16.83,11.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,16,1000,8.83,19.26,13.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,32,1000,9.69,20.69,14.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,64,1000,11.52,23.61,16.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,128,1000,12.82,25.74,17.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,256,1000,14.98,31.97,21.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,512,1000,18.31,40.75,29.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,1024,1000,17.33,54.36,35.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,2048,1000,17.99,75.06,50.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,4096,1000,13.39,141.37,89.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,8192,1000,40.27,269.19,162.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,16384,1000,49.32,540.89,304.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,32768,1000,43.43,526.87,361.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,65536,640,47.6,1012.06,638.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,131072,320,59.87,1964.07,1199.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,262144,160,465.73,8297.19,4927.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,524288,80,535.85,17031.29,9787.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,1048576,40,1104.86,35316.66,20033.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,2097152,20,1818.42,79723.46,45758.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatterv,216,4194304,10,3970.01,150225.62,87786.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,1,1000,0.55,25.21,2.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,2,1000,0.55,15.75,1.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,4,1000,0.56,16.93,1.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,8,1000,0.55,21.07,2.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,16,1000,0.57,20.37,1.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,32,1000,0.57,17.49,1.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,64,1000,0.57,20.44,1.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,128,1000,0.6,29.9,2.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,256,1000,0.6,42.52,2.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,512,1000,0.81,51.13,3.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,1024,1000,0.99,91.47,5.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,2048,1000,1.12,153.39,6.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,4096,1000,1.79,249.7,11.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,8192,1000,2.83,452.38,20.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,16384,1000,5.48,849.73,38.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,32768,1000,10.72,2020.1,72.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,65536,640,22.92,1230.69,697.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,131072,320,51.32,2191.05,1205.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,262144,160,119.19,4331.16,2398.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,524288,80,248.44,9058.12,5099.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,1048576,40,127.95,23766.15,15637.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,2097152,20,3316.23,39881.25,24410.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,216,4194304,10,12004.45,76563.3,51524.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,1,1000,46.48,51.32,49.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,2,1000,46.43,51.71,49.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,4,1000,50.71,57.39,54.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,8,1000,57.96,65.59,62.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,16,1000,61.37,73.13,67.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,32,1000,69.98,90.2,81.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,64,1000,108.27,141.97,129.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,128,1000,190.18,252.23,228.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,256,1000,766.44,842.43,810.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,512,1000,788.26,864.43,834.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,1024,1000,1188.1,1244.96,1225.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,2048,1000,2242.27,2329.56,2296.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,4096,1000,4281.34,4316.46,4296.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,8192,1000,8351.56,8402.3,8373.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,16384,633,16005.53,16095.75,16045.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,32768,307,31878.33,32070.82,31976.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,65536,9,200642.13,206349.73,204667.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,131072,9,119379.2,119701.29,119554.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,262144,9,243290.2,244393.29,243885.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,524288,9,487485.41,489627.9,488744.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,1048576,7,967414.4,972542.42,970282.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,2097152,4,1942529.14,1952214.25,1947967.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,216,4194304,2,3878851.55,3896201.77,3888566.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,144,0,1000,2.19,5.87,2.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,1,1000,13.37,20.2,16.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,2,1000,29.88,53.89,38.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,4,1000,14.19,23.32,18.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,8,1000,17.88,24.71,20.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,16,1000,20.86,28.29,23.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,32,1000,24.06,34.46,29.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,64,1000,23.98,43.58,35.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,128,1000,74.54,95.83,90.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,256,1000,97.9,132.42,125.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,512,1000,129.07,187.6,177.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,1024,1000,262.5,350.11,306.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,2048,1000,388.92,425.94,415.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,4096,1000,352.0,410.1,381.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,8192,1000,594.05,670.85,630.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,16384,1000,1074.28,1334.13,1209.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,32768,1000,2058.67,2684.1,2385.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,65536,640,3742.89,4837.0,4333.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,131072,320,6977.04,8712.38,7907.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,262144,160,13497.97,16652.35,15125.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,524288,80,29798.85,30809.53,30291.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,1048576,40,64827.71,66473.66,65705.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,2097152,20,150094.47,155707.33,152947.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgatherv,144,4194304,10,306191.89,316100.53,310924.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,288,0,1000,2.73,10.87,5.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,1,1000,32.29,231.69,147.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,2,1000,32.37,264.76,156.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,4,1000,32.34,247.02,151.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,8,1000,32.41,344.58,151.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,16,1000,32.75,231.15,147.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,32,1000,32.49,245.65,151.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,64,1000,32.95,238.67,153.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,128,1000,32.76,253.12,155.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,256,1000,33.71,252.81,157.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,512,1000,39.25,262.35,170.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,1024,1000,48.44,312.66,210.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,2048,1000,62.72,393.77,274.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,4096,1000,65.69,479.49,339.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,8192,1000,72.92,573.79,415.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,16384,1000,90.2,918.3,680.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,32768,1000,143.91,1566.58,1179.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,65536,640,197.57,2094.15,1223.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,131072,320,399.72,4149.71,2242.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,262144,160,2012.54,7598.31,4502.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,524288,80,4252.27,15633.55,9476.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,1048576,40,11616.3,30646.67,18948.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,2097152,20,24481.88,62344.89,39108.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gatherv,288,4194304,10,34025.69,109557.85,64048.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,18,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,4,1000,1.28,1.54,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,8,1000,1.18,1.44,1.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,16,1000,1.25,1.47,1.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,32,1000,1.27,1.61,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,64,1000,1.35,2.16,1.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,128,1000,2.0,2.94,2.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,256,1000,1.7,2.57,1.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,512,1000,2.04,2.77,2.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,1024,1000,3.03,3.94,3.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,2048,1000,5.04,6.5,5.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,4096,1000,6.81,8.69,7.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,8192,1000,10.58,12.12,11.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,16384,1000,18.71,20.32,20.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,32768,1000,32.72,33.0,32.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,65536,640,46.82,47.73,47.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,131072,320,91.12,93.12,92.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,262144,160,176.86,181.45,179.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,524288,80,338.35,342.23,340.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,1048576,40,686.47,700.32,693.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,2097152,20,994.27,1026.44,1010.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,4194304,10,1996.41,2069.74,2042.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,0,1000,0.38,0.51,0.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,1,1000,4.52,5.22,4.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,2,1000,4.69,5.83,5.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,4,1000,4.88,5.77,5.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,8,1000,5.22,6.19,5.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,16,1000,5.7,6.73,6.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,32,1000,6.35,7.64,6.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,64,1000,16.58,18.41,17.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,128,1000,18.06,20.08,18.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,256,1000,25.51,27.13,26.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,512,1000,33.43,35.35,33.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,1024,1000,35.97,37.33,36.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,2048,1000,44.36,45.59,44.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,4096,1000,58.91,59.78,59.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,8192,1000,85.0,86.06,85.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,16384,1000,132.39,133.93,133.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,32768,1000,183.97,191.45,187.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,65536,640,467.0,498.5,486.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,131072,320,1223.99,1252.2,1242.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,262144,160,2832.97,2869.58,2851.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,524288,80,6616.44,6956.23,6796.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,1048576,40,15735.94,16385.58,16130.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,2097152,20,32773.67,32776.18,32774.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,36,4194304,10,66669.73,66672.32,66670.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,288,0,1000,0.05,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,4,1000,4.74,7.82,6.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,8,1000,6.57,10.2,8.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,16,1000,6.2,10.33,8.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,32,1000,5.56,9.66,7.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,64,1000,7.59,12.44,9.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,128,1000,8.52,15.66,11.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,256,1000,9.24,16.59,12.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,512,1000,10.64,16.25,13.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,1024,1000,12.91,18.83,15.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,2048,1000,15.65,25.79,18.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,4096,1000,22.19,28.03,24.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,8192,1000,47.09,58.65,50.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,16384,1000,70.85,85.1,78.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,32768,1000,70.75,89.92,79.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,65536,640,97.1,125.44,106.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,131072,320,151.5,201.89,167.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,262144,160,276.38,359.09,309.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,524288,80,436.01,551.51,479.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,1048576,40,2405.83,3232.3,2824.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,2097152,20,3096.0,3152.0,3132.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allreduce,288,4194304,10,5243.66,5309.87,5287.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,1,1000,7.1,7.6,7.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,2,1000,7.18,7.69,7.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,4,1000,7.38,8.0,7.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,8,1000,7.93,8.56,8.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,16,1000,8.3,8.96,8.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,32,1000,7.56,7.99,7.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,64,1000,9.73,11.11,10.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,128,1000,10.59,12.06,11.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,256,1000,11.95,13.39,12.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,512,1000,17.39,17.69,17.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,1024,1000,22.6,22.89,22.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,2048,1000,37.37,38.12,37.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,4096,1000,65.99,66.97,66.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,8192,1000,119.88,122.51,121.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,16384,1000,240.13,242.6,241.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,32768,1000,473.9,476.83,475.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,65536,640,935.78,942.17,939.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,131072,320,1527.96,1570.75,1548.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,262144,160,2571.66,2579.7,2575.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,524288,80,5042.79,5080.46,5060.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,1048576,40,10000.33,10055.1,10037.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,2097152,20,20092.49,20167.4,20139.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,18,4194304,10,39597.78,39789.88,39701.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,0,1000,0.61,0.84,0.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,1,1000,7.51,17.07,16.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,2,1000,6.37,7.5,6.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,4,1000,7.05,8.42,7.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,8,1000,6.8,7.81,7.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,16,1000,10.07,19.75,11.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,32,1000,17.39,19.91,17.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,64,1000,18.28,20.73,18.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,128,1000,23.97,26.14,24.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,256,1000,43.49,46.51,44.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,512,1000,79.61,86.17,81.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,1024,1000,103.23,122.94,112.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,2048,1000,105.32,108.92,107.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,4096,1000,171.36,178.32,175.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,8192,1000,300.01,310.05,305.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,16384,1000,427.08,435.17,429.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,32768,1000,825.77,886.73,854.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,65536,640,1582.01,1749.89,1668.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,131072,320,3196.84,3518.5,3356.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,262144,160,6472.19,7085.48,6783.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,524288,80,16852.31,17443.56,17057.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,1048576,40,36070.3,36075.34,36071.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,2097152,20,77097.05,77102.7,77098.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,4194304,10,149736.86,149742.27,149738.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,288,0,1000,3.54,9.49,3.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,1,1000,21.43,28.03,24.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,2,1000,24.56,31.58,28.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,4,1000,23.2,31.05,26.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,8,1000,31.0,50.47,38.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,16,1000,53.85,100.05,74.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,32,1000,66.97,101.63,87.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,64,1000,82.57,99.87,94.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,128,1000,95.65,129.17,117.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,256,1000,129.67,185.55,167.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,512,1000,195.55,259.35,235.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,1024,1000,361.89,390.52,381.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,2048,1000,618.06,642.53,635.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,4096,1000,657.26,819.78,724.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,8192,1000,1128.81,1315.27,1239.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,16384,1000,2330.28,2905.4,2617.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,32768,1000,4687.81,5491.64,5094.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,65536,640,8492.46,10030.06,9343.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,131072,320,15718.02,17944.19,16791.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,262144,160,30210.28,34520.19,32461.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,524288,80,60645.39,62275.84,61500.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,1048576,40,132885.42,136574.77,134590.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,2097152,20,315311.51,328323.15,321839.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,288,4194304,10,619443.21,640145.89,629336.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,144,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,1,1000,0.57,16.81,1.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,2,1000,0.56,15.89,1.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,4,1000,0.57,17.3,1.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,8,1000,0.55,17.32,1.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,16,1000,0.5,15.89,1.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,32,1000,0.5,16.65,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,64,1000,0.47,18.12,1.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,128,1000,0.5,22.32,1.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,256,1000,0.53,29.92,1.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,512,1000,0.7,43.88,2.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,1024,1000,0.86,73.37,4.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,2048,1000,1.32,172.29,10.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,4096,1000,2.27,237.73,11.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,8192,1000,3.24,363.88,10.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,16384,1000,6.25,610.49,15.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,32768,1000,12.09,946.72,24.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,65536,640,41.0,1011.66,528.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,131072,320,90.44,1674.81,898.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,262144,160,178.85,3126.87,1678.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,524288,80,350.59,6722.32,3588.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,1048576,40,232.11,18066.17,9163.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,2097152,20,2445.11,28182.87,16701.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,4194304,10,12196.02,53005.54,32246.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,1,1000,0.72,1.85,1.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,2,1000,0.71,1.77,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,4,1000,0.71,1.77,1.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,8,1000,0.51,0.93,0.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,16,1000,0.49,0.86,0.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,32,1000,0.49,0.91,0.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,64,1000,0.28,1.13,0.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,128,1000,0.48,1.43,0.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,256,1000,0.44,1.35,0.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,512,1000,0.42,1.24,0.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,1024,1000,0.56,1.38,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,2048,1000,1.1,2.47,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,4096,1000,1.64,3.63,2.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,8192,1000,3.53,5.8,4.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,16384,1000,7.81,10.83,8.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,32768,1000,13.05,15.7,13.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,65536,640,25.36,28.06,26.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,131072,320,45.38,47.55,45.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,262144,160,89.93,92.09,90.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,524288,80,176.14,178.97,176.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,1048576,40,344.8,347.69,345.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,2097152,20,674.0,676.38,674.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,18,4194304,10,1370.2,1371.87,1370.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,144,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,1,1000,34.23,40.23,37.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,2,1000,36.14,41.44,38.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,4,1000,38.79,46.89,42.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,8,1000,49.33,70.29,60.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,16,1000,79.83,130.5,92.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,32,1000,53.56,68.49,62.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,64,1000,58.33,81.05,72.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,128,1000,101.55,133.29,121.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,256,1000,161.0,234.26,210.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,512,1000,334.19,377.27,362.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,1024,1000,496.23,538.22,526.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,2048,1000,912.33,952.2,940.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,4096,1000,1733.75,1876.42,1826.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,8192,1000,4031.72,4079.88,4053.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,16384,1000,7434.51,7526.14,7477.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,32768,678,14359.16,14470.18,14403.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,65536,32,28172.17,28253.26,28213.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,131072,32,56171.1,56271.25,56228.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,262144,32,111857.84,112116.17,111970.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,524288,32,228674.98,229762.4,229245.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,1048576,15,460584.26,463264.26,462069.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,2097152,9,894068.61,895965.37,895131.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Alltoall,144,4194304,5,1792416.86,1797862.53,1794733.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,216,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,4,1000,0.39,17.62,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,8,1000,0.35,27.74,1.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,16,1000,0.36,26.57,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,32,1000,0.36,32.77,1.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,64,1000,0.36,9.46,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,128,1000,0.34,10.22,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,256,1000,0.35,11.2,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,512,1000,0.32,10.9,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,1024,1000,0.35,14.72,1.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,2048,1000,0.46,91.06,3.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,4096,1000,0.79,33.79,2.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,8192,1000,3.37,28.47,5.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,16384,1000,7.01,34.08,11.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,32768,1000,41.36,135.91,84.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,65536,640,64.31,204.21,140.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,131072,320,115.44,329.96,230.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,262144,160,82.16,726.04,377.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,524288,80,131.33,877.23,470.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,1048576,40,218.1,1333.79,717.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,2097152,20,479.91,1671.28,1416.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,216,4194304,10,693.28,3933.65,2046.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,0,1000,1.05,1.15,1.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,4,1000,1.58,14.19,2.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,8,1000,1.58,22.46,2.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,16,1000,1.58,16.58,2.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,32,1000,1.35,16.81,3.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,64,1000,1.37,17.99,4.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,128,1000,1.38,20.3,5.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,256,1000,1.4,19.72,7.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,512,1000,1.51,26.6,13.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,1024,1000,14.59,25.05,18.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,2048,1000,18.71,32.9,24.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,4096,1000,21.53,36.74,28.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,8192,1000,43.16,63.95,53.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,16384,1000,115.08,144.25,133.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,32768,1000,166.28,196.23,183.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,65536,640,233.45,321.06,271.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,131072,320,336.6,511.48,432.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,262144,160,636.8,721.73,671.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,524288,80,822.05,912.39,857.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,1048576,40,1428.71,1539.04,1475.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,2097152,20,2481.71,2594.22,2536.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,216,4194304,10,3273.34,3906.06,3537.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,54,0,1000,0.48,0.56,0.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,4,1000,6.5,8.03,7.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,8,1000,0.83,5.74,1.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,16,1000,0.85,6.42,2.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,32,1000,0.89,7.18,2.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,64,1000,0.92,7.28,3.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,128,1000,0.93,8.53,5.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,256,1000,7.18,9.25,8.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,512,1000,6.24,7.47,6.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,1024,1000,8.82,10.53,9.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,2048,1000,7.95,9.99,8.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,4096,1000,10.28,12.29,11.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,8192,1000,12.37,14.58,13.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,16384,1000,18.06,20.86,19.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,32768,1000,29.29,33.4,32.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,65536,640,51.11,58.19,56.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,131072,320,275.3,339.49,308.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,262144,160,146.58,196.32,172.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,524288,80,269.73,349.55,318.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,1048576,40,512.58,633.62,591.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,2097152,20,1005.85,1189.97,1123.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,4194304,10,1925.11,2281.28,2180.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,1,1000,1.16,2.6,1.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,2,1000,1.17,10.29,2.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,4,1000,1.2,9.9,2.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,8,1000,1.26,3.07,2.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,16,1000,1.36,3.7,2.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,32,1000,1.3,3.91,2.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,64,1000,1.46,4.18,3.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,128,1000,1.66,14.48,4.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,256,1000,2.03,7.02,5.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,512,1000,3.16,10.55,8.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,1024,1000,4.3,13.67,10.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,2048,1000,6.06,22.93,17.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,4096,1000,3.14,86.09,42.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,8192,1000,27.1,216.46,147.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,16384,1000,32.23,276.68,195.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,32768,1000,86.09,533.59,428.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,65536,640,220.68,1059.22,918.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,131072,320,103.72,1434.31,1197.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,262144,160,203.12,2825.77,2421.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,524288,80,359.59,5454.31,4878.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,1048576,40,461.62,7253.36,6335.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,2097152,20,946.06,54517.45,51411.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,72,4194304,10,1443.84,14925.85,11004.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,18,0,1000,0.05,0.05,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,4,1000,1.27,1.55,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,8,1000,1.26,1.51,1.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,16,1000,1.25,1.52,1.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,32,1000,1.31,1.62,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,64,1000,1.44,2.36,1.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,128,1000,2.06,2.97,2.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,256,1000,1.83,2.78,2.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,512,1000,2.54,3.52,2.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,1024,1000,3.72,4.74,3.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,2048,1000,5.83,7.01,6.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,4096,1000,8.89,10.11,9.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,8192,1000,10.36,13.18,12.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,16384,1000,17.8,22.02,21.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,32768,1000,31.94,37.2,36.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,65536,640,33.41,35.87,34.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,131072,320,53.7,55.34,54.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,262144,160,95.7,99.09,97.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,524288,80,154.68,161.08,158.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,1048576,40,361.5,418.84,403.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,2097152,20,840.53,918.04,899.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,18,4194304,10,1858.88,1972.67,1944.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,216,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,1,1000,11.63,17.12,14.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,2,1000,13.91,31.36,27.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,4,1000,24.8,43.47,33.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,8,1000,27.43,51.44,45.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,16,1000,18.52,31.4,23.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,32,1000,16.23,24.83,21.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,64,1000,42.59,74.36,60.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,128,1000,37.97,59.85,55.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,256,1000,73.79,120.85,114.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,512,1000,160.23,206.72,198.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,1024,1000,316.37,430.76,394.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,2048,1000,480.77,596.92,533.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,4096,1000,654.89,758.56,728.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,8192,1000,915.45,1027.95,965.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,16384,1000,1710.64,1988.47,1851.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,32768,1000,3388.16,3992.45,3710.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,65536,640,6151.98,7726.93,7022.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,131072,310,11496.9,15375.84,13535.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,262144,160,21540.9,32116.54,26118.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,524288,80,45678.3,47139.1,46578.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,1048576,40,97927.26,107022.04,101869.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,2097152,20,228288.66,239716.39,232721.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,216,4194304,10,463147.18,478627.1,470667.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,54,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,1,1000,1.43,3.17,2.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,2,1000,1.51,3.32,2.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,4,1000,1.61,3.55,2.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,8,1000,0.93,2.13,1.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,16,1000,0.92,2.06,1.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,32,1000,0.89,2.05,1.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,64,1000,1.01,4.5,1.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,128,1000,1.41,4.69,2.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,256,1000,0.64,3.17,2.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,512,1000,1.12,2.93,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,1024,1000,1.07,2.19,2.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,2048,1000,1.67,3.17,2.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,4096,1000,1.92,4.47,2.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,8192,1000,3.88,6.61,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,16384,1000,7.33,10.41,7.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,32768,1000,12.77,15.83,13.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,65536,640,25.15,28.91,26.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,131072,320,48.45,53.29,49.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,262144,160,96.09,99.88,96.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,524288,80,189.74,193.9,190.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,1048576,40,384.15,388.13,384.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,2097152,20,752.2,757.12,753.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,54,4194304,10,1517.85,1523.98,1519.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,4,1000,2.28,4.4,3.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,8,1000,2.53,3.23,2.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,16,1000,2.69,3.47,3.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,32,1000,3.03,3.96,3.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,64,1000,3.98,7.46,4.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,128,1000,4.32,7.39,4.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,256,1000,6.96,10.19,7.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,512,1000,7.9,10.9,8.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,1024,1000,9.35,12.78,10.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,2048,1000,11.24,15.5,12.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,4096,1000,15.27,18.27,15.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,8192,1000,24.4,27.45,25.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,16384,1000,29.01,40.71,38.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,32768,1000,40.41,48.99,42.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,65536,640,65.29,79.27,68.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,131072,320,202.82,221.09,213.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,262144,160,182.5,213.36,200.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,524288,80,234.69,284.09,265.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,1048576,40,440.75,494.18,470.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,2097152,20,906.71,1031.43,976.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,72,4194304,10,1955.43,2192.29,2090.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,288,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,1,1000,0.49,13.63,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,2,1000,0.56,16.84,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,4,1000,0.56,18.38,1.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,8,1000,0.5,15.78,1.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,16,1000,0.49,16.45,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,32,1000,0.46,18.74,1.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,64,1000,0.47,23.11,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,128,1000,0.49,29.3,1.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,256,1000,0.53,46.4,2.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,512,1000,0.83,79.97,3.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,1024,1000,0.87,115.13,5.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,2048,1000,1.3,269.4,7.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,4096,1000,2.28,345.85,14.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,8192,1000,4.23,643.63,27.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,16384,1000,8.81,1158.28,48.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,32768,1000,14.3,2752.25,84.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,65536,640,38.06,2202.01,1230.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,131072,320,80.22,3999.49,2166.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,262144,160,153.07,7749.72,4188.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,524288,80,309.92,15244.6,8212.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,1048576,40,230.84,30312.08,16213.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,2097152,20,2631.6,61801.3,34452.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gather,288,4194304,10,12296.98,106750.29,57143.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,36,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,1,1000,3.39,4.39,3.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,2,1000,3.41,4.47,3.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,4,1000,3.69,4.83,4.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,8,1000,4.07,5.44,4.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,16,1000,5.37,6.38,5.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,32,1000,6.38,8.1,7.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,64,1000,5.51,7.39,5.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,128,1000,7.0,9.48,7.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,256,1000,10.78,13.33,11.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,512,1000,28.12,29.67,28.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,1024,1000,29.14,32.99,29.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,2048,1000,50.76,51.69,51.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,4096,1000,83.33,84.21,83.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,8192,1000,144.89,146.01,145.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,16384,1000,199.84,200.72,200.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,32768,1000,390.59,393.26,391.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,65536,640,769.08,785.03,779.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,131072,320,1542.93,1568.44,1558.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,262144,160,3103.38,3141.93,3123.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,524288,80,6148.65,6211.92,6179.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,1048576,40,15769.96,15965.87,15890.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,2097152,20,37433.23,37769.69,37590.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,36,4194304,10,75784.56,76714.79,76386.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,144,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,1,1000,3.35,7.39,5.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,2,1000,1.2,5.13,3.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,4,1000,3.24,7.77,5.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,8,1000,3.28,8.04,5.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,16,1000,1.78,8.94,5.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,32,1000,3.21,9.83,6.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,64,1000,5.84,13.33,9.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,128,1000,8.36,18.38,14.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,256,1000,11.78,26.12,19.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,512,1000,11.55,41.12,28.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,1024,1000,15.39,54.94,42.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,2048,1000,21.91,91.66,74.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,4096,1000,31.57,163.67,137.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,8192,1000,51.59,321.52,267.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,16384,1000,88.6,506.05,424.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,32768,1000,21.82,431.48,201.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,65536,640,22.57,414.05,265.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,131072,320,42.05,801.4,422.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,262144,160,132.84,1565.0,1255.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,524288,80,112.37,3114.95,2737.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,1048576,40,272.5,6248.28,5738.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,2097152,20,7839.11,12544.36,11882.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,4194304,10,23610.45,72187.27,47898.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,216,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,1,1000,0.82,5.98,4.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,2,1000,0.8,6.37,4.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,4,1000,0.81,6.02,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,8,1000,0.81,6.09,4.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,16,1000,0.81,6.19,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,32,1000,0.82,6.15,4.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,64,1000,0.83,6.16,4.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,128,1000,0.85,6.22,4.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,256,1000,0.97,6.84,5.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,512,1000,0.95,6.49,4.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,1024,1000,1.04,6.17,4.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,2048,1000,1.57,7.46,5.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,4096,1000,3.85,10.59,7.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,8192,1000,6.33,15.03,11.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,16384,1000,13.31,31.75,26.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,32768,1000,24.27,55.4,50.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,65536,640,45.98,80.32,64.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,131072,320,64.55,111.98,96.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,262144,160,130.77,235.21,176.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,524288,80,263.38,429.43,316.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,1048576,40,543.44,823.78,622.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,2097152,20,1064.85,1292.62,1212.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Bcast,216,4194304,10,2225.08,2617.52,2471.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,288,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,1,1000,1.22,9.75,4.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,2,1000,1.2,11.28,5.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,4,1000,1.57,13.28,6.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,8,1000,1.74,12.01,6.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,16,1000,2.7,12.07,6.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,32,1000,3.84,14.88,8.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,64,1000,5.81,19.28,11.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,128,1000,7.75,25.22,15.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,256,1000,10.43,34.4,23.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,512,1000,23.47,79.15,58.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,1024,1000,23.39,95.86,72.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,2048,1000,34.39,166.06,123.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,4096,1000,50.76,255.6,190.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,8192,1000,101.53,525.62,369.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,16384,1000,178.54,842.1,605.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,32768,1000,22.5,1089.3,504.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,65536,640,47.96,4173.5,1477.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,131072,320,60.13,3061.92,1848.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,262144,160,122.04,4841.35,2701.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,524288,80,259.81,9358.29,5751.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,1048576,40,3763.73,19653.84,14617.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,2097152,20,4186.45,38268.11,29909.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,288,4194304,10,19069.66,74386.89,61247.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,144,0,1000,1.85,6.04,4.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,1,1000,16.62,102.99,55.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,2,1000,16.94,96.4,54.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,4,1000,16.41,94.22,54.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,8,1000,16.11,94.97,54.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,16,1000,16.1,93.85,54.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,32,1000,16.57,94.48,55.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,64,1000,17.42,97.41,55.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,128,1000,19.15,107.12,56.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,256,1000,19.53,116.89,56.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,512,1000,21.1,127.42,60.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,1024,1000,23.09,115.97,69.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,2048,1000,38.11,168.98,86.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,4096,1000,50.5,189.49,112.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,8192,1000,58.05,254.35,152.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,16384,1000,70.69,418.94,229.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,32768,1000,115.8,723.38,358.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,65536,640,224.0,1233.41,772.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,131072,320,818.29,2140.78,1474.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,262144,160,2280.1,4202.7,3192.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,524288,80,5033.54,8996.92,7018.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,1048576,40,11422.8,17493.46,14360.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,2097152,20,24410.66,36513.06,30340.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gatherv,144,4194304,10,34195.0,58370.8,46169.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,18,0,1000,0.71,1.86,1.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,1,1000,2.4,3.35,2.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,2,1000,2.43,3.41,2.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,4,1000,2.27,3.25,2.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,8,1000,2.44,3.43,3.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,16,1000,2.31,3.38,2.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,32,1000,2.51,3.56,3.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,64,1000,2.46,3.57,3.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,128,1000,1.52,4.49,2.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,256,1000,1.59,4.9,3.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,512,1000,3.16,6.45,5.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,1024,1000,2.14,10.93,6.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,2048,1000,2.77,17.76,9.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,4096,1000,3.5,25.47,13.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,8192,1000,6.9,36.46,26.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,16384,1000,7.27,46.3,35.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,32768,1000,7.31,78.48,57.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,65536,640,10.14,109.06,69.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,131072,320,15.75,80.19,49.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,262144,160,27.17,143.93,90.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,524288,80,58.35,292.56,184.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,1048576,40,321.24,1685.48,1466.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,2097152,20,690.43,2774.77,2425.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,18,4194304,10,1348.63,5568.9,4849.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,1,1000,1.41,3.56,2.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,2,1000,1.5,3.5,2.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,4,1000,1.58,3.66,2.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,8,1000,0.96,1.88,1.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,16,1000,0.97,2.01,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,32,1000,0.97,1.99,1.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,64,1000,0.83,4.33,1.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,128,1000,1.25,4.55,2.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,256,1000,0.6,3.13,2.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,512,1000,1.16,4.53,2.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,1024,1000,1.07,2.25,2.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,2048,1000,1.62,2.97,2.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,4096,1000,2.07,4.98,2.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,8192,1000,4.33,7.31,5.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,16384,1000,7.35,10.4,8.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,32768,1000,13.06,16.11,13.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,65536,640,26.43,30.04,27.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,131072,320,51.59,55.1,52.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,262144,160,99.78,103.29,100.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,524288,80,198.97,202.65,199.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,1048576,40,394.31,399.17,395.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,2097152,20,796.7,873.94,805.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,54,4194304,10,1554.08,1559.51,1555.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,4,1000,0.21,0.94,0.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,8,1000,0.21,0.95,0.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,16,1000,0.22,0.95,0.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,32,1000,0.21,0.94,0.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,64,1000,0.22,1.11,0.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,128,1000,0.22,1.37,0.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,256,1000,0.22,1.5,0.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,512,1000,0.22,1.6,0.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,1024,1000,0.24,1.94,0.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,2048,1000,0.32,2.66,0.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,4096,1000,0.73,4.13,1.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,8192,1000,1.51,7.43,2.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,16384,1000,6.32,14.18,8.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,32768,1000,11.62,23.56,14.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,65536,640,21.99,38.37,27.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,131072,320,41.52,67.45,48.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,262144,160,80.87,124.22,93.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,524288,80,115.98,193.64,145.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,1048576,40,230.79,352.28,266.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,2097152,20,473.11,680.96,526.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,4194304,10,953.79,1327.33,1047.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,288,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,1,1000,1.19,10.68,5.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,2,1000,1.25,13.78,6.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,4,1000,1.27,14.08,6.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,8,1000,1.29,15.1,7.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,16,1000,2.87,15.87,8.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,32,1000,4.29,18.75,9.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,64,1000,6.39,23.6,13.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,128,1000,9.78,29.76,17.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,256,1000,13.26,40.7,26.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,512,1000,16.42,58.13,43.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,1024,1000,23.06,76.92,62.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,2048,1000,36.13,152.76,116.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,4096,1000,54.07,232.96,179.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,8192,1000,93.79,438.83,322.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,16384,1000,179.45,848.03,604.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,32768,1000,11.43,895.71,414.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,65536,640,22.03,1244.48,600.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,131072,320,58.35,2351.99,1197.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,262144,160,104.17,4882.39,2705.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,524288,80,247.13,9581.07,6193.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,1048576,40,275.23,18738.55,13845.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,2097152,20,5483.85,37436.52,29375.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatter,288,4194304,10,16830.03,74786.64,60630.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,72,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,1,1000,0.37,4.27,0.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,2,1000,0.37,4.53,0.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,4,1000,0.38,5.21,1.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,8,1000,0.36,4.43,0.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,16,1000,0.38,13.62,1.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,32,1000,0.38,6.25,1.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,64,1000,0.38,6.71,1.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,128,1000,0.4,7.89,1.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,256,1000,0.42,9.22,1.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,512,1000,0.58,12.95,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,1024,1000,0.6,25.62,2.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,2048,1000,0.82,41.24,4.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,4096,1000,1.32,71.95,7.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,8192,1000,5.54,159.81,17.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,16384,1000,6.08,231.07,22.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,32768,1000,10.73,361.96,46.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,65536,640,17.38,587.08,54.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,131072,320,36.5,1025.58,86.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,262144,160,78.38,1953.7,167.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,524288,80,169.42,3819.6,327.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,1048576,40,403.02,9546.08,707.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,2097152,20,5234.26,16098.77,6065.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,72,4194304,10,19661.01,30319.34,20487.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,216,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,1,1000,49.01,53.88,51.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,2,1000,51.94,57.26,54.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,4,1000,51.72,58.28,54.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,8,1000,55.86,63.12,59.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,16,1000,63.49,77.1,68.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,32,1000,69.02,85.52,77.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,64,1000,104.67,138.93,125.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,128,1000,198.1,250.08,227.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,256,1000,693.31,767.36,743.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,512,1000,822.11,869.67,854.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,1024,1000,1177.5,1279.2,1243.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,2048,1000,2166.08,2264.12,2228.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,4096,1000,4133.33,4165.34,4146.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,8192,1000,7764.71,7808.3,7781.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,16384,640,15451.39,15535.79,15490.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,32768,318,31732.67,31929.25,31824.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,65536,9,965413.83,1010739.17,995370.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,131072,9,118986.97,119471.84,119230.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,262144,9,250631.6,251346.87,250927.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,524288,9,481931.13,484193.81,483232.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,1048576,7,965046.12,967860.82,966693.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,2097152,4,1911063.74,1916744.95,1914053.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Alltoall,216,4194304,2,3796745.39,3813083.62,3805204.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,18,0,1000,0.28,0.32,0.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,1,1000,3.52,3.99,3.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,2,1000,3.51,4.1,3.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,4,1000,3.51,4.0,3.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,8,1000,3.61,4.17,3.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,16,1000,3.83,4.34,3.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,32,1000,3.68,4.11,3.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,64,1000,4.12,4.7,4.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,128,1000,9.78,10.96,10.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,256,1000,11.15,12.36,11.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,512,1000,14.6,15.33,15.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,1024,1000,17.65,18.21,17.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,2048,1000,25.55,26.26,25.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,4096,1000,42.76,43.47,42.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,8192,1000,75.1,76.35,75.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,16384,1000,105.8,106.9,106.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,32768,1000,194.56,196.16,195.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,65536,640,377.53,380.68,379.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,131072,320,758.41,763.62,760.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,262144,160,1572.47,1583.5,1576.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,524288,80,3183.01,3191.74,3186.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,1048576,40,8010.85,8163.7,8086.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,2097152,20,19121.26,19352.41,19255.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,18,4194304,10,38622.73,39114.57,38986.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,1,1000,3.43,4.45,3.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,2,1000,3.59,4.63,3.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,4,1000,3.7,4.79,4.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,8,1000,4.01,5.35,4.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,16,1000,5.22,6.35,5.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,32,1000,4.58,5.84,5.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,64,1000,5.51,6.68,5.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,128,1000,7.63,9.01,7.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,256,1000,12.95,14.7,13.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,512,1000,29.72,31.02,30.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,1024,1000,34.59,36.49,35.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,2048,1000,44.37,45.57,44.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,4096,1000,58.42,59.54,58.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,8192,1000,84.8,86.0,85.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,16384,1000,132.64,134.28,133.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,32768,1000,183.06,193.95,188.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,65536,640,478.97,537.19,509.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,131072,320,1255.7,1292.0,1279.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,262144,160,2866.75,2914.93,2898.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,524288,80,6242.95,6278.17,6260.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,1048576,40,15713.79,15987.61,15861.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,2097152,20,36705.24,37650.3,37336.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,4194304,10,76042.42,76404.53,76223.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,144,0,1000,1.77,6.29,4.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,1,1000,17.74,103.11,55.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,2,1000,18.0,93.88,54.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,4,1000,17.41,92.99,54.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,8,1000,16.89,93.88,54.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,16,1000,16.92,93.93,54.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,32,1000,17.51,94.86,55.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,64,1000,18.41,98.57,56.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,128,1000,18.24,96.78,55.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,256,1000,18.51,96.59,56.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,512,1000,25.29,108.86,64.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,1024,1000,34.45,134.81,78.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,2048,1000,42.86,171.26,100.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,4096,1000,54.09,209.9,121.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,8192,1000,81.92,300.41,177.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,16384,1000,132.53,523.3,277.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,32768,1000,216.01,850.76,409.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,65536,640,419.74,1502.18,989.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,131072,320,854.03,2164.06,1502.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,262144,160,2286.81,4328.67,3288.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,524288,80,5136.7,9133.09,7158.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,1048576,40,12049.58,18122.69,14974.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,2097152,20,24693.57,36789.8,30621.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,144,4194304,10,34211.23,58376.05,46194.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,54,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,1,1000,0.49,4.5,1.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,2,1000,0.51,4.82,1.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,4,1000,0.53,5.2,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,8,1000,0.57,5.99,1.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,16,1000,0.58,6.1,1.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,32,1000,0.57,6.98,1.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,64,1000,0.6,7.93,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,128,1000,0.6,10.13,1.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,256,1000,0.62,10.72,2.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,512,1000,0.84,14.34,2.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,1024,1000,0.86,22.46,3.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,2048,1000,0.95,39.98,4.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,4096,1000,1.31,64.96,7.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,8192,1000,1.88,102.68,12.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,16384,1000,8.52,161.41,18.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,32768,1000,17.05,256.78,37.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,65536,640,11.08,418.7,36.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,131072,320,12.38,747.27,48.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,262144,160,21.11,1413.47,85.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,524288,80,44.07,2754.48,173.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,1048576,40,165.07,5438.46,412.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,2097152,20,3506.59,11259.6,4310.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,4194304,10,14399.86,22090.87,15088.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,288,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,1,1000,0.98,5.94,4.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,2,1000,1.1,6.1,4.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,4,1000,1.09,6.17,4.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,8,1000,1.09,6.1,4.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,16,1000,1.1,6.0,4.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,32,1000,1.1,6.11,4.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,64,1000,1.12,6.17,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,128,1000,1.13,6.25,4.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,256,1000,1.25,6.67,5.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,512,1000,1.26,7.67,6.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,1024,1000,1.43,7.72,6.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,2048,1000,2.56,9.15,7.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,4096,1000,5.31,14.29,10.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,8192,1000,9.53,19.18,15.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,16384,1000,15.18,30.52,25.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,32768,1000,22.32,53.36,42.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,65536,640,49.83,86.16,74.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,131072,320,98.33,150.24,130.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,262144,160,199.37,254.29,232.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,524288,80,392.93,425.53,416.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,1048576,40,618.78,649.51,637.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,2097152,20,942.4,1141.88,1026.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,4194304,10,2158.67,2215.68,2180.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgatherv,36,0,1000,0.38,0.49,0.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,1,1000,4.43,5.12,4.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,2,1000,4.54,5.28,4.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,4,1000,4.78,5.62,5.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,8,1000,5.09,6.04,5.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,16,1000,5.72,6.9,6.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,32,1000,6.7,7.91,7.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,64,1000,16.2,17.98,16.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,128,1000,18.19,19.79,18.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,256,1000,22.63,23.63,23.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,512,1000,30.33,32.13,30.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,1024,1000,34.29,34.96,34.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,2048,1000,51.59,52.98,52.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,4096,1000,83.39,84.98,84.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,8192,1000,144.1,148.15,145.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,16384,1000,198.21,200.68,199.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,32768,1000,387.73,393.28,390.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,65536,640,767.39,782.89,776.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,131072,320,1536.13,1564.96,1553.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,262144,160,3122.22,3176.47,3145.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,524288,80,6267.39,6336.74,6307.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,1048576,40,15869.84,16018.92,15944.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,2097152,20,32365.81,32368.34,32366.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,4194304,10,65024.2,65026.95,65025.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,288,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,1,1000,0.95,4.03,3.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,2,1000,1.13,5.58,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,4,1000,1.14,5.8,4.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,8,1000,1.1,5.78,4.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,16,1000,1.1,5.71,4.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,32,1000,1.13,5.75,4.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,64,1000,1.13,5.78,4.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,128,1000,1.15,5.9,4.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,256,1000,1.24,6.33,5.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,512,1000,1.28,6.33,4.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,1024,1000,1.15,5.39,4.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,2048,1000,2.1,6.56,4.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,4096,1000,4.27,10.08,7.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,8192,1000,7.29,14.93,12.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,16384,1000,12.29,25.63,22.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,32768,1000,18.71,45.9,38.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,65536,640,36.84,62.66,54.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,131072,320,69.43,109.51,96.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,262144,160,148.7,193.26,178.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,524288,80,308.19,342.27,328.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,1048576,40,625.56,663.83,647.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,2097152,20,1167.96,1207.99,1196.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Bcast,288,4194304,10,2393.72,2423.93,2410.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,0,1000,3.54,9.98,3.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,1,1000,22.13,29.04,25.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,2,1000,23.81,30.62,27.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,4,1000,24.81,32.09,28.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,8,1000,27.06,40.9,33.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,16,1000,37.48,70.42,53.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,32,1000,46.61,64.15,57.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,64,1000,91.7,115.37,109.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,128,1000,104.74,144.96,136.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,256,1000,142.01,204.51,193.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,512,1000,244.32,327.84,302.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,1024,1000,385.21,421.69,415.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,2048,1000,503.48,535.66,524.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,4096,1000,763.15,840.47,805.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,8192,1000,1263.15,1373.42,1320.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,16384,1000,2412.21,2722.12,2575.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,32768,1000,4711.79,5484.23,5097.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,65536,640,8393.89,9907.83,9160.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,131072,320,16026.61,18130.9,17114.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,262144,160,29698.41,33663.19,31721.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,524288,80,62847.81,65244.29,64153.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,1048576,40,132688.94,136749.04,134395.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,2097152,20,306660.27,316368.21,310447.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgatherv,288,4194304,10,619138.39,635846.9,628187.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,72,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,1,1000,4.57,5.41,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,2,1000,4.75,5.74,5.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,4,1000,5.65,6.82,6.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,8,1000,6.19,7.5,6.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,16,1000,8.16,11.74,10.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,32,1000,7.18,9.97,7.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,64,1000,9.52,13.1,9.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,128,1000,11.31,14.38,11.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,256,1000,18.52,21.63,19.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,512,1000,67.43,69.93,68.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,1024,1000,55.6,60.34,56.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,2048,1000,108.09,110.86,109.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,4096,1000,170.52,173.91,171.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,8192,1000,297.85,300.99,299.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,16384,1000,427.57,437.7,432.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,32768,1000,837.44,897.78,868.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,65536,640,1626.41,1766.71,1698.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,131072,320,3267.6,3551.76,3417.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,262144,160,6549.49,7132.29,6849.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,524288,80,15611.73,16049.72,15816.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,1048576,40,33125.9,33991.46,33591.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,2097152,20,75253.12,78328.66,77081.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,72,4194304,10,154577.89,163078.48,158809.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,0,1000,0.75,1.84,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,1,1000,1.01,6.49,1.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,2,1000,1.04,6.51,1.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,4,1000,1.08,6.6,2.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,8,1000,1.14,6.82,2.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,16,1000,1.19,6.96,2.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,32,1000,0.99,6.43,1.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,64,1000,1.02,6.42,1.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,128,1000,1.01,6.51,1.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,256,1000,1.02,7.02,1.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,512,1000,1.45,9.95,2.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,1024,1000,1.83,11.75,3.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,2048,1000,2.39,15.4,3.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,4096,1000,3.73,22.78,5.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,8192,1000,5.18,36.96,8.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,16384,1000,22.88,62.9,43.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,32768,1000,27.15,112.53,71.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,65536,640,47.11,153.44,103.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,131072,320,95.36,280.99,184.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,262144,160,65.89,525.8,119.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,524288,80,689.39,1018.42,865.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,1048576,40,1605.8,1935.3,1783.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,2097152,20,3503.03,3834.0,3682.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,18,4194304,10,7657.94,8001.44,7849.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,0,1000,1.87,3.3,2.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,1,1000,4.13,5.92,5.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,2,1000,4.47,6.53,5.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,4,1000,5.11,7.71,6.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,8,1000,5.16,7.78,6.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,16,1000,5.36,7.91,6.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,32,1000,5.76,8.24,7.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,64,1000,4.76,6.67,5.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,128,1000,5.18,7.47,6.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,256,1000,2.54,15.31,7.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,512,1000,7.43,10.43,8.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,1024,1000,9.01,13.09,11.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,2048,1000,3.57,47.44,25.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,4096,1000,5.33,85.01,45.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,8192,1000,21.08,159.76,103.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,16384,1000,26.51,202.12,145.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,32768,1000,35.12,346.54,268.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,65536,640,53.33,612.29,505.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,131072,320,84.5,1048.15,855.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,262144,160,163.56,2021.36,1651.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,524288,80,288.84,4174.53,3666.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,1048576,40,645.59,8226.37,7289.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,2097152,20,751.67,9464.62,8091.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,54,4194304,10,1513.7,16676.8,14386.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,0,1000,0.05,0.05,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,4,1000,0.26,0.96,0.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,8,1000,0.26,0.97,0.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,16,1000,0.27,1.02,0.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,32,1000,0.27,1.03,0.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,64,1000,0.27,1.32,0.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,128,1000,0.28,1.38,0.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,256,1000,0.28,1.57,0.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,512,1000,0.28,1.66,0.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,1024,1000,0.3,2.11,0.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,2048,1000,0.41,3.08,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,4096,1000,0.87,4.93,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,8192,1000,1.85,8.69,2.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,16384,1000,6.05,15.57,10.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,32768,1000,11.27,25.59,17.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,65536,640,20.79,40.98,31.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,131072,320,39.98,70.44,55.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,262144,160,78.93,132.91,105.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,524288,80,113.79,177.91,144.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,1048576,40,224.67,328.14,275.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,2097152,20,480.55,646.19,548.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,18,4194304,10,965.19,1268.62,1090.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,0,1000,0.36,0.47,0.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,4,1000,0.69,4.35,1.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,8,1000,0.7,4.41,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,16,1000,0.72,4.73,1.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,32,1000,0.84,4.82,1.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,64,1000,0.93,5.68,2.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,128,1000,2.75,6.14,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,256,1000,4.8,6.35,5.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,512,1000,5.49,7.01,6.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,1024,1000,6.69,8.51,7.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,2048,1000,7.2,9.1,7.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,4096,1000,8.75,10.84,9.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,8192,1000,12.0,14.8,12.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,16384,1000,17.87,21.09,18.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,32768,1000,45.55,66.48,55.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,65536,640,70.95,93.9,82.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,131072,320,171.08,214.82,189.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,262144,160,204.96,270.93,247.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,524288,80,371.53,459.23,428.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,1048576,40,508.38,637.76,593.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,2097152,20,910.66,1056.43,1007.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,36,4194304,10,1922.08,2095.45,2019.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,144,0,1000,2.18,5.94,2.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,1,1000,13.66,19.16,16.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,2,1000,14.44,21.03,17.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,4,1000,14.45,22.13,17.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,8,1000,19.74,27.15,22.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,16,1000,32.06,43.6,36.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,32,1000,22.5,33.92,28.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,64,1000,23.89,43.7,35.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,128,1000,77.66,99.1,93.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,256,1000,90.45,125.72,118.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,512,1000,128.96,186.44,176.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,1024,1000,221.24,283.55,267.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,2048,1000,254.35,278.08,274.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,4096,1000,357.62,416.94,386.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,8192,1000,580.93,661.46,620.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,16384,1000,1054.46,1339.76,1199.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,32768,1000,2039.88,2676.89,2371.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,65536,640,3828.29,5077.08,4477.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,131072,320,7000.55,8842.1,8001.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,262144,160,13367.89,16530.05,15027.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,524288,80,30837.83,32279.87,31561.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,1048576,40,65475.5,73366.48,69414.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,2097152,20,151005.98,156322.13,153875.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,144,4194304,10,306306.41,320572.19,313688.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,72,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,1,1000,4.65,5.67,4.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,2,1000,4.93,6.23,5.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,4,1000,5.43,6.56,5.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,8,1000,5.46,6.37,5.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,16,1000,6.42,8.64,8.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,32,1000,7.4,10.24,7.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,64,1000,9.02,12.32,9.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,128,1000,11.35,14.42,11.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,256,1000,18.39,21.56,18.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,512,1000,70.53,73.44,72.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,1024,1000,55.23,59.57,56.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,2048,1000,116.43,119.59,118.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,4096,1000,170.56,174.1,172.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,8192,1000,295.9,300.97,297.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,16384,1000,422.55,432.72,428.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,32768,1000,829.63,886.6,858.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,65536,640,1586.65,1741.74,1671.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,131072,320,3177.35,3463.83,3329.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,262144,160,6454.28,7135.96,6796.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,524288,80,15446.82,15942.52,15662.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,1048576,40,32868.26,33961.77,33501.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,2097152,20,74520.25,78304.39,77080.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,72,4194304,10,153120.23,159342.41,156963.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,0,1000,0.79,1.92,1.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,1,1000,1.05,6.41,2.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,2,1000,1.08,6.45,2.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,4,1000,1.12,6.59,2.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,8,1000,1.19,7.15,2.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,16,1000,1.26,7.23,2.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,32,1000,1.25,6.75,2.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,64,1000,1.24,6.72,2.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,128,1000,1.24,6.78,2.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,256,1000,1.26,6.86,2.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,512,1000,2.0,10.3,3.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,1024,1000,2.49,11.49,3.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,2048,1000,2.82,14.79,4.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,4096,1000,4.68,21.34,6.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,8192,1000,6.51,32.66,9.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,16384,1000,50.95,57.07,54.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,32768,1000,87.2,99.55,93.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,65536,640,65.25,150.01,111.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,131072,320,82.7,267.03,173.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,262144,160,22.45,505.17,85.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,524288,80,597.87,938.45,787.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,1048576,40,1578.95,1953.22,1796.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,2097152,20,3445.62,3809.56,3658.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,18,4194304,10,7319.1,7658.02,7505.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,216,0,1000,2.28,8.85,6.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,1,1000,29.65,138.7,85.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,2,1000,30.21,137.33,84.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,4,1000,28.34,137.58,84.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,8,1000,30.31,142.67,85.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,16,1000,30.42,137.69,85.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,32,1000,30.03,139.57,86.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,64,1000,31.2,145.68,88.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,128,1000,31.23,147.36,88.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,256,1000,31.21,149.47,90.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,512,1000,37.16,164.92,98.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,1024,1000,49.24,205.03,123.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,2048,1000,67.28,279.5,166.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,4096,1000,76.23,318.39,187.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,8192,1000,88.73,429.91,253.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,16384,1000,125.04,723.16,369.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,32768,1000,184.21,1281.56,550.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,65536,640,347.06,1619.09,1065.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,131072,320,685.47,2961.95,2005.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,262144,160,2011.45,5863.92,4411.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,524288,80,4746.39,12418.4,9722.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,1048576,40,11965.1,24623.07,20042.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,2097152,20,24790.42,49887.6,41135.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,216,4194304,10,35004.08,85648.38,68330.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,72,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,4,1000,2.82,5.08,3.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,8,1000,3.31,4.34,3.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,16,1000,3.61,4.89,4.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,32,1000,3.8,5.08,4.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,64,1000,3.69,6.67,4.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,128,1000,4.39,7.62,4.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,256,1000,6.5,9.77,7.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,512,1000,7.72,10.78,8.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,1024,1000,5.86,8.01,6.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,2048,1000,6.14,8.39,6.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,4096,1000,9.4,20.72,10.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,8192,1000,17.07,19.82,17.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,16384,1000,24.62,28.73,27.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,32768,1000,40.69,48.77,42.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,65536,640,74.35,88.84,78.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,131072,320,116.54,125.82,121.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,262144,160,185.31,188.89,187.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,524288,80,349.82,361.95,355.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,1048576,40,657.94,698.35,679.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,2097152,20,1064.74,1151.45,1104.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,4194304,10,2066.97,2289.36,2191.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,144,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,1,1000,32.67,37.9,35.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,2,1000,36.55,56.31,46.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,4,1000,34.97,42.37,38.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,8,1000,38.48,47.26,42.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,16,1000,41.82,51.83,47.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,32,1000,51.09,66.5,59.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,64,1000,63.06,87.74,77.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,128,1000,90.79,123.31,112.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,256,1000,143.36,212.38,190.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,512,1000,444.42,499.34,474.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,1024,1000,461.48,505.02,493.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,2048,1000,850.47,951.79,921.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,4096,1000,1671.67,1974.53,1863.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,8192,1000,3636.27,3666.25,3648.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,16384,1000,7564.12,7625.84,7588.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,32768,689,14496.35,14620.79,14546.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,65536,354,28114.52,28210.26,28167.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,131072,174,57010.87,57652.04,57284.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,262144,90,111959.97,112178.23,112083.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,524288,45,223696.64,225248.16,224544.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,1048576,23,445540.14,446709.48,446132.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,2097152,9,887821.12,889798.97,889087.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Alltoall,144,4194304,5,1775970.06,1781130.27,1778560.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,1,1000,2.32,5.38,4.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,2,1000,0.63,4.83,4.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,4,1000,0.67,4.88,4.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,8,1000,0.64,4.85,4.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,16,1000,0.63,4.84,4.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,32,1000,0.63,4.87,4.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,64,1000,0.64,5.76,4.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,128,1000,0.67,5.06,4.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,256,1000,0.76,6.45,4.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,512,1000,0.77,5.95,5.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,1024,1000,0.96,6.5,5.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,2048,1000,1.63,7.54,6.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,4096,1000,3.22,10.86,8.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,8192,1000,7.31,16.68,12.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,16384,1000,12.2,25.59,21.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,32768,1000,19.1,43.67,36.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,65536,640,40.57,70.28,61.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,131072,320,83.19,121.66,107.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,262144,160,164.35,197.31,187.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,524288,80,331.0,377.09,357.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,1048576,40,502.41,521.66,515.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,2097152,20,794.73,843.78,824.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Bcast,144,4194304,10,3304.36,3696.15,3449.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatter,144,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,1,1000,2.79,6.91,5.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,2,1000,1.23,4.98,3.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,4,1000,3.08,7.96,5.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,8,1000,3.18,8.23,6.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,16,1000,1.74,7.89,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,32,1000,2.56,7.2,4.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,64,1000,5.58,11.12,8.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,128,1000,7.63,15.46,12.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,256,1000,9.67,22.76,17.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,512,1000,11.53,41.56,30.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,1024,1000,16.14,56.03,44.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,2048,1000,25.77,107.12,90.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,4096,1000,32.85,185.23,163.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,8192,1000,54.38,339.68,290.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,16384,1000,95.5,562.06,460.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,32768,1000,39.3,568.86,264.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,65536,640,35.3,425.19,247.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,131072,320,46.63,806.68,432.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,262144,160,537.32,1589.99,1390.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,524288,80,227.06,3147.19,2738.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,1048576,40,3673.63,6271.73,5882.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,2097152,20,791.8,14087.15,12441.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,144,4194304,10,19984.35,25686.21,24996.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gatherv,54,0,1000,1.87,3.4,2.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,1,1000,6.51,27.51,15.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,2,1000,6.99,31.4,17.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,4,1000,6.91,31.23,17.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,8,1000,6.94,31.28,17.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,16,1000,6.87,31.43,17.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,32,1000,6.51,26.66,15.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,64,1000,6.48,26.72,15.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,128,1000,6.68,26.89,15.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,256,1000,6.59,24.97,14.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,512,1000,8.54,29.06,17.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,1024,1000,11.82,42.06,25.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,2048,1000,12.75,48.13,27.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,4096,1000,14.92,78.99,45.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,8192,1000,62.03,128.52,91.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,16384,1000,38.83,183.66,106.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,32768,1000,62.15,272.83,164.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,65536,640,97.84,433.99,246.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,131072,320,167.76,782.04,431.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,262144,160,309.88,1485.66,813.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,524288,80,1685.16,2873.25,2333.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,1048576,40,4356.57,5570.88,5030.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,2097152,20,10057.27,11237.11,10696.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,54,4194304,10,21024.88,22325.61,21782.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,4,1000,0.93,1.15,1.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,8,1000,0.97,1.15,1.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,16,1000,0.92,1.1,0.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,32,1000,0.94,1.14,1.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,64,1000,1.01,1.62,1.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,128,1000,1.3,1.92,1.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,256,1000,1.24,1.85,1.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,512,1000,1.66,2.27,1.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,1024,1000,2.23,2.96,2.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,2048,1000,4.06,5.2,4.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,4096,1000,5.11,6.61,5.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,8192,1000,8.68,9.91,9.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,16384,1000,16.04,17.5,17.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,32768,1000,29.59,29.99,29.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,65536,640,45.21,46.59,45.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,131072,320,85.76,88.84,87.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,262144,160,167.73,175.21,172.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,524288,80,323.35,328.73,325.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,1048576,40,662.5,681.34,674.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,2097152,20,940.76,1004.21,981.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,18,4194304,10,1946.12,2059.94,2015.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,1,1000,1.31,3.2,2.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,2,1000,1.39,3.38,2.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,4,1000,1.51,3.6,2.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,8,1000,1.65,3.97,2.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,16,1000,1.9,4.46,3.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,32,1000,1.72,3.8,2.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,64,1000,2.99,4.9,3.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,128,1000,4.35,6.89,5.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,256,1000,5.69,8.61,7.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,512,1000,5.83,10.06,7.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,1024,1000,8.84,15.45,12.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,2048,1000,15.06,25.99,21.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,4096,1000,26.33,44.42,37.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,8192,1000,40.18,64.3,56.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,16384,1000,58.63,97.59,84.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,32768,1000,22.33,328.71,245.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,65536,640,40.74,559.34,434.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,131072,320,498.5,806.77,724.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,262144,160,169.1,2056.73,1754.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,524288,80,311.32,4198.4,3743.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,1048576,40,637.38,8182.68,7423.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,2097152,20,763.52,9084.03,7669.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,54,4194304,10,1618.57,28029.86,22868.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,0,1000,1.11,2.89,2.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,1,1000,1.84,10.78,3.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,2,1000,1.9,11.52,4.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,4,1000,2.0,12.37,4.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,8,1000,1.85,11.14,4.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,16,1000,2.15,13.62,4.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,32,1000,1.92,13.02,4.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,64,1000,1.93,13.42,4.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,128,1000,1.78,15.53,4.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,256,1000,1.77,18.43,4.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,512,1000,1.94,27.07,4.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,1024,1000,11.2,53.5,30.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,2048,1000,18.21,83.45,43.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,4096,1000,32.42,116.26,64.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,8192,1000,42.62,160.57,95.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,16384,1000,74.18,271.54,167.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,32768,1000,80.99,346.37,195.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,65536,640,111.1,567.59,304.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,131072,320,187.42,1115.41,583.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,262144,160,323.42,1968.86,1032.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,524288,80,2177.0,3837.88,3089.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,1048576,40,5876.8,7624.5,6873.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,2097152,20,13727.89,15396.23,14648.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,72,4194304,10,28587.74,30358.55,29607.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,1,1000,1.34,3.25,2.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,2,1000,1.41,3.38,2.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,4,1000,1.54,3.62,2.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,8,1000,1.67,4.06,2.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,16,1000,1.83,4.28,3.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,32,1000,2.15,4.68,3.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,64,1000,3.71,6.27,4.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,128,1000,5.25,9.26,7.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,256,1000,7.82,11.82,9.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,512,1000,7.42,13.37,10.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,1024,1000,11.27,18.94,15.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,2048,1000,19.97,31.16,25.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,4096,1000,31.63,48.29,41.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,8192,1000,56.32,85.11,74.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,16384,1000,90.34,140.25,126.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,32768,1000,10.6,298.31,224.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,65536,640,10.07,518.43,407.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,131072,320,486.05,774.16,664.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,262144,160,37.28,1880.08,1558.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,524288,80,94.11,3786.18,3388.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,1048576,40,537.7,7777.16,6979.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,2097152,20,744.7,9114.47,8019.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,54,4194304,10,2639.23,65354.38,60877.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,1,1000,0.8,1.92,1.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,2,1000,0.8,1.73,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,4,1000,0.79,1.71,1.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,8,1000,0.8,1.76,1.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,16,1000,0.84,1.72,1.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,32,1000,0.85,1.59,1.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,64,1000,0.88,1.67,1.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,128,1000,0.89,2.23,1.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,256,1000,1.06,2.77,2.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,512,1000,1.19,4.78,3.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,1024,1000,1.59,5.95,4.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,2048,1000,2.27,7.72,5.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,4096,1000,3.18,11.6,8.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,8192,1000,6.38,30.37,22.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,16384,1000,9.93,42.46,33.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,32768,1000,16.51,61.87,42.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,65536,640,25.11,75.74,51.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,131072,320,42.59,109.39,81.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,262144,160,82.95,202.11,155.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,524288,80,166.03,410.21,319.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,1048576,40,323.57,1395.39,1167.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,2097152,20,689.96,2762.97,2414.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,18,4194304,10,1418.52,5702.49,4978.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,4,1000,0.27,1.01,0.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,8,1000,0.27,1.0,0.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,16,1000,0.27,1.0,0.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,32,1000,0.27,1.05,0.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,64,1000,0.28,1.33,0.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,128,1000,0.27,1.47,0.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,256,1000,0.28,1.65,0.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,512,1000,0.28,1.89,0.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,1024,1000,0.3,2.57,0.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,2048,1000,0.33,3.65,0.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,4096,1000,0.35,5.66,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,8192,1000,1.01,9.36,2.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,16384,1000,4.66,16.89,10.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,32768,1000,9.35,26.32,17.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,65536,640,19.37,43.74,34.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,131072,320,41.15,78.22,65.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,262144,160,81.35,144.13,126.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,524288,80,201.36,222.58,211.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,1048576,40,205.64,225.63,215.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,2097152,20,391.98,440.36,410.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,18,4194304,10,799.65,1099.45,899.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,216,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,1,1000,12.29,19.33,15.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,2,1000,16.49,28.89,20.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,4,1000,15.82,24.3,19.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,8,1000,15.45,25.5,18.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,16,1000,17.78,37.58,24.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,32,1000,16.85,27.54,23.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,64,1000,42.72,74.73,61.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,128,1000,39.61,65.34,60.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,256,1000,74.48,125.42,118.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,512,1000,158.94,209.47,199.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,1024,1000,290.77,403.3,370.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,2048,1000,381.42,469.86,431.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,4096,1000,671.86,776.9,745.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,8192,1000,914.79,1012.52,964.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,16384,1000,1718.04,2013.97,1864.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,32768,1000,3389.34,4044.64,3721.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,65536,640,6208.81,8230.13,7285.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,131072,320,11452.11,15998.56,13588.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,262144,160,21838.63,33326.88,26870.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,524288,80,44570.06,45835.53,45231.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,1048576,40,105279.48,108441.96,106719.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,2097152,20,227095.29,234432.46,230826.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgather,216,4194304,10,472641.14,489730.32,480854.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,54,0,1000,1.78,3.21,2.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,1,1000,3.95,5.47,4.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,2,1000,4.1,5.79,5.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,4,1000,4.43,6.56,5.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,8,1000,5.03,7.93,6.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,16,1000,5.25,7.96,6.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,32,1000,5.59,8.17,6.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,64,1000,5.86,8.78,7.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,128,1000,6.78,10.85,8.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,256,1000,2.88,22.46,11.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,512,1000,8.45,14.73,11.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,1024,1000,9.96,17.86,14.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,2048,1000,3.24,64.05,32.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,4096,1000,3.74,95.16,49.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,8192,1000,20.72,145.88,101.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,16384,1000,22.2,198.53,142.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,32768,1000,8.38,309.76,238.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,65536,640,13.19,516.54,403.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,131072,320,18.67,959.83,780.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,262144,160,28.99,1885.63,1593.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,524288,80,84.99,4031.15,3652.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,1048576,40,504.89,7992.91,7268.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,2097152,20,811.47,9881.45,8673.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,54,4194304,10,1416.52,16190.59,14045.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,288,0,1000,1.07,1.55,1.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,4,1000,1.43,12.16,2.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,8,1000,1.42,14.42,2.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,16,1000,1.46,20.28,3.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,32,1000,1.58,19.31,5.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,64,1000,1.59,19.99,6.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,128,1000,1.62,21.69,7.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,256,1000,2.72,21.82,8.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,512,1000,2.82,26.31,12.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,1024,1000,9.24,28.27,21.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,2048,1000,30.46,46.91,36.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,4096,1000,44.22,60.47,50.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,8192,1000,63.17,116.93,75.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,16384,1000,90.15,114.66,102.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,32768,1000,169.39,199.12,186.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,65536,640,387.08,467.8,418.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,131072,320,242.58,411.28,333.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,262144,160,576.04,681.41,616.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,524288,80,867.24,992.25,919.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,1048576,40,1484.4,1624.03,1540.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,2097152,20,2814.55,2991.12,2888.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,4194304,10,3574.13,4133.24,3849.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,144,0,1000,0.78,0.88,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,4,1000,1.08,13.69,3.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,8,1000,1.08,13.52,3.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,16,1000,1.08,13.81,3.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,32,1000,1.09,14.41,4.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,64,1000,1.11,16.13,5.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,128,1000,1.73,19.9,7.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,256,1000,1.87,22.16,11.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,512,1000,6.34,20.43,15.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,1024,1000,13.68,23.86,18.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,2048,1000,17.12,29.85,23.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,4096,1000,26.32,36.0,31.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,8192,1000,35.72,51.42,43.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,16384,1000,59.6,104.38,77.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,32768,1000,114.4,179.2,139.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,65536,640,157.18,235.1,188.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,131072,320,224.49,357.89,292.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,262144,160,507.38,596.42,543.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,524288,80,762.91,881.91,810.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,1048576,40,1360.5,1530.39,1431.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,2097152,20,9253.98,15423.68,9451.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce_scatter,144,4194304,10,4284.12,4996.03,4679.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,288,0,1000,0.04,0.09,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,1,1000,14.3,20.92,17.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,2,1000,15.98,24.63,19.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,4,1000,17.32,25.96,21.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,8,1000,18.92,29.86,23.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,16,1000,23.27,41.78,31.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,32,1000,26.46,39.38,35.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,64,1000,73.03,100.33,91.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,128,1000,59.54,102.54,92.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,256,1000,100.06,172.03,155.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,512,1000,199.42,280.12,257.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,1024,1000,344.38,379.04,372.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,2048,1000,546.76,577.33,567.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,4096,1000,995.54,1027.38,1016.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,8192,1000,1246.8,1374.24,1311.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,16384,1000,2479.05,2889.67,2687.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,32768,1000,4636.88,5350.01,5015.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,65536,640,9272.57,10804.02,10060.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,131072,320,16511.03,21165.86,18520.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,262144,160,31146.13,43876.89,36099.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,524288,80,60797.87,62481.9,61484.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,1048576,40,130886.16,137854.74,133479.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,2097152,20,303491.0,312237.71,308269.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,4194304,10,621139.06,644515.45,633015.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,216,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,4,1000,6.56,10.42,8.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,8,1000,6.51,10.31,8.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,16,1000,10.11,14.58,12.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,32,1000,9.94,17.45,14.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,64,1000,12.67,19.36,15.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,128,1000,9.59,16.75,12.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,256,1000,10.03,17.64,13.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,512,1000,8.79,14.42,10.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,1024,1000,15.08,21.65,17.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,2048,1000,13.11,17.8,14.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,4096,1000,16.8,21.8,18.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,8192,1000,32.95,38.52,34.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,16384,1000,76.9,92.41,82.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,32768,1000,86.13,111.72,94.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,65536,640,93.16,124.33,102.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,131072,320,154.52,199.65,169.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,262144,160,297.4,372.56,325.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,524288,80,705.19,853.57,760.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,1048576,40,1677.98,1735.64,1697.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,2097152,20,3046.24,3082.65,3074.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allreduce,216,4194304,10,5274.32,5311.45,5299.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,18,0,1000,0.63,1.45,1.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,1,1000,1.89,2.66,2.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,2,1000,1.87,2.75,2.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,4,1000,1.77,2.57,2.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,8,1000,1.86,2.68,2.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,16,1000,1.84,2.66,2.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,32,1000,1.9,2.69,2.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,64,1000,1.86,2.76,2.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,128,1000,1.31,3.63,2.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,256,1000,1.39,3.83,2.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,512,1000,2.45,4.64,3.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,1024,1000,1.72,6.99,4.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,2048,1000,2.19,10.01,5.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,4096,1000,3.04,14.47,8.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,8192,1000,5.28,22.29,16.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,16384,1000,7.72,31.45,24.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,32768,1000,12.52,37.06,25.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,65536,640,22.03,60.59,43.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,131072,320,40.73,106.44,79.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,262144,160,77.81,200.71,154.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,524288,80,162.66,393.44,307.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,1048576,40,326.17,799.69,626.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,2097152,20,683.08,2505.25,2133.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,4194304,10,1656.46,5075.47,4351.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,144,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,4,1000,4.88,8.42,6.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,8,1000,4.82,8.52,6.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,16,1000,4.73,8.3,6.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,32,1000,4.56,8.33,6.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,64,1000,6.54,12.19,9.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,128,1000,7.4,16.0,11.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,256,1000,12.24,22.83,17.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,512,1000,14.7,23.11,17.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,1024,1000,11.72,18.24,14.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,2048,1000,11.43,15.88,13.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,4096,1000,13.44,19.29,15.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,8192,1000,30.41,36.98,32.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,16384,1000,63.29,70.76,66.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,32768,1000,47.36,58.99,51.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,65536,640,80.14,96.5,85.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,131072,320,136.48,160.22,144.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,262144,160,241.59,284.86,256.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,524288,80,840.16,968.35,877.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,1048576,40,1466.96,1541.03,1499.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,2097152,20,2623.46,2819.7,2715.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allreduce,144,4194304,10,5267.66,5293.59,5282.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,1,1000,1.27,8.73,4.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,2,1000,1.28,8.42,4.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,4,1000,1.27,9.49,5.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,8,1000,1.24,9.43,5.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,16,1000,2.45,11.25,6.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,32,1000,3.72,13.19,8.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,64,1000,5.22,16.07,10.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,128,1000,9.2,19.66,14.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,256,1000,14.16,27.04,21.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,512,1000,24.9,44.05,33.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,1024,1000,34.92,69.75,53.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,2048,1000,51.25,111.96,87.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,4096,1000,76.03,190.63,151.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,8192,1000,127.01,409.32,283.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,16384,1000,226.04,674.2,500.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,32768,1000,27.18,1081.93,637.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,65536,640,24.69,820.92,472.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,131072,320,58.23,1582.9,909.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,262144,160,76.76,3114.92,2263.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,524288,80,115.47,6189.49,4728.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,1048576,40,2826.37,12434.96,9890.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,2097152,20,6836.99,24888.6,20057.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,216,4194304,10,4199.15,50635.78,38388.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,0,1000,2.92,8.7,3.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,1,1000,18.41,24.37,21.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,2,1000,20.54,39.27,28.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,4,1000,24.99,40.14,32.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,8,1000,21.96,29.8,25.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,16,1000,27.81,37.25,32.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,32,1000,37.7,56.52,46.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,64,1000,73.44,87.68,82.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,128,1000,85.29,107.42,100.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,256,1000,113.38,152.06,142.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,512,1000,165.42,207.02,194.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,1024,1000,260.68,346.81,313.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,2048,1000,450.69,512.78,491.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,4096,1000,546.0,649.93,595.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,8192,1000,989.27,1262.87,1111.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,16384,1000,1526.63,1767.39,1652.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,32768,1000,3280.69,4019.51,3666.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,65536,640,6030.7,7335.6,6681.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,131072,320,11981.42,14172.74,13069.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,262144,160,21744.65,25325.4,23636.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,524288,80,48255.04,49475.64,48863.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,1048576,40,100725.52,102921.89,102169.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,2097152,20,227099.21,235199.28,230508.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgatherv,216,4194304,10,461066.89,483249.35,472296.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,54,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,1,1000,14.05,14.64,14.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,2,1000,15.4,16.61,15.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,4,1000,16.35,17.19,16.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,8,1000,16.81,17.79,17.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,16,1000,16.3,16.87,16.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,32,1000,20.39,22.94,21.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,64,1000,21.44,23.87,22.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,128,1000,26.13,28.24,27.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,256,1000,35.34,37.55,36.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,512,1000,58.82,66.85,62.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,1024,1000,83.55,92.68,88.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,2048,1000,142.57,145.12,143.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,4096,1000,249.04,252.85,251.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,8192,1000,427.69,477.92,450.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,16384,1000,890.79,908.45,902.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,32768,1000,1787.06,1808.57,1798.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,65536,640,2441.74,2467.99,2455.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,131072,320,4560.1,4642.01,4613.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,262144,160,9312.37,9397.32,9352.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,524288,80,15717.56,15838.33,15780.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,1048576,40,31610.05,31814.68,31700.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,2097152,20,61570.08,62032.81,61885.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,54,4194304,10,122949.09,128739.41,125925.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,288,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,1,1000,61.43,70.49,64.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,2,1000,62.29,72.77,65.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,4,1000,69.11,79.42,72.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,8,1000,74.59,93.36,81.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,16,1000,109.0,139.18,125.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,32,1000,104.25,121.08,114.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,64,1000,178.57,199.37,190.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,128,1000,313.3,366.68,347.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,256,1000,860.65,883.67,869.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,512,1000,1199.5,1225.79,1209.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,1024,1000,2143.04,2203.87,2169.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,2048,1000,3456.07,3509.01,3483.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,4096,1000,6705.56,6728.0,6716.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,8192,830,12227.34,12269.05,12246.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,16384,436,23404.73,23501.12,23454.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,32768,213,46353.14,46535.69,46445.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,65536,6,102239.28,105437.92,103715.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,131072,6,177460.06,178181.38,177835.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,262144,6,364168.47,365989.13,365045.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,524288,6,716622.6,719392.93,718110.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,1048576,5,1412359.97,1417948.39,1415322.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,288,2097152,3,2824447.07,2836912.31,2830828.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,54,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,1,1000,3.99,4.89,4.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,2,1000,4.02,4.94,4.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,4,1000,4.04,4.95,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,8,1000,4.1,5.09,4.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,16,1000,4.74,6.19,5.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,32,1000,5.1,6.63,5.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,64,1000,6.1,8.02,6.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,128,1000,7.52,10.43,8.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,256,1000,10.96,15.33,13.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,512,1000,18.35,25.85,21.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,1024,1000,38.17,42.16,39.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,2048,1000,63.27,68.74,65.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,4096,1000,114.32,132.48,119.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,8192,1000,207.78,230.42,218.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,16384,1000,296.02,331.17,319.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,32768,1000,578.31,672.14,628.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,65536,640,1132.36,1282.08,1213.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,131072,320,2310.05,2577.14,2457.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,262144,160,4806.13,5350.31,5088.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,524288,80,11449.71,12263.71,11979.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,1048576,40,24220.19,25598.3,25083.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,2097152,20,54931.87,59479.87,57991.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,4194304,10,113085.77,120184.32,117993.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,1,1000,0.35,2.94,0.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,2,1000,0.35,2.88,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,4,1000,0.35,2.96,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,8,1000,0.36,3.05,0.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,16,1000,0.35,3.12,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,32,1000,0.35,3.41,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,64,1000,0.37,4.19,0.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,128,1000,0.39,4.95,1.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,256,1000,0.4,6.25,1.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,512,1000,0.55,7.48,1.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,1024,1000,1.79,20.11,2.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,2048,1000,2.52,26.64,3.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,4096,1000,3.99,39.51,6.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,8192,1000,7.4,69.1,10.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,16384,1000,5.8,110.93,18.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,32768,1000,9.32,207.01,32.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,65536,640,20.79,291.54,42.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,131072,320,36.72,544.36,65.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,262144,160,74.48,1059.61,123.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,524288,80,156.58,2021.71,240.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,1048576,40,321.42,3605.67,473.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,2097152,20,2436.17,7158.23,2859.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,36,4194304,10,9693.07,14469.51,10105.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,288,0,1000,2.7,11.01,5.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,1,1000,34.44,231.41,153.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,2,1000,34.51,230.78,152.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,4,1000,33.93,230.95,152.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,8,1000,34.42,232.39,153.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,16,1000,33.96,229.5,151.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,32,1000,34.86,237.01,157.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,64,1000,34.07,246.67,164.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,128,1000,34.47,240.45,160.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,256,1000,34.41,243.58,163.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,512,1000,39.97,286.33,196.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,1024,1000,49.37,346.15,244.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,2048,1000,66.16,442.44,318.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,4096,1000,59.36,509.7,371.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,8192,1000,101.39,666.51,500.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,16384,1000,110.65,1087.31,826.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,32768,1000,172.14,1796.85,1365.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,65536,640,317.73,2183.92,1283.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,131072,320,608.33,3821.54,2206.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,262144,160,1923.34,7494.22,4467.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,524288,80,4404.52,15476.46,9488.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,1048576,40,12047.51,30650.96,19341.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,2097152,20,25064.4,62287.08,39642.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,4194304,10,34346.16,108214.48,63181.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gatherv,288,0,1000,2.68,9.68,5.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,1,1000,32.73,212.61,143.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,2,1000,33.51,211.54,142.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,4,1000,33.71,212.69,142.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,8,1000,33.16,212.99,143.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,16,1000,32.93,224.15,144.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,32,1000,34.13,215.6,146.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,64,1000,34.12,235.85,159.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,128,1000,34.84,242.88,165.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,256,1000,35.11,247.69,169.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,512,1000,47.48,282.87,197.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,1024,1000,59.07,359.34,249.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,2048,1000,71.23,436.61,321.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,4096,1000,79.4,487.55,361.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,8192,1000,107.96,650.34,492.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,16384,1000,153.3,1063.91,812.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,32768,1000,254.69,1916.99,1462.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,65536,640,419.07,2514.97,1443.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,131072,320,696.08,4054.88,2416.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,262144,160,1630.49,8033.07,4848.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,524288,80,4732.92,15395.96,9492.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,1048576,40,11928.22,30425.25,19217.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,2097152,20,24838.95,61610.1,39224.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Gatherv,288,4194304,10,34288.31,107660.02,62942.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,216,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,4,1000,0.39,18.96,0.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,8,1000,0.35,13.01,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,16,1000,0.36,9.37,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,32,1000,0.36,10.72,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,64,1000,0.35,12.08,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,128,1000,0.34,13.18,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,256,1000,0.35,12.14,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,512,1000,0.35,13.46,0.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,1024,1000,0.36,16.1,1.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,2048,1000,0.37,19.7,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,4096,1000,0.38,21.94,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,8192,1000,2.35,32.18,4.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,16384,1000,6.55,43.87,12.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,32768,1000,11.47,87.09,43.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,65536,640,25.39,173.02,88.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,131072,320,59.87,224.79,136.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,262144,160,49.81,544.09,259.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,524288,80,95.7,795.2,396.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,1048576,40,214.63,1275.61,670.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,2097152,20,488.13,1770.68,1500.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,216,4194304,10,693.42,3958.24,2030.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce,288,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,4,1000,0.35,7.92,0.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,8,1000,0.33,9.41,0.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,16,1000,0.35,14.04,0.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,32,1000,0.35,10.49,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,64,1000,0.36,10.76,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,128,1000,0.35,11.04,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,256,1000,0.34,12.36,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,512,1000,0.31,10.43,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,1024,1000,0.34,16.02,0.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,2048,1000,0.41,12.63,1.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,4096,1000,0.73,16.04,1.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,8192,1000,2.67,29.69,4.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,16384,1000,7.26,37.6,11.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,32768,1000,40.01,153.29,102.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,65536,640,79.94,193.57,149.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,131072,320,157.57,332.12,270.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,262144,160,88.05,764.29,395.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,524288,80,133.38,870.94,477.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,1048576,40,220.52,1268.06,709.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,2097152,20,501.16,1881.63,1541.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce,288,4194304,10,693.91,3910.76,2142.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,72,0,1000,0.44,1.01,0.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,4,1000,1.04,6.45,2.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,8,1000,1.02,6.66,2.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,16,1000,1.08,7.69,2.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,32,1000,1.08,7.12,2.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,64,1000,1.27,7.48,3.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,128,1000,1.3,8.55,4.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,256,1000,3.35,10.05,7.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,512,1000,6.43,7.84,6.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,1024,1000,9.85,12.12,10.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,2048,1000,7.64,9.31,8.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,4096,1000,8.68,10.31,9.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,8192,1000,14.71,17.24,15.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,16384,1000,18.77,21.48,19.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,32768,1000,30.0,34.03,31.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,65536,640,52.63,59.15,54.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,131072,320,102.9,120.84,109.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,262144,160,197.64,219.05,206.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,524288,80,384.0,390.08,386.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,1048576,40,690.74,698.58,694.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,2097152,20,1274.57,1292.01,1282.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,72,4194304,10,2509.47,2563.89,2532.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,216,0,1000,7.77,14.8,11.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,1,1000,7.96,15.85,11.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,2,1000,7.97,16.13,11.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,4,1000,8.09,16.4,12.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,8,1000,7.4,15.53,11.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,16,1000,8.01,16.88,12.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,32,1000,8.17,16.59,11.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,64,1000,9.89,20.01,14.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,128,1000,11.51,22.4,16.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,256,1000,13.02,26.89,19.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,512,1000,19.72,44.97,33.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,1024,1000,18.92,56.22,39.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,2048,1000,22.31,83.59,59.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,4096,1000,14.0,156.98,95.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,8192,1000,40.16,289.85,169.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,16384,1000,49.53,517.55,290.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,32768,1000,59.67,929.02,529.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,65536,640,49.72,1034.54,658.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,131072,320,64.58,2065.06,1245.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,262144,160,372.6,6114.24,3658.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,524288,80,583.29,17571.28,10297.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,1048576,40,936.88,35429.37,20064.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,2097152,20,1846.58,79940.86,45886.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,216,4194304,10,4173.44,155721.24,90187.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,288,0,1000,7.96,14.81,10.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,1,1000,8.62,16.66,11.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,2,1000,9.46,19.0,13.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,4,1000,9.68,19.56,13.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,8,1000,8.71,16.67,12.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,16,1000,8.85,16.41,12.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,32,1000,10.13,17.82,13.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,64,1000,11.46,21.0,15.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,128,1000,13.73,24.49,18.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,256,1000,16.45,32.11,23.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,512,1000,22.3,49.46,37.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,1024,1000,20.87,56.76,44.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,2048,1000,15.08,93.5,67.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,4096,1000,15.5,147.4,96.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,8192,1000,26.38,213.35,151.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,16384,1000,31.68,398.69,284.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,32768,1000,53.21,842.81,583.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,65536,640,58.32,1779.93,1114.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,131072,320,201.07,3712.42,2262.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,262144,160,298.77,6709.72,4496.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,524288,80,554.55,17923.11,11736.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,1048576,40,1063.37,35994.89,24251.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,2097152,20,1756.34,78081.83,51329.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,288,4194304,10,3922.61,153554.39,101492.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatter,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,1,1000,0.77,1.72,1.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,2,1000,0.77,1.77,1.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,4,1000,0.76,1.72,1.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,8,1000,0.77,1.74,1.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,16,1000,0.81,1.45,1.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,32,1000,0.83,1.54,1.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,64,1000,0.85,1.59,1.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,128,1000,0.89,2.29,1.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,256,1000,1.05,2.85,2.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,512,1000,1.21,5.02,3.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,1024,1000,1.6,6.52,4.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,2048,1000,2.76,9.83,7.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,4096,1000,3.51,13.73,9.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,8192,1000,3.98,34.85,25.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,16384,1000,6.1,47.66,36.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,32768,1000,6.21,74.87,54.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,65536,640,8.75,71.51,43.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,131072,320,14.81,79.7,49.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,262144,160,26.08,139.51,86.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,524288,80,49.99,258.89,163.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,1048576,40,416.54,2178.52,1878.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,2097152,20,667.15,2823.26,2469.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,4194304,10,1353.87,5686.18,4954.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,1,1000,4.53,5.47,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,2,1000,4.89,5.97,5.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,4,1000,5.15,6.33,5.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,8,1000,6.12,7.52,6.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,16,1000,8.21,12.61,11.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,32,1000,9.88,13.16,10.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,64,1000,12.87,16.84,13.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,128,1000,16.63,30.27,24.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,256,1000,22.43,26.0,23.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,512,1000,63.08,67.08,65.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,1024,1000,64.07,69.37,65.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,2048,1000,103.11,112.11,106.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,4096,1000,132.99,147.21,138.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,8192,1000,175.07,179.78,177.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,16384,1000,276.87,279.21,277.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,32768,1000,525.59,617.98,570.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,65536,640,1395.13,1490.21,1442.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,131072,320,3167.82,3735.46,3490.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,262144,160,6513.08,7178.66,6864.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,524288,80,15320.53,15745.52,15542.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,1048576,40,32826.71,33722.28,33413.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,2097152,20,74404.73,78198.39,76889.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,72,4194304,10,154015.82,160192.58,157802.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,1,1000,1.43,3.3,2.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,2,1000,1.55,3.55,2.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,4,1000,1.63,3.71,2.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,8,1000,0.91,1.8,1.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,16,1000,0.97,1.98,1.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,32,1000,0.95,1.92,1.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,64,1000,1.08,4.09,1.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,128,1000,1.53,4.33,2.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,256,1000,0.59,3.12,2.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,512,1000,1.58,4.4,2.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,1024,1000,1.68,3.51,3.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,2048,1000,2.61,4.67,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,4096,1000,3.28,5.86,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,8192,1000,4.67,8.27,6.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,16384,1000,8.19,12.38,10.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,32768,1000,15.48,19.87,17.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,65536,640,29.01,35.27,32.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,131072,320,32.18,35.55,33.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,262144,160,62.5,65.87,64.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,524288,80,112.14,115.09,113.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,1048576,40,206.42,209.44,207.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,2097152,20,423.27,426.8,424.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,54,4194304,10,1176.55,1181.64,1177.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,4,1000,0.28,2.39,0.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,8,1000,0.29,2.55,0.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,16,1000,0.29,2.81,0.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,32,1000,0.29,3.51,0.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,64,1000,0.3,3.87,0.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,128,1000,0.28,4.64,0.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,256,1000,0.28,4.83,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,512,1000,0.28,3.28,0.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,1024,1000,0.34,3.79,0.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,2048,1000,0.49,4.74,0.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,4096,1000,1.0,7.08,1.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,8192,1000,1.98,11.95,3.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,16384,1000,5.22,18.07,10.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,32768,1000,9.46,28.06,17.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,65536,640,26.26,44.27,31.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,131072,320,46.95,74.46,53.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,262144,160,89.93,137.67,100.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,524288,80,90.17,231.51,170.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,1048576,40,195.15,609.25,426.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,2097152,20,351.0,797.1,610.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,4194304,10,683.98,1540.82,1192.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,216,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,1,1000,0.56,51.85,3.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,2,1000,0.56,62.6,3.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,4,1000,0.56,23.02,1.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,8,1000,0.56,15.1,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,16,1000,0.51,31.95,2.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,32,1000,0.46,14.08,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,64,1000,0.47,16.6,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,128,1000,0.5,25.51,1.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,256,1000,0.52,29.69,1.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,512,1000,0.75,52.02,2.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,1024,1000,0.89,85.68,4.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,2048,1000,1.29,199.67,8.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,4096,1000,2.2,260.95,12.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,8192,1000,3.96,466.4,22.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,16384,1000,8.12,911.56,42.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,32768,1000,15.25,2119.47,80.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,65536,640,40.11,1222.6,700.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,131072,320,83.44,2247.59,1253.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,262144,160,160.25,4640.16,2622.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,524288,80,307.23,9374.62,5322.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,1048576,40,250.9,24505.18,16169.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,2097152,20,2106.18,40938.39,25215.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,216,4194304,10,12132.8,78592.3,53672.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,54,0,1000,0.48,0.59,0.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,4,1000,6.37,7.74,6.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,8,1000,0.83,5.51,1.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,16,1000,0.84,6.17,2.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,32,1000,0.87,6.87,2.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,64,1000,0.94,7.33,3.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,128,1000,0.95,8.49,5.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,256,1000,7.42,9.37,8.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,512,1000,6.42,7.66,7.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,1024,1000,8.87,10.44,9.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,2048,1000,7.89,9.98,9.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,4096,1000,10.15,12.14,11.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,8192,1000,14.0,16.71,15.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,16384,1000,18.31,21.26,20.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,32768,1000,29.5,33.69,32.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,65536,640,52.84,59.79,57.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,131072,320,258.08,324.13,291.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,262144,160,144.55,192.23,169.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,524288,80,272.81,352.94,321.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,1048576,40,510.6,628.85,588.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,2097152,20,970.36,1172.97,1105.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,54,4194304,10,1956.27,2275.37,2171.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,216,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,1,1000,0.55,11.93,1.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,2,1000,0.55,13.02,1.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,4,1000,0.56,16.61,1.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,8,1000,0.49,12.5,1.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,16,1000,0.48,12.45,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,32,1000,0.46,12.52,1.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,64,1000,0.47,15.27,1.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,128,1000,0.5,24.67,1.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,256,1000,0.51,26.53,1.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,512,1000,0.68,45.28,2.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,1024,1000,0.87,86.37,4.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,2048,1000,1.18,206.71,8.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,4096,1000,2.25,259.27,12.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,8192,1000,4.09,506.59,24.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,16384,1000,7.83,912.67,43.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,32768,1000,14.43,2256.35,80.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,65536,640,52.03,2054.07,1108.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,131072,320,81.82,2777.13,1596.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,262144,160,155.67,4697.76,2695.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,524288,80,302.19,9238.63,5283.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,1048576,40,227.92,24128.67,15880.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,2097152,20,1923.13,40034.11,24822.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gather,216,4194304,10,12527.96,77077.56,52710.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,18,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,4,1000,0.26,1.02,0.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,8,1000,0.27,1.03,0.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,16,1000,0.27,1.05,0.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,32,1000,0.27,1.06,0.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,64,1000,0.28,1.35,0.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,128,1000,0.27,1.5,0.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,256,1000,0.28,1.57,0.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,512,1000,0.27,1.67,0.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,1024,1000,0.29,2.64,0.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,2048,1000,0.43,3.08,0.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,4096,1000,0.87,4.76,1.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,8192,1000,1.89,8.05,2.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,16384,1000,5.86,15.24,10.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,32768,1000,10.89,25.12,17.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,65536,640,20.53,39.29,30.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,131072,320,39.28,69.45,53.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,262144,160,78.12,130.8,103.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,524288,80,111.73,177.75,142.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,1048576,40,216.16,327.36,269.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,2097152,20,434.61,642.23,535.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,18,4194304,10,872.13,1266.45,1068.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,54,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,1,1000,4.83,5.9,5.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,2,1000,5.11,6.4,5.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,4,1000,5.6,7.12,6.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,8,1000,6.66,8.77,7.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,16,1000,7.75,10.57,9.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,32,1000,10.18,13.79,11.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,64,1000,8.02,10.77,9.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,128,1000,9.43,13.01,11.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,256,1000,11.64,16.37,14.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,512,1000,19.27,27.03,22.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,1024,1000,42.61,47.13,43.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,2048,1000,68.49,73.49,69.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,4096,1000,121.43,129.93,124.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,8192,1000,223.96,239.31,230.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,16384,1000,320.89,350.14,338.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,32768,1000,622.1,695.77,663.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,65536,640,1202.96,1342.5,1282.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,131072,320,2408.78,2685.01,2562.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,262144,160,4858.59,5383.34,5166.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,524288,80,11769.22,12230.05,12055.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,1048576,40,24723.44,26059.57,25565.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,2097152,20,55638.07,60355.59,58574.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,4194304,10,113638.32,120846.59,118420.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,216,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,1,1000,0.84,14.92,5.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,2,1000,0.84,6.39,4.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,4,1000,0.84,7.32,4.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,8,1000,0.85,6.28,4.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,16,1000,0.84,6.17,4.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,32,1000,0.84,6.26,4.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,64,1000,0.85,6.09,4.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,128,1000,0.87,6.6,5.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,256,1000,0.99,8.27,6.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,512,1000,0.93,8.23,5.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,1024,1000,1.04,8.22,5.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,2048,1000,1.65,7.76,5.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,4096,1000,3.66,10.82,7.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,8192,1000,6.59,16.62,13.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,16384,1000,13.28,31.51,27.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,32768,1000,19.87,49.21,42.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,65536,640,38.16,60.82,55.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,131072,320,64.86,113.82,97.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,262144,160,133.54,200.68,178.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,524288,80,263.38,356.52,324.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,1048576,40,523.39,654.08,607.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,2097152,20,1047.48,1282.66,1199.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Bcast,216,4194304,10,2200.46,2560.16,2435.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatterv,54,0,1000,1.9,3.47,2.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,1,1000,4.45,6.45,5.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,2,1000,5.07,7.5,6.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,4,1000,5.19,7.76,6.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,8,1000,5.16,7.6,6.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,16,1000,6.4,9.97,8.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,32,1000,5.11,6.68,5.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,64,1000,4.96,6.94,5.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,128,1000,5.26,7.46,6.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,256,1000,2.5,15.02,7.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,512,1000,7.56,10.56,9.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,1024,1000,9.19,12.89,10.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,2048,1000,3.4,43.44,23.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,4096,1000,4.81,78.17,41.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,8192,1000,21.54,162.56,113.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,16384,1000,28.4,209.21,152.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,32768,1000,29.38,339.33,261.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,65536,640,54.02,584.17,472.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,131072,320,114.66,1025.02,837.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,262144,160,212.85,2074.23,1784.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,524288,80,426.5,4174.21,3739.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,1048576,40,565.33,6626.55,5945.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,2097152,20,1046.02,21750.9,19642.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,54,4194304,10,1518.42,16472.83,14416.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,72,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,4,1000,4.31,16.83,8.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,8,1000,3.58,12.53,4.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,16,1000,3.46,4.4,3.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,32,1000,4.23,5.29,4.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,64,1000,6.73,30.81,15.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,128,1000,4.33,7.62,4.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,256,1000,6.54,10.33,7.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,512,1000,7.55,19.75,8.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,1024,1000,5.78,7.88,6.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,2048,1000,6.11,8.56,6.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,4096,1000,8.8,11.69,9.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,8192,1000,16.22,19.48,16.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,16384,1000,24.54,28.61,27.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,32768,1000,41.01,48.66,42.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,65536,640,83.16,96.29,86.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,131072,320,110.81,118.91,113.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,262144,160,184.86,194.45,190.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,524288,80,350.18,367.79,358.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,1048576,40,653.88,705.41,682.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,2097152,20,1038.61,1140.0,1088.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,72,4194304,10,2053.74,2270.72,2174.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,288,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,1,1000,1.26,11.81,5.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,2,1000,1.28,14.35,6.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,4,1000,1.62,13.95,6.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,8,1000,1.77,11.99,5.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,16,1000,2.58,12.92,6.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,32,1000,3.93,15.73,8.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,64,1000,5.26,20.04,11.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,128,1000,7.02,26.51,16.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,256,1000,10.3,35.53,23.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,512,1000,17.28,69.18,50.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,1024,1000,24.77,89.86,71.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,2048,1000,33.83,164.75,123.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,4096,1000,52.96,252.25,190.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,8192,1000,95.83,464.33,341.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,16384,1000,174.17,813.48,594.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,32768,1000,18.43,961.97,416.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,65536,640,30.57,1691.08,670.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,131072,320,95.29,2443.24,1258.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,262144,160,208.87,4701.98,2668.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,524288,80,242.4,9348.88,6160.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,1048576,40,4112.0,18610.19,13807.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,2097152,20,9086.98,37274.94,29081.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatter,288,4194304,10,13311.15,74664.08,60621.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,18,0,1000,0.03,0.04,0.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,1,1000,0.28,1.94,0.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,2,1000,0.28,1.99,0.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,4,1000,0.28,2.21,0.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,8,1000,0.28,1.92,0.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,16,1000,0.28,1.99,0.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,32,1000,0.28,2.05,0.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,64,1000,0.29,2.26,0.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,128,1000,0.31,2.94,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,256,1000,0.34,4.67,0.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,512,1000,0.5,4.43,1.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,1024,1000,0.99,8.15,1.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,2048,1000,1.37,10.69,2.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,4096,1000,2.56,15.85,3.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,8192,1000,3.53,25.96,5.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,16384,1000,7.18,46.49,10.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,32768,1000,12.77,80.71,19.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,65536,640,24.02,129.5,35.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,131072,320,28.58,242.69,56.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,262144,160,62.99,470.35,106.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,524288,80,138.95,907.94,210.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,1048576,40,286.16,1752.41,424.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,2097152,20,1419.3,3504.95,1687.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,18,4194304,10,5005.73,7075.13,5240.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,36,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,4,1000,0.26,1.21,0.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,8,1000,0.27,1.26,0.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,16,1000,0.27,1.36,0.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,32,1000,0.27,1.35,0.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,64,1000,0.27,1.57,0.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,128,1000,0.27,1.87,0.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,256,1000,0.28,2.14,0.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,512,1000,0.28,2.38,0.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,1024,1000,0.31,3.15,0.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,2048,1000,0.33,4.3,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,4096,1000,0.36,6.28,1.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,8192,1000,0.82,9.68,2.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,16384,1000,6.25,17.65,9.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,32768,1000,12.09,29.57,17.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,65536,640,23.96,49.61,35.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,131072,320,29.74,53.52,39.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,262144,160,61.48,107.31,81.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,524288,80,153.28,191.82,172.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,1048576,40,313.6,349.63,331.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,2097152,20,536.0,682.17,558.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,36,4194304,10,1044.46,1382.89,1072.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,1,1000,0.91,2.29,1.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,2,1000,0.92,2.28,1.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,4,1000,0.92,2.35,1.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,8,1000,0.93,2.37,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,16,1000,1.06,2.15,1.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,32,1000,1.1,2.34,1.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,64,1000,1.16,2.64,1.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,128,1000,1.21,4.0,2.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,256,1000,2.35,5.05,3.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,512,1000,2.54,7.69,5.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,1024,1000,4.06,10.95,7.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,2048,1000,4.41,15.9,10.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,4096,1000,6.11,23.28,15.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,8192,1000,4.62,74.48,52.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,16384,1000,6.68,104.48,75.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,32768,1000,6.44,180.9,132.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,65536,640,8.81,270.11,191.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,131072,320,14.44,257.39,145.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,262144,160,26.88,395.79,242.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,524288,80,52.82,1931.57,1626.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,1048576,40,456.51,4259.08,3707.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,2097152,20,664.9,4979.15,4272.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,4194304,10,1418.23,10049.32,8720.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,144,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,1,1000,9.0,13.57,11.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,2,1000,10.08,14.88,12.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,4,1000,14.04,25.89,22.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,8,1000,12.16,18.9,14.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,16,1000,14.68,29.28,24.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,32,1000,13.79,25.76,18.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,64,1000,26.68,37.52,32.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,128,1000,23.73,65.66,47.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,256,1000,47.4,82.09,74.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,512,1000,86.64,152.55,138.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,1024,1000,169.21,233.59,215.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,2048,1000,274.75,305.01,298.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,4096,1000,498.0,569.63,518.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,8192,1000,940.24,961.08,957.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,16384,1000,1061.06,1351.04,1204.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,32768,1000,2063.39,2646.77,2370.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,65536,640,4057.23,5272.75,4697.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,131072,320,7995.11,10242.8,9270.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,262144,160,14786.33,20639.72,17952.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,524288,80,29554.68,30555.84,30144.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,1048576,40,66394.06,68023.91,67070.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,2097152,20,150034.98,155736.42,153243.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,144,4194304,10,306331.03,317392.38,311244.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,36,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,1,1000,0.37,3.31,0.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,2,1000,0.37,3.37,0.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,4,1000,0.38,3.45,0.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,8,1000,0.38,3.67,0.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,16,1000,0.38,3.85,1.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,32,1000,0.39,4.7,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,64,1000,0.44,5.71,1.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,128,1000,0.45,6.87,1.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,256,1000,0.48,8.53,1.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,512,1000,0.81,10.59,2.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,1024,1000,2.5,22.52,3.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,2048,1000,3.47,29.41,4.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,4096,1000,6.13,43.15,8.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,8192,1000,9.68,68.43,13.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,16384,1000,5.98,109.72,20.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,32768,1000,6.43,184.21,27.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,65536,640,11.41,311.11,39.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,131072,320,12.02,516.2,49.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,262144,160,23.78,969.26,81.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,524288,80,57.42,1816.14,149.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,1048576,40,192.27,3516.61,355.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,2097152,20,2416.08,7301.6,2923.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,36,4194304,10,9682.77,14488.48,10139.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,1,1000,1.26,3.02,2.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,2,1000,1.2,2.94,2.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,4,1000,1.22,3.11,2.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,8,1000,1.32,4.18,2.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,16,1000,1.48,4.27,3.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,32,1000,1.53,7.03,4.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,64,1000,2.58,6.93,5.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,128,1000,2.25,9.17,6.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,256,1000,3.01,10.88,8.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,512,1000,4.46,13.84,10.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,1024,1000,6.59,17.87,13.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,2048,1000,8.74,30.17,23.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,4096,1000,2.3,106.25,49.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,8192,1000,21.02,176.97,116.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,16384,1000,24.38,256.29,177.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,32768,1000,6.1,426.76,328.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,65536,640,10.7,726.24,575.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,131072,320,15.48,1314.1,1066.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,262144,160,29.57,2679.12,2281.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,524288,80,292.6,15964.78,15252.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,1048576,40,575.86,11227.68,10355.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,2097152,20,1343.93,16821.24,14819.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,72,4194304,10,3500.51,23071.01,20065.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,36,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,1,1000,3.45,4.46,3.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,2,1000,3.64,4.76,4.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,4,1000,3.81,4.95,4.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,8,1000,4.07,5.26,4.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,16,1000,5.17,6.26,5.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,32,1000,6.26,8.05,7.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,64,1000,7.6,10.43,8.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,128,1000,7.05,9.49,7.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,256,1000,10.92,13.45,11.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,512,1000,27.98,29.52,28.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,1024,1000,28.17,30.92,28.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,2048,1000,51.07,51.79,51.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,4096,1000,82.11,83.37,82.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,8192,1000,144.57,149.33,147.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,16384,1000,193.13,194.05,193.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,32768,1000,369.6,374.49,372.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,65536,640,744.34,762.02,754.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,131072,320,1480.9,1517.53,1503.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,262144,160,2984.2,3029.48,3010.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,524288,80,6235.66,6313.38,6284.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,1048576,40,15868.66,16125.13,15989.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,2097152,20,37166.23,37803.04,37492.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,36,4194304,10,75577.29,76565.37,76207.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,54,0,1000,0.48,0.53,0.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,4,1000,6.36,7.72,6.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,8,1000,0.82,5.51,1.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,16,1000,0.84,6.2,2.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,32,1000,0.88,6.96,2.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,64,1000,0.92,7.19,3.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,128,1000,0.93,8.49,5.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,256,1000,7.3,9.28,8.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,512,1000,8.02,10.02,9.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,1024,1000,10.34,12.63,11.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,2048,1000,9.79,12.7,11.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,4096,1000,12.08,14.96,13.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,8192,1000,15.69,19.09,17.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,16384,1000,21.52,26.65,24.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,32768,1000,34.17,41.36,37.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,65536,640,50.25,58.82,56.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,131072,320,243.86,314.54,279.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,262144,160,199.66,301.43,248.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,524288,80,415.69,559.82,503.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,1048576,40,536.03,664.09,621.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,2097152,20,999.48,1213.3,1152.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,54,4194304,10,1900.49,2285.29,2187.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,4,1000,2.65,4.1,3.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,8,1000,2.87,4.53,3.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,16,1000,3.24,5.11,3.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,32,1000,3.86,6.1,4.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,64,1000,5.33,7.69,6.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,128,1000,6.41,9.26,7.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,256,1000,6.88,9.67,7.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,512,1000,4.57,6.19,5.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,1024,1000,5.65,7.38,6.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,2048,1000,7.13,9.48,7.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,4096,1000,9.91,12.81,10.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,8192,1000,17.55,20.52,18.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,16384,1000,39.37,42.22,40.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,32768,1000,45.19,48.76,45.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,65536,640,76.28,84.19,77.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,131072,320,128.41,135.07,129.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,262144,160,237.81,248.69,240.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,524288,80,439.08,451.56,442.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,1048576,40,802.45,831.6,816.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,2097152,20,1636.53,1644.77,1638.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,54,4194304,10,3302.41,3306.88,3303.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,0,1000,0.6,0.72,0.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,1,1000,6.78,8.84,7.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,2,1000,15.72,26.68,23.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,4,1000,8.24,17.69,9.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,8,1000,8.96,10.56,9.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,16,1000,10.12,11.86,10.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,32,1000,20.0,23.63,20.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,64,1000,21.85,24.66,22.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,128,1000,27.4,31.12,27.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,256,1000,40.35,43.85,41.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,512,1000,68.64,71.8,69.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,1024,1000,82.13,95.39,89.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,2048,1000,99.55,109.12,103.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,4096,1000,134.51,147.71,140.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,8192,1000,179.08,184.36,181.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,16384,1000,277.9,279.97,278.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,32768,1000,532.83,574.14,554.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,65536,640,1372.32,1476.98,1425.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,131072,320,2989.87,3258.56,3135.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,262144,160,6526.89,7032.91,6774.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,524288,80,15583.79,16128.32,15861.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,1048576,40,35702.1,35715.59,35710.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,2097152,20,72105.89,72111.28,72106.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,72,4194304,10,143439.81,143449.04,143441.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,144,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,1,1000,2.27,5.83,4.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,2,1000,0.62,5.72,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,4,1000,0.62,5.72,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,8,1000,0.61,5.75,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,16,1000,0.61,6.09,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,32,1000,0.62,5.73,4.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,64,1000,0.63,6.09,4.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,128,1000,0.64,5.87,4.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,256,1000,0.73,6.52,4.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,512,1000,0.7,4.72,3.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,1024,1000,0.81,6.06,4.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,2048,1000,1.23,5.52,3.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,4096,1000,2.42,8.85,5.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,8192,1000,4.9,13.2,9.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,16384,1000,8.13,20.71,16.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,32768,1000,12.86,35.08,28.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,65536,640,30.2,51.15,45.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,131072,320,61.69,91.37,82.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,262144,160,126.17,150.79,144.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,524288,80,256.47,284.34,276.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,1048576,40,517.97,556.44,542.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,2097152,20,1033.49,1096.0,1074.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,4194304,10,3461.45,3649.37,3562.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,36,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,1,1000,0.94,2.38,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,2,1000,0.93,2.36,1.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,4,1000,0.93,2.36,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,8,1000,0.93,2.39,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,16,1000,1.05,2.18,1.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,32,1000,1.11,2.4,1.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,64,1000,1.12,2.55,1.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,128,1000,1.19,3.74,2.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,256,1000,2.24,4.54,3.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,512,1000,1.87,6.24,4.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,1024,1000,2.62,8.68,6.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,2048,1000,3.45,13.66,9.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,4096,1000,5.07,22.62,14.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,8192,1000,6.12,50.45,36.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,16384,1000,12.04,86.02,64.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,32768,1000,62.45,236.92,174.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,65536,640,26.82,136.18,84.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,131072,320,51.38,196.17,129.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,262144,160,99.61,367.68,251.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,524288,80,194.34,865.3,594.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,1048576,40,351.8,2607.72,2199.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,2097152,20,927.51,5096.08,4401.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,36,4194304,10,1481.12,10133.36,8843.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,288,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,4,1000,7.3,10.98,9.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,8,1000,7.52,12.25,9.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,16,1000,6.86,10.83,8.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,32,1000,7.18,11.02,8.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,64,1000,8.46,13.97,10.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,128,1000,9.27,16.28,12.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,256,1000,12.05,19.5,15.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,512,1000,11.95,17.38,13.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,1024,1000,13.02,18.25,14.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,2048,1000,13.06,18.83,14.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,4096,1000,18.08,22.36,19.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,8192,1000,44.94,55.23,47.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,16384,1000,84.1,96.62,88.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,32768,1000,60.16,85.58,72.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,65536,640,100.61,128.49,111.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,131072,320,161.87,200.15,175.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,262144,160,284.9,347.77,306.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,524288,80,583.72,721.75,626.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,1048576,40,1925.93,2469.75,2209.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,2097152,20,3226.88,3279.78,3260.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,288,4194304,10,5332.17,5379.06,5356.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allreduce,144,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,4,1000,4.98,8.21,6.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,8,1000,5.73,9.07,7.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,16,1000,4.86,8.17,6.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,32,1000,4.97,8.34,6.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,64,1000,6.42,11.36,8.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,128,1000,7.38,14.93,10.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,256,1000,8.44,16.86,12.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,512,1000,14.85,23.02,18.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,1024,1000,11.58,20.05,15.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,2048,1000,13.85,21.82,17.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,4096,1000,17.98,26.05,21.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,8192,1000,38.6,48.83,41.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,16384,1000,67.72,76.64,71.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,32768,1000,47.33,61.44,54.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,65536,640,72.28,90.96,80.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,131072,320,122.57,151.03,134.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,262144,160,229.7,272.06,246.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,524288,80,353.97,412.82,376.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,1048576,40,1228.97,1335.81,1274.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,2097152,20,2365.17,2530.35,2438.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,144,4194304,10,6246.03,6417.1,6326.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,0,1000,6.09,17.46,8.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,1,1000,6.41,12.62,9.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,2,1000,6.44,12.63,9.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,4,1000,6.49,12.98,9.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,8,1000,6.62,13.04,9.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,16,1000,7.35,14.2,10.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,32,1000,6.99,12.06,9.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,64,1000,7.93,13.52,10.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,128,1000,7.72,14.66,10.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,256,1000,9.23,18.58,13.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,512,1000,10.03,28.09,19.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,1024,1000,13.07,39.48,28.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,2048,1000,18.43,77.02,54.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,4096,1000,13.09,177.8,112.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,8192,1000,38.81,314.23,192.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,16384,1000,48.18,572.86,348.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,32768,1000,58.02,1035.83,620.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,65536,640,77.06,2359.12,1487.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,131072,320,115.65,4299.65,2496.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,262144,160,652.53,7405.46,4644.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,524288,80,683.28,21029.71,11210.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,1048576,40,1194.98,35192.3,18408.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,2097152,20,1860.69,78160.23,41173.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatterv,144,4194304,10,4423.29,154879.12,81775.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,288,0,1000,0.05,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,4,1000,0.28,6.67,0.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,8,1000,0.25,7.34,0.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,16,1000,0.25,8.54,0.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,32,1000,0.25,8.54,0.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,64,1000,0.25,9.94,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,128,1000,0.25,10.03,0.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,256,1000,0.25,11.05,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,512,1000,0.25,11.68,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,1024,1000,0.26,13.35,0.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,2048,1000,0.26,16.3,1.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,4096,1000,0.31,20.27,1.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,8192,1000,1.42,31.25,4.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,16384,1000,4.26,43.25,11.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,32768,1000,12.48,110.11,66.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,65536,640,28.86,145.03,99.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,131072,320,62.01,243.4,174.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,262144,160,25.46,559.89,250.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,524288,80,52.47,867.77,395.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,1048576,40,122.04,1399.91,674.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,2097152,20,544.82,1970.31,1644.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,288,4194304,10,655.48,3829.22,2021.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,0,1000,7.95,15.0,10.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,1,1000,8.57,17.05,11.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,2,1000,9.42,19.19,13.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,4,1000,9.59,19.86,13.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,8,1000,9.75,20.03,14.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,16,1000,10.58,20.59,15.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,32,1000,11.65,22.11,16.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,64,1000,14.0,26.62,18.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,128,1000,14.99,29.39,20.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,256,1000,17.7,38.69,26.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,512,1000,22.62,49.53,36.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,1024,1000,18.81,59.8,44.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,2048,1000,14.08,91.05,60.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,4096,1000,15.34,134.25,94.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,8192,1000,32.88,252.27,172.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,16384,1000,27.21,450.15,298.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,32768,1000,39.24,744.47,523.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,65536,640,50.36,1908.42,1100.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,131072,320,238.06,2837.25,2132.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,262144,160,338.87,6124.67,4237.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,524288,80,459.26,15438.53,10689.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,1048576,40,1064.92,35356.39,24218.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,2097152,20,1806.1,77216.19,51467.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Scatterv,288,4194304,10,4200.29,154340.89,102663.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Bcast,288,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,1,1000,0.93,4.73,3.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,2,1000,1.15,6.24,4.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,4,1000,1.1,6.22,4.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,8,1000,1.09,6.01,4.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,16,1000,1.1,6.26,4.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,32,1000,1.15,6.05,4.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,64,1000,1.15,6.06,4.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,128,1000,1.18,6.28,4.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,256,1000,1.24,6.7,5.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,512,1000,1.28,6.8,5.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,1024,1000,1.16,5.76,4.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,2048,1000,2.11,11.06,7.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,4096,1000,4.38,11.1,8.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,8192,1000,7.47,17.22,12.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,16384,1000,12.52,25.77,22.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,32768,1000,20.51,50.27,43.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,65536,640,37.26,63.64,56.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,131072,320,71.33,111.94,97.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,262144,160,147.72,195.65,178.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,524288,80,307.15,337.59,327.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,1048576,40,613.76,651.5,636.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,2097152,20,1182.94,1271.81,1218.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,288,4194304,10,2395.72,2412.26,2405.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,54,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,1,1000,14.18,14.93,14.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,2,1000,15.81,17.26,16.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,4,1000,16.22,17.32,16.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,8,1000,16.56,17.79,17.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,16,1000,17.99,18.99,18.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,32,1000,21.1,24.14,22.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,64,1000,22.5,26.32,23.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,128,1000,27.89,31.84,29.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,256,1000,40.4,46.12,43.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,512,1000,87.83,107.5,96.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,1024,1000,97.22,118.93,107.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,2048,1000,136.65,142.76,139.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,4096,1000,131.7,135.37,133.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,8192,1000,193.69,231.6,211.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,16384,1000,464.38,472.9,468.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,32768,1000,1546.35,1570.82,1556.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,65536,640,2389.62,2492.96,2447.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,131072,320,5849.14,5965.7,5928.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,262144,160,9491.09,9830.45,9648.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,524288,80,24199.63,25764.7,25142.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,1048576,40,33148.22,33409.11,33301.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,2097152,20,63407.08,64119.49,63833.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,54,4194304,10,122032.54,125134.85,123702.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,216,0,1000,2.89,7.59,3.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,1,1000,24.57,64.14,47.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,2,1000,20.85,28.01,24.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,4,1000,22.36,30.08,25.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,8,1000,23.96,30.94,26.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,16,1000,29.32,38.45,33.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,32,1000,29.15,44.68,36.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,64,1000,77.73,94.08,90.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,128,1000,89.58,116.66,112.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,256,1000,116.93,165.87,158.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,512,1000,210.67,276.06,248.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,1024,1000,307.32,413.12,384.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,2048,1000,444.1,515.41,494.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,4096,1000,554.74,621.54,589.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,8192,1000,939.11,1035.91,986.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,16384,1000,1746.45,2037.99,1898.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,32768,1000,3395.39,4083.33,3746.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,65536,640,6021.44,7116.88,6587.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,131072,320,11442.08,13551.44,12623.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,262144,160,21035.86,24716.21,22889.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,524288,80,46213.25,49101.27,47676.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,1048576,40,99853.09,104073.75,101884.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,2097152,20,228650.93,235982.81,232246.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgatherv,216,4194304,10,463896.45,476753.45,469653.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce_scatter,36,0,1000,0.36,0.49,0.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,4,1000,0.74,4.21,1.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,8,1000,0.73,4.36,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,16,1000,0.74,4.66,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,32,1000,0.9,4.96,2.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,64,1000,0.93,5.65,2.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,128,1000,2.69,6.4,5.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,256,1000,4.98,6.52,5.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,512,1000,5.64,7.2,6.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,1024,1000,5.15,6.33,5.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,2048,1000,5.83,7.27,6.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,4096,1000,7.58,9.25,8.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,8192,1000,11.07,13.18,11.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,16384,1000,16.36,19.07,17.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,32768,1000,41.51,54.47,47.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,65536,640,69.06,84.21,76.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,131072,320,157.8,184.26,170.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,262144,160,146.28,185.28,172.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,524288,80,228.28,284.79,266.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,1048576,40,455.4,544.09,519.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,2097152,20,895.45,998.68,942.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,36,4194304,10,1758.41,1920.0,1841.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,1,1000,1.35,8.63,4.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,2,1000,1.33,9.17,4.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,4,1000,1.37,10.43,5.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,8,1000,1.44,12.81,6.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,16,1000,2.4,12.43,6.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,32,1000,3.17,22.32,11.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,64,1000,5.11,18.33,9.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,128,1000,8.38,19.52,13.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,256,1000,13.66,23.56,19.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,512,1000,24.77,42.24,33.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,1024,1000,34.26,73.41,56.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,2048,1000,52.91,132.5,101.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,4096,1000,74.77,215.36,167.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,8192,1000,130.35,470.96,342.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,16384,1000,228.5,650.87,488.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,32768,1000,42.25,1539.14,858.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,65536,640,64.59,3837.91,1207.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,131072,320,68.19,2282.61,1297.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,262144,160,173.01,3187.87,1987.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,524288,80,296.94,6313.52,4100.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,1048576,40,4400.43,12643.64,10140.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,2097152,20,9321.63,25265.3,20429.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatter,216,4194304,10,11459.61,50498.99,42341.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Reduce,144,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,4,1000,0.33,8.73,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,8,1000,0.35,7.98,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,16,1000,0.36,7.88,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,32,1000,0.36,8.98,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,64,1000,0.37,9.07,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,128,1000,0.34,9.47,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,256,1000,0.35,10.47,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,512,1000,0.36,11.2,0.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,1024,1000,0.38,13.79,1.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,2048,1000,0.42,11.65,1.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,4096,1000,0.77,15.68,1.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,8192,1000,2.7,29.54,5.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,16384,1000,7.42,34.23,11.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,32768,1000,14.68,50.48,21.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,65536,640,80.4,180.24,146.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,131072,320,142.75,277.0,231.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,262144,160,81.7,434.92,277.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,524288,80,147.33,716.74,447.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,1048576,40,242.86,1068.46,675.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,2097152,20,334.89,1980.29,1162.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce,144,4194304,10,694.3,3309.68,2010.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Gather,144,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,1,1000,0.56,16.34,1.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,2,1000,0.57,16.0,1.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,4,1000,0.57,17.03,1.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,8,1000,0.56,26.88,2.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,16,1000,0.57,23.28,1.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,32,1000,0.57,21.39,2.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,64,1000,0.58,30.29,2.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,128,1000,0.59,36.34,2.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,256,1000,0.61,33.7,2.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,512,1000,0.84,47.8,3.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,1024,1000,0.98,78.36,5.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,2048,1000,1.15,116.83,6.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,4096,1000,1.74,230.84,10.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,8192,1000,1.39,251.73,6.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,16384,1000,2.26,396.62,8.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,32768,1000,4.11,701.88,13.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,65536,640,23.85,831.86,428.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,131072,320,58.46,1498.17,796.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,262144,160,136.23,2840.93,1509.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,524288,80,266.9,6315.56,3331.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,1048576,40,124.62,17793.32,9023.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,2097152,20,2683.42,28108.98,16797.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Gather,144,4194304,10,11608.39,53244.64,32359.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,54,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,4,1000,3.12,4.64,3.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,8,1000,3.62,5.85,4.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,16,1000,4.24,6.39,5.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,32,1000,4.23,6.29,5.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,64,1000,5.68,7.97,6.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,128,1000,6.84,9.65,7.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,256,1000,7.02,9.65,7.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,512,1000,7.76,10.47,8.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,1024,1000,9.02,11.73,9.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,2048,1000,10.75,13.51,11.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,4096,1000,14.19,16.84,15.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,8192,1000,21.76,24.9,23.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,16384,1000,51.89,58.94,54.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,32768,1000,59.75,64.22,62.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,65536,640,102.81,119.85,107.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,131072,320,121.63,125.96,124.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,262144,160,257.24,262.54,259.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,524288,80,352.34,357.2,354.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,1048576,40,663.48,676.42,669.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,2097152,20,1512.56,1537.38,1516.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,54,4194304,10,3075.21,3087.6,3078.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,4,1000,1.77,2.05,1.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,8,1000,1.51,2.15,1.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,16,1000,1.88,2.35,2.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,32,1000,1.62,2.26,1.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,64,1000,1.98,3.12,2.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,128,1000,2.47,3.81,2.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,256,1000,2.88,4.27,3.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,512,1000,2.6,3.89,2.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,1024,1000,3.26,4.5,3.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,2048,1000,4.5,6.36,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,4096,1000,7.22,9.42,7.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,8192,1000,13.19,15.12,14.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,16384,1000,22.58,25.0,24.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,32768,1000,40.71,42.95,41.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,65536,640,51.03,52.19,51.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,131072,320,90.69,93.28,91.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,262144,160,172.77,178.98,175.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,524288,80,320.86,334.99,329.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,1048576,40,637.93,673.02,659.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,2097152,20,973.99,1016.81,997.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,4194304,10,1950.85,2072.59,2034.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,144,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,1,1000,37.77,42.83,40.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,2,1000,35.18,44.43,37.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,4,1000,54.56,102.68,84.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,8,1000,41.2,61.5,50.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,16,1000,48.01,66.3,55.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,32,1000,54.75,94.94,79.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,64,1000,58.71,79.78,72.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,128,1000,98.39,129.31,118.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,256,1000,161.62,234.34,211.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,512,1000,337.24,372.04,357.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,1024,1000,471.69,513.49,500.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,2048,1000,897.33,942.5,928.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,4096,1000,1701.96,1850.62,1797.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,8192,1000,3646.47,3673.65,3657.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,16384,1000,7323.25,7376.86,7345.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,32768,692,14380.24,14485.47,14422.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,65536,32,197335.61,198029.26,197681.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,131072,32,57150.85,57280.88,57216.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,262144,32,111372.72,111608.46,111486.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,524288,8,223496.21,224116.03,223852.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,1048576,8,444702.76,445935.99,445370.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,2097152,7,888016.4,890196.59,889222.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Alltoall,144,4194304,5,1777011.41,1781535.28,1779478.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,72,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,1,1000,1.14,2.67,2.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,2,1000,1.16,2.69,2.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,4,1000,1.18,2.78,2.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,8,1000,0.64,1.71,1.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,16,1000,0.7,1.89,1.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,32,1000,0.7,1.87,1.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,64,1000,1.73,3.74,2.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,128,1000,2.32,4.53,2.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,256,1000,2.14,5.18,2.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,512,1000,1.29,7.9,1.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,1024,1000,1.44,3.04,1.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,2048,1000,2.12,4.85,4.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,4096,1000,1.95,4.81,2.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,8192,1000,3.92,6.81,4.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,16384,1000,7.23,10.38,7.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,32768,1000,13.05,16.11,13.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,65536,640,26.7,30.1,27.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,131072,320,51.49,54.62,52.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,262144,160,99.51,102.97,100.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,524288,80,194.66,198.28,195.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,1048576,40,376.28,379.83,377.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,2097152,20,739.56,743.73,740.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,72,4194304,10,1546.7,1551.41,1548.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,216,0,1000,2.11,14.05,5.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,1,1000,29.46,139.24,83.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,2,1000,28.77,136.13,83.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,4,1000,28.16,139.58,83.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,8,1000,29.54,140.3,83.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,16,1000,28.86,146.24,83.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,32,1000,28.57,172.85,84.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,64,1000,29.68,144.0,87.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,128,1000,29.82,149.61,88.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,256,1000,30.73,154.31,91.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,512,1000,41.8,208.89,103.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,1024,1000,55.18,218.68,128.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,2048,1000,65.13,271.05,159.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,4096,1000,66.58,284.02,165.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,8192,1000,105.74,455.07,266.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,16384,1000,148.89,763.84,397.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,32768,1000,212.86,1348.23,601.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,65536,640,712.74,3761.39,1878.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,131072,320,737.07,3249.4,2250.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,262144,160,1718.73,6185.88,4565.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,524288,80,4627.68,12205.35,9564.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,1048576,40,11932.27,24118.95,19752.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,2097152,20,25069.03,49410.39,40914.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Gatherv,216,4194304,10,34258.71,82902.51,66271.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,36,0,1000,1.02,2.66,1.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,1,1000,3.14,4.39,3.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,2,1000,3.22,4.55,4.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,4,1000,3.36,4.79,4.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,8,1000,3.52,5.01,4.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,16,1000,3.89,5.56,4.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,32,1000,4.37,6.11,5.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,64,1000,3.41,4.82,4.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,128,1000,3.94,5.98,5.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,256,1000,4.72,7.0,5.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,512,1000,4.1,8.33,6.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,1024,1000,4.88,10.76,8.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,2048,1000,2.8,22.72,12.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,4096,1000,3.81,34.08,18.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,8192,1000,7.85,54.17,38.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,16384,1000,11.6,73.47,56.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,32768,1000,33.9,188.37,137.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,65536,640,28.12,132.58,82.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,131072,320,52.38,197.77,131.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,262144,160,101.45,364.63,252.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,524288,80,195.91,804.49,546.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,1048576,40,400.33,2945.25,2502.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,2097152,20,796.85,5022.9,4336.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,36,4194304,10,1468.54,9811.84,8554.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,1,1000,16.76,17.81,17.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,2,1000,18.16,27.23,19.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,4,1000,19.64,21.11,20.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,8,1000,20.31,23.12,22.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,16,1000,24.06,26.95,25.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,32,1000,21.92,23.49,22.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,64,1000,26.91,28.72,27.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,128,1000,39.94,42.15,41.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,256,1000,50.45,54.79,53.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,512,1000,79.16,86.05,82.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,1024,1000,113.45,118.98,115.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,2048,1000,177.55,184.38,180.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,4096,1000,305.93,314.76,309.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,8192,1000,591.27,612.35,602.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,16384,1000,1124.88,1146.14,1133.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,32768,1000,1924.67,1974.65,1944.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,65536,640,3249.74,3306.11,3282.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,131072,320,6529.4,6649.7,6579.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,262144,160,11737.28,12012.28,11853.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,524288,80,20934.58,21297.07,21126.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,1048576,40,44770.51,45195.03,44982.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,2097152,20,92645.22,93621.01,93107.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,72,4194304,10,171713.83,174361.17,173047.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,1,1000,2.64,3.55,2.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,2,1000,2.69,3.5,2.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,4,1000,2.79,3.61,3.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,8,1000,2.95,4.01,3.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,16,1000,3.09,3.98,3.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,32,1000,3.69,4.64,3.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,64,1000,4.76,5.93,5.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,128,1000,6.22,7.38,6.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,256,1000,12.08,13.11,12.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,512,1000,11.81,13.01,12.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,1024,1000,16.18,16.94,16.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,2048,1000,20.66,21.54,21.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,4096,1000,26.72,27.32,26.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,8192,1000,39.96,40.44,40.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,16384,1000,64.53,65.14,64.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,32768,1000,76.14,77.06,76.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,65536,640,164.91,173.24,168.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,131072,320,448.76,462.66,455.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,262144,160,1344.12,1362.69,1352.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,524288,80,3238.66,3242.2,3239.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,1048576,40,8186.54,8413.01,8314.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,2097152,20,18968.91,19173.61,19117.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,4194304,10,38697.32,38965.4,38856.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,0,1000,1.31,3.74,2.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,1,1000,4.95,7.07,6.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,2,1000,5.31,7.67,6.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,4,1000,5.9,8.76,7.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,8,1000,5.96,8.96,7.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,16,1000,6.32,9.33,8.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,32,1000,4.87,8.04,7.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,64,1000,5.57,8.74,7.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,128,1000,5.32,9.32,7.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,256,1000,5.63,10.93,9.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,512,1000,6.5,13.01,11.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,1024,1000,8.17,17.06,14.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,2048,1000,4.0,71.13,34.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,4096,1000,5.97,107.51,53.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,8192,1000,21.87,264.95,179.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,16384,1000,24.6,268.91,183.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,32768,1000,34.23,453.65,351.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,65536,640,51.7,788.6,654.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,131072,320,83.06,1398.91,1158.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,262144,160,172.82,2715.32,2299.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,524288,80,294.75,5597.09,5011.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,1048576,40,904.72,11597.4,10583.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,2097152,20,725.23,11894.71,10430.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,4194304,10,1481.97,23403.14,20332.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,72,0,1000,1.33,13.03,4.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,1,1000,5.27,8.53,7.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,2,1000,5.75,8.73,7.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,4,1000,5.77,8.68,7.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,8,1000,5.8,8.8,7.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,16,1000,6.07,9.1,8.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,32,1000,4.88,8.17,7.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,64,1000,5.11,8.04,7.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,128,1000,5.29,17.87,8.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,256,1000,5.56,11.04,9.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,512,1000,6.44,13.25,11.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,1024,1000,8.2,17.41,14.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,2048,1000,4.32,76.58,36.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,4096,1000,5.11,92.22,46.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,8192,1000,26.88,178.02,116.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,16384,1000,31.01,270.39,180.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,32768,1000,57.79,500.33,394.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,65536,640,82.13,839.54,694.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,131072,320,113.09,1473.34,1264.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,262144,160,200.33,2789.5,2397.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,524288,80,364.24,9001.15,8376.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,1048576,40,733.72,9080.69,8103.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,2097152,20,1147.82,11340.02,9968.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,72,4194304,10,1419.52,14619.09,10800.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,0,1000,0.49,0.53,0.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,1,1000,4.77,5.33,5.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,2,1000,4.87,5.4,5.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,4,1000,4.9,5.44,5.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,8,1000,5.04,5.57,5.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,16,1000,5.3,5.86,5.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,32,1000,6.21,7.01,6.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,64,1000,7.33,8.41,7.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,128,1000,22.18,23.76,22.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,256,1000,25.76,27.85,26.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,512,1000,40.16,42.64,40.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,1024,1000,53.4,56.78,54.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,2048,1000,82.14,86.79,83.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,4096,1000,122.49,129.87,125.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,8192,1000,216.43,227.81,221.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,16384,1000,298.84,334.51,322.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,32768,1000,579.35,660.56,627.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,65536,640,1122.49,1290.57,1216.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,131072,320,2289.68,2553.08,2439.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,262144,160,4779.12,5307.23,5061.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,524288,80,11558.16,12245.17,12038.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,1048576,40,24282.11,25689.99,25261.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,2097152,20,55029.36,59920.84,58524.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,54,4194304,10,113028.99,120726.74,118019.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,18,0,1000,0.78,1.74,1.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,1,1000,2.39,3.48,3.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,2,1000,2.51,3.57,3.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,4,1000,2.6,3.69,3.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,8,1000,2.61,3.79,3.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,16,1000,2.6,3.86,3.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,32,1000,2.72,4.1,3.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,64,1000,2.83,4.48,3.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,128,1000,1.85,6.0,3.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,256,1000,1.64,4.7,2.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,512,1000,3.13,5.98,5.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,1024,1000,2.21,9.09,5.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,2048,1000,2.74,13.29,7.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,4096,1000,3.76,18.94,11.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,8192,1000,6.93,27.14,20.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,16384,1000,10.99,40.01,32.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,32768,1000,15.68,45.59,31.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,65536,640,28.15,71.35,52.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,131072,320,53.59,125.42,97.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,262144,160,107.05,239.54,189.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,524288,80,216.42,459.2,371.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,1048576,40,360.57,1513.97,1287.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,2097152,20,742.25,2923.12,2549.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,18,4194304,10,1505.39,5855.85,5126.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,216,0,1000,2.21,9.7,5.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,1,1000,26.06,140.19,82.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,2,1000,26.89,136.2,81.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,4,1000,27.21,139.46,81.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,8,1000,27.36,137.31,81.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,16,1000,26.42,136.14,81.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,32,1000,26.52,141.55,82.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,64,1000,27.54,140.46,83.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,128,1000,27.7,145.9,84.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,256,1000,27.21,144.59,84.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,512,1000,33.59,154.1,92.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,1024,1000,38.82,172.88,103.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,2048,1000,54.5,223.58,135.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,4096,1000,52.37,230.91,138.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,8192,1000,65.72,342.65,206.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,16384,1000,84.26,599.7,316.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,32768,1000,139.78,1181.68,498.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,65536,640,204.97,1567.12,1047.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,131072,320,682.72,2914.61,2056.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,262144,160,2213.51,5727.44,4405.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,524288,80,4535.74,12094.08,9454.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,1048576,40,11447.74,23640.88,19274.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,2097152,20,24353.54,48675.14,40227.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,216,4194304,10,33316.62,82782.35,66097.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,1,1000,0.81,5.99,4.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,2,1000,0.81,6.01,4.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,4,1000,0.82,5.72,4.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,8,1000,0.83,5.72,4.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,16,1000,0.81,5.73,4.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,32,1000,0.82,5.68,4.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,64,1000,0.84,6.15,4.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,128,1000,0.85,6.15,4.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,256,1000,0.98,6.34,4.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,512,1000,0.98,6.75,5.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,1024,1000,1.09,7.24,5.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,2048,1000,1.91,8.58,6.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,4096,1000,4.51,12.31,9.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,8192,1000,7.96,17.19,13.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,16384,1000,13.61,29.37,22.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,32768,1000,23.3,47.14,40.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,65536,640,51.93,79.07,72.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,131072,320,83.01,145.87,121.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,262144,160,170.05,252.69,221.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,524288,80,289.49,410.13,354.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,1048576,40,439.99,651.27,573.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,2097152,20,820.9,1130.16,998.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,216,4194304,10,2020.89,2398.09,2249.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,72,0,1000,1.19,3.16,2.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,1,1000,2.1,12.35,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,2,1000,2.28,13.38,4.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,4,1000,2.29,13.27,5.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,8,1000,1.88,11.16,4.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,16,1000,1.9,21.3,4.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,32,1000,1.89,12.71,4.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,64,1000,1.85,13.71,4.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,128,1000,1.92,16.62,4.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,256,1000,1.76,19.49,4.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,512,1000,1.97,24.65,4.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,1024,1000,12.05,52.91,29.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,2048,1000,17.51,85.53,41.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,4096,1000,29.07,108.77,61.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,8192,1000,76.52,178.34,120.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,16384,1000,125.13,282.24,199.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,32768,1000,94.94,371.35,219.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,65536,640,127.44,590.33,327.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,131072,320,192.38,1029.57,539.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,262144,160,367.74,1958.99,1020.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,524288,80,2186.35,3829.24,3081.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,1048576,40,5953.83,7705.18,6954.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,2097152,20,13731.29,15418.11,14671.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,4194304,10,28656.95,30407.02,29657.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,0,1000,0.05,0.07,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,4,1000,0.25,1.56,0.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,8,1000,0.26,1.59,0.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,16,1000,0.26,1.55,0.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,32,1000,0.26,1.59,0.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,64,1000,0.27,2.17,0.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,128,1000,0.26,2.51,0.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,256,1000,0.27,2.69,0.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,512,1000,0.27,2.94,0.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,1024,1000,0.3,4.11,0.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,2048,1000,0.32,6.42,0.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,4096,1000,0.35,9.23,1.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,8192,1000,1.03,35.74,3.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,16384,1000,6.48,25.82,11.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,32768,1000,11.82,37.14,17.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,65536,640,27.78,63.6,37.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,131072,320,52.48,102.08,65.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,262144,160,100.89,186.64,124.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,524288,80,154.5,274.18,215.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,1048576,40,205.23,403.26,262.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,2097152,20,393.11,737.57,506.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,72,4194304,10,690.57,1769.84,1261.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,1,1000,0.8,1.77,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,2,1000,0.77,1.81,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,4,1000,0.78,1.78,1.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,8,1000,0.78,1.81,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,16,1000,0.85,1.79,1.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,32,1000,0.84,1.63,1.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,64,1000,0.87,1.74,1.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,128,1000,0.87,2.25,1.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,256,1000,1.06,2.82,2.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,512,1000,1.27,4.97,3.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,1024,1000,1.79,6.15,4.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,2048,1000,2.36,7.81,5.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,4096,1000,3.27,11.41,8.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,8192,1000,5.82,24.6,18.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,16384,1000,9.63,38.24,30.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,32768,1000,14.58,44.73,30.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,65536,640,27.04,70.35,51.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,131072,320,52.99,131.5,96.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,262144,160,103.78,232.69,185.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,524288,80,214.14,502.57,402.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,1048576,40,368.09,1490.89,1267.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,2097152,20,746.24,2907.65,2538.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,18,4194304,10,1488.33,5803.03,5087.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,0,1000,0.05,0.05,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,4,1000,0.25,1.2,0.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,8,1000,0.27,1.26,0.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,16,1000,0.26,1.34,0.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,32,1000,0.27,1.33,0.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,64,1000,0.27,1.61,0.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,128,1000,0.27,1.85,0.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,256,1000,0.27,2.04,0.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,512,1000,0.27,2.08,0.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,1024,1000,0.3,2.62,0.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,2048,1000,0.39,3.5,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,4096,1000,0.83,5.35,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,8192,1000,1.77,8.93,2.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,16384,1000,7.2,16.6,9.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,32768,1000,12.24,24.8,15.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,65536,640,22.87,40.7,29.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,131072,320,43.33,71.45,52.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,262144,160,84.33,132.88,98.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,524288,80,127.96,202.92,154.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,1048576,40,256.43,380.55,287.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,2097152,20,527.84,731.2,563.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,36,4194304,10,1050.83,1422.88,1115.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,0,1000,0.25,0.37,0.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,4,1000,0.68,3.48,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,8,1000,0.68,3.44,1.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,16,1000,0.76,3.66,1.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,32,1000,0.77,4.2,2.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,64,1000,2.29,4.55,3.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,128,1000,3.69,4.84,4.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,256,1000,4.01,5.2,4.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,512,1000,4.78,5.92,5.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,1024,1000,4.32,5.42,4.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,2048,1000,5.11,6.31,5.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,4096,1000,6.68,8.0,7.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,8192,1000,9.32,11.15,9.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,16384,1000,14.89,17.49,15.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,32768,1000,26.54,30.48,27.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,65536,640,48.78,55.02,50.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,131072,320,87.43,96.48,89.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,262144,160,145.04,168.92,161.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,524288,80,258.31,259.53,258.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,1048576,40,502.98,507.19,505.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,2097152,20,993.27,1001.74,996.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,18,4194304,10,2092.71,2115.51,2103.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,4,1000,0.25,1.43,0.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,8,1000,0.26,1.46,0.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,16,1000,0.26,1.48,0.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,32,1000,0.27,1.52,0.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,64,1000,0.27,2.11,0.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,128,1000,0.27,2.52,0.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,256,1000,0.27,2.62,0.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,512,1000,0.27,2.74,0.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,1024,1000,0.31,4.74,0.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,2048,1000,0.38,4.44,0.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,4096,1000,0.8,6.84,1.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,8192,1000,1.62,12.07,2.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,16384,1000,6.78,19.6,9.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,32768,1000,12.14,30.17,16.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,65536,640,26.37,51.64,32.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,131072,320,43.88,79.11,52.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,262144,160,84.36,147.44,99.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,524288,80,95.59,245.77,173.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,1048576,40,189.95,432.36,310.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,2097152,20,359.63,808.35,597.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,72,4194304,10,713.68,1551.8,1174.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,1,1000,7.03,7.47,7.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,2,1000,7.12,7.67,7.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,4,1000,7.34,7.91,7.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,8,1000,7.87,8.45,8.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,16,1000,8.31,8.93,8.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,32,1000,8.59,9.33,8.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,64,1000,9.99,11.15,10.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,128,1000,10.64,12.16,11.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,256,1000,12.04,13.45,12.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,512,1000,17.39,17.68,17.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,1024,1000,22.53,22.84,22.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,2048,1000,37.07,38.06,37.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,4096,1000,65.43,67.36,66.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,8192,1000,120.45,124.33,122.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,16384,1000,241.11,243.53,242.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,32768,1000,477.98,480.59,479.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,65536,640,946.26,952.75,949.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,131072,320,1521.2,1572.32,1546.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,262144,160,2549.9,2567.52,2558.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,524288,80,4960.89,5018.34,4999.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,1048576,40,9796.33,9842.67,9824.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,2097152,20,20132.48,20326.45,20281.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,18,4194304,10,39836.47,40150.2,40050.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,1,1000,10.56,11.33,10.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,2,1000,10.87,11.8,11.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,4,1000,11.63,12.58,11.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,8,1000,11.92,12.93,12.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,16,1000,12.27,13.23,12.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,32,1000,13.17,14.19,13.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,64,1000,14.7,15.36,15.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,128,1000,18.32,19.2,18.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,256,1000,26.85,28.97,28.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,512,1000,34.28,35.47,34.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,1024,1000,48.4,49.86,48.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,2048,1000,75.39,77.5,76.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,4096,1000,131.5,133.71,132.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,8192,1000,244.17,249.06,247.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,16384,1000,468.64,474.06,471.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,32768,1000,925.85,933.25,928.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,65536,640,1557.74,1602.48,1579.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,131072,320,2595.45,2623.56,2611.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,262144,160,5148.82,5222.07,5189.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,524288,80,10261.67,10340.63,10311.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,1048576,40,19782.08,19877.74,19832.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,2097152,20,39220.55,39423.33,39344.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,4194304,10,78163.93,78545.67,78444.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,72,0,1000,1.22,3.23,2.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,1,1000,2.17,38.15,7.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,2,1000,2.24,12.64,4.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,4,1000,2.25,12.87,4.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,8,1000,2.23,12.93,4.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,16,1000,2.25,23.21,5.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,32,1000,2.25,15.11,5.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,64,1000,2.26,16.15,5.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,128,1000,2.33,19.18,5.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,256,1000,2.33,22.94,5.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,512,1000,2.51,28.79,6.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,1024,1000,11.86,57.56,31.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,2048,1000,14.99,82.03,39.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,4096,1000,32.31,100.87,57.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,8192,1000,72.73,165.0,114.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,16384,1000,90.44,267.71,178.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,32768,1000,57.58,335.4,189.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,65536,640,67.0,552.93,291.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,131072,320,105.94,1076.24,542.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,262144,160,195.31,1896.45,958.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,524288,80,2004.02,3694.74,2946.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,1048576,40,5668.09,7423.56,6672.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,2097152,20,15340.95,17478.82,16562.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,72,4194304,10,31275.55,33070.04,32319.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,0,1000,0.59,0.65,0.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,1,1000,6.3,6.96,6.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,2,1000,6.76,7.5,7.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,4,1000,7.76,9.0,8.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,8,1000,8.48,9.44,8.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,16,1000,8.87,9.98,9.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,32,1000,9.92,11.81,10.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,64,1000,11.27,13.64,12.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,128,1000,26.07,29.19,27.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,256,1000,28.99,33.14,31.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,512,1000,49.53,55.43,52.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,1024,1000,68.12,73.89,71.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,2048,1000,99.94,107.01,103.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,4096,1000,98.62,110.91,104.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,8192,1000,144.12,161.69,150.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,16384,1000,206.17,210.9,208.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,32768,1000,353.49,385.81,367.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,65536,640,931.75,1045.97,1007.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,131072,320,2074.52,2436.28,2294.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,262144,160,4633.0,5249.03,5014.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,524288,80,11994.79,12440.67,12261.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,1048576,40,24603.27,25875.58,25357.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,2097152,20,55639.78,59815.78,58503.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,54,4194304,10,114989.56,121604.25,119202.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,54,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,1,1000,0.47,4.36,1.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,2,1000,0.49,4.63,1.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,4,1000,0.51,4.96,1.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,8,1000,0.54,5.64,1.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,16,1000,0.56,6.06,1.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,32,1000,0.48,5.24,1.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,64,1000,0.5,5.7,1.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,128,1000,0.49,6.82,1.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,256,1000,0.49,7.71,1.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,512,1000,0.64,10.35,1.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,1024,1000,0.64,18.14,2.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,2048,1000,0.85,38.66,4.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,4096,1000,1.56,72.2,7.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,8192,1000,1.81,87.5,11.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,16384,1000,11.5,168.46,20.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,32768,1000,24.63,251.58,38.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,65536,640,21.66,420.76,42.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,131072,320,37.64,772.0,70.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,262144,160,79.33,1481.83,137.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,524288,80,171.49,2855.87,274.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,1048576,40,366.28,5533.62,566.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,2097152,20,3677.86,11194.31,4263.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gather,54,4194304,10,14638.59,22260.71,15226.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,216,0,1000,1.06,1.14,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,4,1000,1.58,23.43,2.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,8,1000,1.57,16.56,2.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,16,1000,1.6,19.89,2.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,32,1000,1.36,34.94,4.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,64,1000,1.38,18.69,4.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,128,1000,1.39,28.66,6.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,256,1000,1.4,20.03,7.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,512,1000,1.51,34.76,18.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,1024,1000,21.8,38.18,29.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,2048,1000,18.72,31.95,23.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,4096,1000,21.06,36.59,28.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,8192,1000,42.71,63.31,52.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,16384,1000,92.67,124.7,109.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,32768,1000,111.82,157.28,138.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,65536,640,248.43,331.1,283.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,131072,320,330.67,499.02,421.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,262144,160,646.72,737.16,682.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,524288,80,918.46,1016.54,957.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,1048576,40,1484.9,1604.68,1533.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,2097152,20,2605.12,2733.4,2671.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce_scatter,216,4194304,10,3279.59,3935.46,3551.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gatherv,18,0,1000,0.79,1.91,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,1,1000,0.95,6.41,1.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,2,1000,1.04,6.59,2.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,4,1000,1.04,6.67,2.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,8,1000,1.11,6.67,2.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,16,1000,1.15,6.91,2.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,32,1000,1.15,6.92,2.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,64,1000,1.16,6.91,2.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,128,1000,0.95,6.42,1.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,256,1000,0.96,6.93,1.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,512,1000,1.35,9.96,2.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,1024,1000,1.66,11.56,2.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,2048,1000,2.31,15.02,3.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,4096,1000,3.6,21.98,5.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,8192,1000,5.69,36.95,8.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,16384,1000,37.7,61.91,49.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,32768,1000,39.96,101.38,67.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,65536,640,80.82,155.26,117.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,131072,320,90.55,271.27,177.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,262144,160,64.02,521.65,117.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,524288,80,669.3,999.59,849.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,1048576,40,1542.1,1886.15,1735.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,2097152,20,3387.94,3764.65,3608.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,18,4194304,10,7184.55,7557.69,7406.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,216,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,1,1000,1.1,7.0,4.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,2,1000,1.17,8.11,5.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,4,1000,1.19,9.04,5.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,8,1000,1.19,8.17,5.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,16,1000,2.13,9.76,6.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,32,1000,3.18,10.58,7.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,64,1000,4.78,13.96,9.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,128,1000,7.56,16.5,12.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,256,1000,14.88,27.13,21.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,512,1000,32.24,54.05,41.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,1024,1000,45.57,87.12,66.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,2048,1000,57.91,143.63,100.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,4096,1000,75.68,212.05,163.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,8192,1000,130.62,394.38,301.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,16384,1000,232.24,702.27,511.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,32768,1000,47.17,1248.72,752.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,65536,640,40.56,824.02,459.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,131072,320,88.97,1734.43,986.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,262144,160,242.87,3185.46,2239.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,524288,80,1618.68,6301.84,4843.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,1048576,40,337.02,12415.68,9850.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,2097152,20,10295.92,24815.02,20045.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Scatter,216,4194304,10,3989.39,49659.39,37511.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,36,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,1,1000,0.36,3.03,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,2,1000,0.37,3.4,0.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,4,1000,0.37,3.26,0.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,8,1000,0.38,3.61,0.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,16,1000,0.38,3.59,0.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,32,1000,0.38,4.17,1.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,64,1000,0.38,4.08,0.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,128,1000,0.39,5.0,1.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,256,1000,0.41,6.23,1.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,512,1000,0.59,7.52,1.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,1024,1000,1.91,21.06,2.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,2048,1000,2.77,28.25,3.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,4096,1000,5.07,43.53,6.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,8192,1000,7.66,72.58,10.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,16384,1000,6.06,129.17,19.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,32768,1000,9.18,238.72,33.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,65536,640,21.37,285.38,42.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,131072,320,38.04,519.83,66.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,262144,160,77.38,1002.91,124.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,524288,80,159.03,1931.28,242.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,1048576,40,331.35,3716.84,485.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,2097152,20,2454.3,7170.64,2875.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,36,4194304,10,9768.3,14523.06,10162.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,4,1000,0.27,2.22,0.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,8,1000,0.28,1.82,0.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,16,1000,0.28,1.92,0.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,32,1000,0.28,1.88,0.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,64,1000,0.3,2.72,0.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,128,1000,0.3,3.45,0.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,256,1000,0.31,3.96,0.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,512,1000,0.28,3.13,0.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,1024,1000,0.31,3.83,0.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,2048,1000,0.39,5.08,0.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,4096,1000,0.78,7.04,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,8192,1000,1.62,21.96,2.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,16384,1000,6.76,19.26,9.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,32768,1000,11.87,29.23,15.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,65536,640,26.16,47.61,31.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,131072,320,45.34,79.23,53.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,262144,160,86.43,148.85,100.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,524288,80,91.03,250.59,176.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,1048576,40,182.87,599.42,395.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,2097152,20,365.29,994.05,724.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,72,4194304,10,723.06,1549.94,1197.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,0,1000,0.59,0.66,0.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,1,1000,6.27,7.46,6.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,2,1000,7.04,7.96,7.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,4,1000,8.29,9.26,8.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,8,1000,8.6,9.58,9.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,16,1000,9.0,10.1,9.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,32,1000,10.42,12.19,11.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,64,1000,9.78,11.13,10.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,128,1000,27.15,29.05,27.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,256,1000,32.43,34.62,32.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,512,1000,55.77,58.69,56.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,1024,1000,72.34,76.04,73.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,2048,1000,91.81,96.41,93.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,4096,1000,129.21,134.26,131.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,8192,1000,223.22,233.64,228.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,16384,1000,322.07,351.37,340.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,32768,1000,621.84,693.21,666.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,65536,640,1212.65,1346.3,1290.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,131072,320,2426.64,2701.19,2573.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,262144,160,4849.74,5426.48,5193.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,524288,80,11969.67,12504.84,12255.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,1048576,40,24682.5,26380.4,25688.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,2097152,20,55733.51,59930.63,58712.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,54,4194304,10,113880.13,121585.81,118859.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,1,1000,10.42,11.16,10.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,2,1000,10.52,11.29,10.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,4,1000,11.17,11.94,11.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,8,1000,11.86,12.85,12.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,16,1000,12.02,13.19,12.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,32,1000,14.56,16.17,15.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,64,1000,16.15,17.16,16.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,128,1000,19.29,20.32,19.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,256,1000,26.98,29.9,28.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,512,1000,42.9,45.19,43.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,1024,1000,54.21,57.52,55.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,2048,1000,67.72,71.55,69.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,4096,1000,101.21,106.7,104.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,8192,1000,101.65,107.42,103.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,16384,1000,200.98,204.11,202.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,32768,1000,594.16,605.57,599.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,65536,640,1382.94,1434.67,1408.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,131072,320,2439.6,2469.06,2456.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,262144,160,5121.03,5158.28,5143.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,524288,80,10661.57,10881.91,10792.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,1048576,40,19686.66,19891.76,19786.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,2097152,20,39696.52,40232.23,40003.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,36,4194304,10,77874.21,79955.93,79239.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,1,1000,7.0,7.58,7.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,2,1000,7.09,7.55,7.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,4,1000,7.27,7.84,7.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,8,1000,7.81,8.63,7.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,16,1000,8.19,8.89,8.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,32,1000,8.4,9.22,8.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,64,1000,11.52,12.76,12.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,128,1000,11.79,13.09,12.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,256,1000,12.99,14.63,13.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,512,1000,19.87,20.58,20.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,1024,1000,24.32,25.6,24.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,2048,1000,28.37,29.93,29.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,4096,1000,29.68,31.01,30.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,8192,1000,43.01,46.62,44.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,16384,1000,81.26,83.44,82.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,32768,1000,163.14,167.13,165.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,65536,640,589.8,600.82,596.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,131072,320,1298.12,1349.35,1323.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,262144,160,2388.17,2435.6,2414.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,524288,80,4927.62,4973.19,4959.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,1048576,40,9905.37,9994.81,9955.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,2097152,20,19979.12,20129.33,20067.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,18,4194304,10,39976.42,40227.36,40145.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,0,1000,0.76,2.01,1.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,1,1000,2.49,3.49,3.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,2,1000,2.49,3.51,3.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,4,1000,2.45,3.5,3.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,8,1000,2.48,3.51,3.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,16,1000,2.47,3.56,3.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,32,1000,2.68,3.7,3.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,64,1000,2.73,3.88,3.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,128,1000,3.1,4.69,3.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,256,1000,3.78,5.61,4.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,512,1000,3.42,6.99,5.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,1024,1000,4.04,8.92,6.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,2048,1000,2.38,18.56,9.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,4096,1000,3.23,27.21,14.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,8192,1000,5.8,42.21,30.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,16384,1000,9.0,58.06,44.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,32768,1000,12.42,68.24,41.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,65536,640,21.44,99.96,62.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,131072,320,39.74,192.15,113.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,262144,160,71.82,328.88,211.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,524288,80,131.95,573.23,370.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,1048576,40,293.19,2140.01,1666.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,2097152,20,602.66,4252.02,3569.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatterv,36,4194304,10,1244.4,8324.36,6971.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,144,0,1000,0.79,0.87,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,4,1000,1.08,17.91,4.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,8,1000,1.08,15.07,4.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,16,1000,1.1,15.6,4.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,32,1000,1.08,15.97,4.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,64,1000,1.11,18.0,5.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,128,1000,1.72,20.64,7.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,256,1000,1.83,21.69,10.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,512,1000,6.77,33.63,25.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,1024,1000,12.33,25.03,18.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,2048,1000,16.44,29.63,22.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,4096,1000,19.9,34.13,26.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,8192,1000,32.25,48.64,39.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,16384,1000,59.4,99.16,75.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,32768,1000,143.38,214.09,171.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,65536,640,211.71,290.28,243.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,131072,320,330.05,463.47,397.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,262144,160,560.98,652.53,598.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,524288,80,789.12,878.93,825.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,1048576,40,1279.02,1401.21,1333.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,2097152,20,1764.23,1999.58,1858.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,144,4194304,10,2778.67,3245.09,3022.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Allgather,18,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,1,1000,2.13,2.82,2.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,2,1000,2.1,2.83,2.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,4,1000,2.2,2.96,2.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,8,1000,2.16,2.88,2.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,16,1000,2.21,2.95,2.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,32,1000,2.51,3.14,2.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,64,1000,2.93,3.68,3.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,128,1000,3.63,4.82,3.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,256,1000,9.17,9.62,9.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,512,1000,7.75,10.18,8.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,1024,1000,15.13,15.54,15.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,2048,1000,24.24,24.88,24.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,4096,1000,40.92,41.66,41.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,8192,1000,73.91,74.76,74.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,16384,1000,98.61,99.25,98.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,32768,1000,187.26,191.32,188.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,65536,640,363.09,365.85,364.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,131072,320,738.92,744.51,741.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,262144,160,1506.63,1520.7,1512.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,524288,80,3185.52,3191.47,3188.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,1048576,40,7942.21,8160.67,8075.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,2097152,20,18740.22,18901.16,18838.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgather,18,4194304,10,38666.28,38840.77,38770.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,216,0,1000,1.05,1.37,1.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,4,1000,1.59,15.57,2.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,8,1000,1.58,16.08,2.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,16,1000,1.58,18.22,2.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,32,1000,1.36,18.88,4.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,64,1000,1.36,18.26,4.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,128,1000,1.38,19.59,5.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,256,1000,1.39,20.75,7.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,512,1000,1.5,28.21,14.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,1024,1000,16.6,28.56,21.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,2048,1000,21.27,36.81,27.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,4096,1000,41.54,61.59,48.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,8192,1000,47.48,63.35,54.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,16384,1000,66.82,102.92,85.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,32768,1000,110.87,164.2,148.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,65536,640,188.21,271.64,222.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,131072,320,244.05,400.27,328.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,262144,160,548.15,638.33,584.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,524288,80,806.44,920.62,849.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,1048576,40,1528.7,1680.46,1588.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,2097152,20,3003.45,3156.73,3084.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Reduce_scatter,216,4194304,10,3198.1,3858.12,3471.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Bcast,36,0,1000,0.03,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,1,1000,0.84,2.21,1.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,2,1000,0.94,2.23,1.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,4,1000,0.87,2.14,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,8,1000,0.48,1.25,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,16,1000,0.53,1.32,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,32,1000,0.55,1.35,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,64,1000,0.9,2.25,1.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,128,1000,1.14,2.6,1.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,256,1000,0.68,2.19,1.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,512,1000,0.61,1.62,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,1024,1000,1.38,2.7,2.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,2048,1000,1.81,3.33,3.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,4096,1000,1.89,4.16,2.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,8192,1000,3.84,6.3,4.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,16384,1000,7.09,9.48,7.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,32768,1000,12.42,14.74,12.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,65536,640,24.66,27.54,25.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,131072,320,47.05,49.88,47.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,262144,160,92.77,95.43,93.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,524288,80,177.75,180.35,178.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,1048576,40,366.1,369.14,366.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,2097152,20,715.05,717.69,716.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,36,4194304,10,1436.49,1438.47,1436.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,0,1000,0.28,0.33,0.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,1,1000,3.47,3.93,3.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,2,1000,3.51,3.97,3.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,4,1000,3.55,4.06,3.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,8,1000,3.65,4.18,3.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,16,1000,3.82,4.44,4.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,32,1000,4.18,4.72,4.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,64,1000,4.95,5.83,5.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,128,1000,9.52,10.68,9.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,256,1000,10.99,12.21,11.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,512,1000,14.58,15.36,14.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,1024,1000,17.78,18.27,18.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,2048,1000,25.64,26.46,25.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,4096,1000,43.79,44.57,44.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,8192,1000,76.09,77.16,76.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,16384,1000,111.16,112.66,112.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,32768,1000,201.49,202.83,201.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,65536,640,394.49,398.08,395.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,131072,320,789.94,797.7,793.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,262144,160,1625.93,1637.49,1630.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,524288,80,3527.56,3627.6,3580.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,1048576,40,8404.81,8819.98,8644.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,2097152,20,18689.46,19736.1,19295.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,18,4194304,10,38557.28,40645.62,39786.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,216,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,4,1000,6.71,9.94,8.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,8,1000,6.31,17.91,15.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,16,1000,5.96,9.06,7.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,32,1000,5.91,9.01,7.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,64,1000,7.46,12.72,9.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,128,1000,8.66,15.93,11.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,256,1000,9.84,17.2,12.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,512,1000,10.46,17.23,13.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,1024,1000,12.15,18.61,15.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,2048,1000,15.07,22.11,18.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,4096,1000,22.12,30.53,25.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,8192,1000,37.9,44.25,40.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,16384,1000,75.67,89.77,81.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,32768,1000,59.15,80.24,68.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,65536,640,85.05,114.56,97.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,131072,320,141.56,187.31,161.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,262144,160,247.61,320.25,278.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,524288,80,439.26,549.79,492.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,1048576,40,1451.71,1594.35,1518.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,2097152,20,2980.01,3093.91,3038.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allreduce,216,4194304,10,5113.23,5202.83,5153.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gather,72,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,1,1000,0.38,5.47,1.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,2,1000,0.39,15.02,1.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,4,1000,0.41,5.42,1.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,8,1000,0.42,49.27,3.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,16,1000,0.42,14.2,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,32,1000,0.39,6.1,1.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,64,1000,0.38,6.36,1.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,128,1000,0.39,7.09,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,256,1000,0.42,9.03,1.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,512,1000,0.57,12.88,1.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,1024,1000,0.6,25.74,2.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,2048,1000,0.82,40.18,4.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,4096,1000,1.35,89.39,8.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,8192,1000,3.66,128.99,13.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,16384,1000,5.45,233.85,21.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,32768,1000,9.93,332.49,31.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,65536,640,21.22,567.16,42.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,131072,320,46.04,1034.71,79.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,262144,160,94.3,1967.76,155.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,524288,80,191.74,3836.11,312.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,1048576,40,419.46,7654.25,664.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,2097152,20,4769.1,15371.15,5574.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,4194304,10,19836.06,30400.6,20574.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatterv,144,0,1000,6.37,13.27,9.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,1,1000,6.37,12.64,9.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,2,1000,6.44,12.79,9.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,4,1000,6.44,12.73,9.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,8,1000,6.58,29.27,10.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,16,1000,7.32,13.91,10.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,32,1000,8.33,14.13,11.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,64,1000,9.23,17.33,13.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,128,1000,9.63,18.85,13.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,256,1000,11.2,23.4,16.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,512,1000,11.97,69.27,27.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,1024,1000,14.26,37.97,30.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,2048,1000,15.6,68.12,50.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,4096,1000,11.95,142.62,95.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,8192,1000,37.12,269.15,169.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,16384,1000,46.88,524.35,332.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,32768,1000,48.05,727.07,421.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,65536,640,52.39,1460.49,819.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,131072,320,69.22,2385.77,1307.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,262144,160,443.0,6809.16,4294.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,524288,80,832.47,22974.65,12084.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,1048576,40,1122.77,36501.12,19372.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,2097152,20,1841.77,81356.52,42951.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,4194304,10,4170.49,157157.02,83149.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,288,0,1000,3.53,10.33,3.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,1,1000,23.26,30.5,26.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,2,1000,25.18,33.55,29.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,4,1000,25.69,33.52,29.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,8,1000,29.14,41.44,34.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,16,1000,37.63,62.74,51.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,32,1000,45.66,63.02,56.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,64,1000,87.17,111.32,104.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,128,1000,102.74,143.91,135.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,256,1000,139.8,205.66,193.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,512,1000,244.93,331.01,305.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,1024,1000,400.63,439.26,432.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,2048,1000,505.54,537.69,528.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,4096,1000,800.46,1008.33,897.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,8192,1000,1264.62,1383.39,1326.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,16384,1000,2428.4,2722.04,2581.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,32768,1000,4814.86,5604.03,5203.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,65536,640,8651.91,10277.76,9510.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,131072,202,15595.83,18397.31,16987.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,262144,160,30691.21,34761.97,32693.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,524288,80,61061.37,63044.22,62040.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,1048576,40,131233.57,135676.75,132779.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,2097152,20,304696.92,313825.51,309248.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgatherv,288,4194304,10,620738.48,660739.87,637976.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,1,1000,13.1,21.18,16.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,2,1000,16.5,24.32,19.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,4,1000,16.71,26.6,20.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,8,1000,20.92,34.72,26.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,16,1000,21.46,39.34,29.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,32,1000,26.74,38.22,34.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,64,1000,74.24,99.84,90.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,128,1000,60.5,102.38,92.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,256,1000,104.56,173.24,159.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,512,1000,202.39,286.34,260.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,1024,1000,419.65,460.3,449.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,2048,1000,559.28,655.57,601.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,4096,1000,1010.54,1067.63,1032.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,8192,1000,1255.51,1394.97,1323.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,16384,1000,2395.52,2748.34,2580.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,32768,1000,4818.53,5588.47,5183.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,65536,640,9364.05,11096.15,10191.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,131072,208,16448.59,20501.72,18297.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,262144,160,31599.56,42761.49,35827.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,524288,80,59869.81,61255.19,60465.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,1048576,40,132026.07,134470.34,133028.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,2097152,20,303934.57,312841.77,308303.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Allgather,288,4194304,10,619482.11,667062.39,637006.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,18,0,1000,0.25,0.34,0.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,4,1000,0.68,3.34,1.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,8,1000,0.68,3.4,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,16,1000,0.73,3.5,1.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,32,1000,0.77,4.07,2.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,64,1000,2.23,4.36,3.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,128,1000,3.53,4.61,3.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,256,1000,3.85,4.84,4.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,512,1000,4.65,5.82,5.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,1024,1000,5.36,6.87,5.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,2048,1000,5.96,7.6,6.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,4096,1000,7.44,9.32,8.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,8192,1000,9.86,12.08,10.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,16384,1000,15.8,19.02,16.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,32768,1000,28.58,33.25,30.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,65536,640,53.14,59.95,55.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,131072,320,97.23,107.64,100.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,262144,160,187.96,226.59,212.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,524288,80,167.69,170.84,168.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,1048576,40,311.15,319.02,314.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,2097152,20,753.63,763.57,758.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,4194304,10,1867.41,1890.9,1878.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatter,36,0,1000,0.03,0.04,0.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,1,1000,0.76,1.78,1.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,2,1000,0.74,1.78,1.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,4,1000,0.75,1.8,1.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,8,1000,0.75,1.87,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,16,1000,0.78,1.69,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,32,1000,0.89,1.82,1.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,64,1000,0.89,2.0,1.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,128,1000,0.95,2.95,2.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,256,1000,1.83,3.48,2.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,512,1000,1.58,5.19,3.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,1024,1000,2.18,6.94,4.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,2048,1000,2.75,10.75,7.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,4096,1000,3.94,17.16,11.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,8192,1000,4.75,41.87,30.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,16384,1000,7.58,57.23,43.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,32768,1000,11.55,72.05,43.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,65536,640,20.24,100.45,61.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,131072,320,39.04,174.79,110.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,262144,160,72.33,313.55,199.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,524288,80,133.0,562.1,366.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,1048576,40,356.58,2173.16,1699.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,2097152,20,811.81,4138.61,3480.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,36,4194304,10,1329.5,8440.61,7131.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,0,1000,0.94,2.36,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,1,1000,1.67,8.16,3.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,2,1000,1.76,8.54,3.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,4,1000,1.91,9.47,3.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,8,1000,1.92,9.43,3.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,16,1000,1.9,9.61,3.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,32,1000,1.91,10.46,3.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,64,1000,1.94,11.69,4.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,128,1000,1.64,10.51,3.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,256,1000,4.33,14.4,8.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,512,1000,4.69,18.27,11.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,1024,1000,5.87,21.97,13.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,2048,1000,7.73,28.79,17.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,4096,1000,11.34,44.39,26.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,8192,1000,42.98,75.25,57.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,16384,1000,36.88,125.2,79.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,32768,1000,90.13,187.07,138.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,65536,640,83.58,299.34,182.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,131072,320,134.84,554.93,328.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,262144,160,235.61,1004.22,589.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,524288,80,1184.28,1911.52,1578.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,1048576,40,2902.8,3648.6,3314.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,2097152,20,6472.57,7228.6,6897.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,36,4194304,10,13874.88,14630.25,14298.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,0,1000,1.91,3.55,2.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,1,1000,6.98,30.37,16.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,2,1000,7.21,31.14,17.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,4,1000,7.02,31.05,17.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,8,1000,7.09,31.04,17.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,16,1000,7.06,31.02,17.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,32,1000,7.26,31.28,17.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,64,1000,6.61,26.33,15.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,128,1000,6.37,23.93,14.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,256,1000,6.74,24.78,14.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,512,1000,9.08,30.54,18.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,1024,1000,10.23,37.77,22.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,2048,1000,13.73,49.76,29.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,4096,1000,28.78,84.5,48.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,8192,1000,61.39,134.12,92.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,16384,1000,42.34,191.91,111.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,32768,1000,63.62,274.85,165.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,65536,640,91.5,432.53,245.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,131072,320,148.21,778.96,429.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,262144,160,271.41,1481.66,812.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,524288,80,1710.39,2878.45,2340.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,1048576,40,4358.8,5565.48,5027.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,2097152,20,10025.93,11199.61,10661.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,4194304,10,21023.03,22218.02,21679.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,54,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,1,1000,5.18,6.49,5.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,2,1000,5.68,7.21,6.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,4,1000,6.67,8.75,7.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,8,1000,6.93,9.17,7.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,16,1000,7.54,10.84,9.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,32,1000,8.15,11.59,9.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,64,1000,9.77,13.34,11.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,128,1000,11.32,16.24,14.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,256,1000,15.44,21.98,18.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,512,1000,20.98,32.26,27.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,1024,1000,52.2,58.34,55.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,2048,1000,83.78,90.71,87.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,4096,1000,153.51,159.32,156.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,8192,1000,309.92,318.77,313.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,16384,1000,206.15,208.21,206.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,32768,1000,347.34,382.68,362.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,65536,640,965.65,1076.29,1036.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,131072,320,2125.6,2490.65,2345.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,262144,160,4618.96,5329.9,5024.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,524288,80,11839.84,12823.81,12438.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,1048576,40,24616.84,25934.86,25554.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,2097152,20,56032.83,59667.76,58608.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,54,4194304,10,113582.09,121050.34,118677.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,1,1000,20.89,30.11,28.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,2,1000,19.34,21.07,20.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,4,1000,19.89,30.44,23.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,8,1000,22.22,37.85,30.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,16,1000,24.38,38.02,35.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,32,1000,25.52,28.03,26.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,64,1000,29.19,31.45,30.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,128,1000,37.43,41.22,39.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,256,1000,73.12,80.88,77.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,512,1000,109.73,128.24,119.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,1024,1000,135.38,154.84,145.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,2048,1000,106.77,113.96,109.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,4096,1000,168.1,177.11,172.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,8192,1000,304.75,316.08,309.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,16384,1000,841.01,873.5,856.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,32768,1000,1761.67,1821.59,1788.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,65536,640,2792.8,2841.78,2820.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,131072,320,7048.68,7373.66,7245.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,262144,160,13673.14,13940.46,13829.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,524288,80,22166.93,22467.83,22307.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,1048576,40,41012.11,41712.89,41329.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,2097152,20,89283.87,89854.95,89682.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,4194304,10,174227.89,175550.34,174960.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,1,1000,1.1,2.64,2.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,2,1000,1.12,2.64,2.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,4,1000,1.15,2.82,2.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,8,1000,0.6,1.81,0.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,16,1000,0.62,1.63,0.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,32,1000,0.69,1.79,1.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,64,1000,1.49,4.09,1.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,128,1000,2.11,13.15,2.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,256,1000,2.15,4.7,2.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,512,1000,2.36,4.89,2.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,1024,1000,2.72,15.06,3.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,2048,1000,3.94,9.92,9.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,4096,1000,4.11,6.51,4.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,8192,1000,5.89,8.48,6.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,16384,1000,9.42,20.97,10.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,32768,1000,16.42,19.69,17.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,65536,640,30.1,34.54,31.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,131072,320,48.75,55.67,49.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,262144,160,82.29,85.08,83.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,524288,80,139.03,142.25,139.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,1048576,40,194.09,196.17,194.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,2097152,20,415.19,419.28,416.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,72,4194304,10,1163.54,1184.87,1165.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,288,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,1,1000,59.27,66.29,62.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,2,1000,62.2,68.66,65.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,4,1000,66.87,74.95,69.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,8,1000,73.65,86.94,79.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,16,1000,115.31,148.41,132.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,32,1000,102.54,117.68,112.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,64,1000,172.26,192.79,184.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,128,1000,302.71,354.85,335.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,256,1000,812.72,834.17,823.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,512,1000,1130.68,1145.23,1136.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,1024,1000,1965.56,2031.13,1995.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,2048,1000,3388.53,3431.41,3410.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,4096,1000,5882.16,5899.17,5890.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,8192,891,11605.81,11628.38,11614.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,16384,448,22949.37,23005.75,22971.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,32768,224,45328.36,45488.36,45395.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,65536,6,1700506.09,1733943.57,1718711.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,131072,6,177093.78,177440.23,177263.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,262144,5,348833.89,349357.15,348982.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,524288,5,692783.56,693300.65,693050.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,1048576,4,1381423.48,1382756.33,1382224.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Alltoall,288,2097152,3,2752073.09,2754682.93,2753489.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,72,0,1000,0.44,0.83,0.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,4,1000,0.92,5.35,1.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,8,1000,0.93,5.37,1.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,16,1000,1.02,12.61,2.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,32,1000,1.08,7.9,2.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,64,1000,1.27,31.02,8.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,128,1000,1.3,8.67,4.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,256,1000,3.32,10.43,8.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,512,1000,8.07,10.0,8.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,1024,1000,12.34,14.38,13.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,2048,1000,7.75,9.61,8.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,4096,1000,8.77,10.47,9.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,8192,1000,15.52,19.5,17.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,16384,1000,19.84,22.61,20.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,32768,1000,30.4,34.59,31.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,65536,640,65.06,74.15,68.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,131072,320,95.53,106.64,98.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,262144,160,184.96,203.94,191.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,524288,80,401.7,406.85,403.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,1048576,40,735.09,741.77,738.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,2097152,20,1302.84,1320.57,1309.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,72,4194304,10,2490.62,2548.18,2515.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce_scatter,288,0,1000,1.27,1.36,1.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,4,1000,1.76,13.11,2.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,8,1000,1.82,14.57,2.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,16,1000,1.84,16.89,2.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,32,1000,1.58,20.09,5.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,64,1000,1.6,20.87,6.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,128,1000,1.62,22.5,6.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,256,1000,2.71,23.55,9.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,512,1000,2.77,26.92,12.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,1024,1000,8.83,27.84,20.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,2048,1000,23.08,35.28,28.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,4096,1000,31.63,43.35,37.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,8192,1000,52.08,66.27,58.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,16384,1000,94.37,114.35,103.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,32768,1000,175.87,200.82,190.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,65536,640,256.35,335.4,290.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,131072,320,309.84,477.15,400.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,262144,160,679.39,774.82,717.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,524288,80,1114.05,1221.96,1159.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,1048576,40,1459.42,1569.08,1505.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,2097152,20,2454.11,2576.23,2508.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce_scatter,288,4194304,10,3660.57,4163.46,3907.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,1,1000,0.5,12.98,1.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,2,1000,0.56,17.14,1.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,4,1000,0.57,17.19,1.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,8,1000,0.56,22.72,1.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,16,1000,0.56,23.69,1.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,32,1000,0.56,21.76,1.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,64,1000,0.58,27.61,1.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,128,1000,0.6,32.83,2.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,256,1000,0.6,45.29,2.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,512,1000,0.83,77.48,3.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,1024,1000,0.99,377.7,14.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,2048,1000,1.1,242.47,8.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,4096,1000,1.76,318.43,12.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,8192,1000,3.1,602.05,23.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,16384,1000,5.58,1091.61,40.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,32768,1000,10.4,2477.89,76.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,65536,640,23.22,2100.38,1134.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,131072,320,51.43,3844.8,2009.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,262144,160,123.48,7419.67,3890.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,524288,80,253.5,15494.47,8286.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,1048576,40,122.37,30466.17,16041.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,2097152,20,4335.49,62044.98,34531.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,288,4194304,10,11957.2,108855.33,57664.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce,54,0,1000,0.05,0.07,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,4,1000,0.23,1.81,0.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,8,1000,0.23,1.8,0.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,16,1000,0.24,1.81,0.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,32,1000,0.23,1.8,0.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,64,1000,0.24,1.99,0.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,128,1000,0.22,2.19,0.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,256,1000,0.23,2.47,0.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,512,1000,0.24,2.6,0.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,1024,1000,0.28,2.98,0.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,2048,1000,0.4,3.62,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,4096,1000,0.78,5.29,1.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,8192,1000,1.65,9.11,2.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,16384,1000,4.68,15.29,8.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,32768,1000,8.8,24.95,15.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,65536,640,24.89,41.69,29.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,131072,320,44.03,70.26,50.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,262144,160,85.35,129.69,95.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,524288,80,91.34,217.54,161.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,1048576,40,179.05,395.65,297.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,2097152,20,338.25,764.13,581.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,54,4194304,10,657.03,1483.07,1153.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,216,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,1,1000,46.21,50.86,48.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,2,1000,46.02,50.69,48.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,4,1000,67.07,78.34,72.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,8,1000,53.96,61.23,58.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,16,1000,66.07,80.0,72.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,32,1000,74.56,93.91,84.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,64,1000,100.3,139.44,125.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,128,1000,181.95,237.56,214.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,256,1000,708.38,768.24,744.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,512,1000,782.59,835.69,815.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,1024,1000,1206.43,1264.41,1245.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,2048,1000,2247.74,2349.0,2316.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,4096,1000,3958.05,3989.82,3970.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,8192,1000,7910.26,7945.46,7924.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,16384,630,15985.56,16056.25,16018.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,32768,264,32070.56,32271.69,32163.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,65536,129,73914.44,75017.63,74483.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,131072,83,121466.64,121970.61,121698.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,262144,42,241121.1,241818.11,241474.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,524288,12,491238.39,492742.82,492006.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,1048576,7,982626.09,985394.12,984187.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,2097152,4,1944011.0,1949369.64,1946875.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Alltoall,216,4194304,2,3878298.88,3890369.06,3884858.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Scatter,54,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,1,1000,1.31,3.28,2.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,2,1000,1.39,3.4,2.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,4,1000,1.48,3.56,2.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,8,1000,1.64,3.86,2.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,16,1000,1.74,4.57,3.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,32,1000,1.65,3.75,2.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,64,1000,2.93,4.97,3.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,128,1000,4.4,6.95,5.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,256,1000,6.23,10.42,9.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,512,1000,5.59,9.98,7.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,1024,1000,8.8,15.21,12.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,2048,1000,14.93,26.26,21.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,4096,1000,24.38,43.43,36.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,8192,1000,45.01,75.01,63.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,16384,1000,64.63,113.17,97.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,32768,1000,33.18,346.66,269.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,65536,640,107.73,699.25,595.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,131072,320,519.15,953.22,820.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,262144,160,154.1,1533.6,1223.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,524288,80,355.21,4054.17,3575.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,1048576,40,645.34,7953.2,7092.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,2097152,20,886.27,20750.99,19026.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,54,4194304,10,2591.35,16140.76,14046.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,288,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,1,1000,0.49,16.26,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,2,1000,0.55,18.19,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,4,1000,0.55,18.07,1.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,8,1000,0.51,15.02,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,16,1000,0.47,16.84,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,32,1000,0.46,18.61,1.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,64,1000,0.48,22.82,1.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,128,1000,0.51,29.75,1.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,256,1000,0.54,40.56,2.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,512,1000,0.81,61.82,3.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,1024,1000,1.0,117.24,5.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,2048,1000,1.3,244.11,8.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,4096,1000,2.2,323.52,13.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,8192,1000,4.12,619.32,25.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,16384,1000,8.08,1124.79,46.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,32768,1000,15.56,2712.65,87.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,65536,640,37.73,2040.72,1097.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,131072,320,78.54,3751.24,1987.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,262144,160,152.36,7477.84,3974.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,524288,80,312.23,15242.41,8205.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,1048576,40,235.17,30429.29,16264.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,2097152,20,2295.87,61408.63,34554.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Gather,288,4194304,10,12417.99,106535.11,57036.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,72,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,1,1000,1.35,3.44,2.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,2,1000,1.35,3.69,2.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,4,1000,1.39,3.74,2.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,8,1000,0.79,2.18,1.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,16,1000,0.78,2.15,1.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,32,1000,0.78,2.19,1.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,64,1000,2.27,4.72,2.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,128,1000,2.7,5.26,3.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,256,1000,2.2,4.82,2.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,512,1000,1.27,2.75,1.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,1024,1000,1.37,2.9,1.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,2048,1000,2.19,4.78,4.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,4096,1000,2.04,4.73,2.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,8192,1000,3.91,6.78,4.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,16384,1000,7.29,10.46,7.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,32768,1000,13.75,16.78,14.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,65536,640,27.03,30.88,27.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,131072,320,52.14,56.48,53.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,262144,160,103.69,107.63,104.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,524288,80,203.89,214.81,204.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,1048576,40,402.58,406.98,403.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,2097152,20,771.5,994.23,802.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,72,4194304,10,1721.33,1725.82,1722.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,54,0,1000,1.8,3.34,2.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,1,1000,6.63,26.32,15.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,2,1000,7.38,31.49,17.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,4,1000,7.29,31.42,17.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,8,1000,7.26,31.39,17.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,16,1000,7.47,31.48,17.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,32,1000,7.35,31.49,17.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,64,1000,7.3,31.58,17.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,128,1000,7.51,31.5,17.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,256,1000,7.58,31.86,17.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,512,1000,9.83,36.6,20.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,1024,1000,11.16,42.11,24.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,2048,1000,13.44,52.58,29.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,4096,1000,16.18,74.94,43.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,8192,1000,47.45,122.4,85.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,16384,1000,28.09,171.03,100.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,32768,1000,56.18,295.04,174.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,65536,640,75.22,460.34,257.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,131072,320,83.35,752.14,403.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,262144,160,175.18,1426.43,757.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,524288,80,1524.19,2777.27,2239.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,1048576,40,4130.7,5411.8,4873.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,2097152,20,10057.48,11332.14,10795.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,54,4194304,10,22619.12,23892.57,23353.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,1,1000,2.6,3.52,2.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,2,1000,2.61,3.44,2.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,4,1000,2.68,3.53,2.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,8,1000,2.7,3.59,3.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,16,1000,2.88,3.81,3.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,32,1000,3.44,4.34,3.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,64,1000,4.41,5.59,4.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,128,1000,4.65,6.2,5.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,256,1000,11.66,12.17,11.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,512,1000,10.01,12.46,10.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,1024,1000,17.43,17.82,17.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,2048,1000,25.48,26.36,25.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,4096,1000,43.1,43.97,43.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,8192,1000,75.32,76.23,75.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,16384,1000,110.12,112.16,111.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,32768,1000,201.41,203.46,202.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,65536,640,391.09,393.27,392.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,131072,320,780.06,787.17,782.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,262144,160,1614.24,1624.94,1617.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,524288,80,3167.75,3177.45,3172.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,1048576,40,8140.68,8264.23,8218.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,2097152,20,19073.4,19205.85,19144.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgather,18,4194304,10,38853.05,39123.8,39039.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,288,0,1000,0.06,0.09,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,4,1000,0.35,6.69,0.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,8,1000,0.33,7.48,0.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,16,1000,0.36,8.36,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,32,1000,0.36,8.82,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,64,1000,0.35,9.49,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,128,1000,0.34,9.97,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,256,1000,0.35,11.42,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,512,1000,0.32,10.94,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,1024,1000,0.35,12.3,0.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,2048,1000,0.4,11.98,1.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,4096,1000,0.72,15.11,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,8192,1000,2.64,24.89,4.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,16384,1000,7.4,37.65,11.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,32768,1000,39.51,171.58,114.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,65536,640,83.18,198.01,148.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,131072,320,166.65,336.39,275.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,262144,160,86.65,805.14,405.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,524288,80,140.95,935.27,518.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,1048576,40,217.47,1305.97,735.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,2097152,20,493.8,1879.39,1557.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Reduce,288,4194304,10,698.58,3975.21,2141.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allgather,288,0,1000,0.03,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,1,1000,11.23,19.31,14.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,2,1000,14.07,23.44,18.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,4,1000,15.5,24.13,19.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,8,1000,18.05,30.82,23.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,16,1000,22.54,46.33,33.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,32,1000,27.16,38.31,33.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,64,1000,68.4,94.12,85.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,128,1000,56.91,86.7,73.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,256,1000,83.2,141.79,117.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,512,1000,133.73,214.25,182.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,1024,1000,240.03,357.15,324.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,2048,1000,433.57,647.54,588.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,4096,1000,834.22,1291.79,1172.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,8192,1000,1577.25,2010.49,1779.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,16384,1000,2143.52,2516.28,2335.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,32768,1000,4571.6,5345.84,4975.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,65536,640,8797.99,10460.66,9620.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,131072,320,16422.45,20797.27,18277.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,262144,160,31200.06,42933.6,35807.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,524288,80,61075.83,63026.31,61855.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,1048576,40,131196.97,134333.09,132808.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,2097152,20,307085.63,318490.46,313211.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Allgather,288,4194304,10,618191.85,643989.9,631234.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Reduce_scatter,288,0,1000,1.27,1.37,1.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,4,1000,1.75,14.65,2.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,8,1000,1.8,15.6,2.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,16,1000,1.83,17.94,2.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,32,1000,1.57,21.71,5.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,64,1000,1.59,22.73,6.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,128,1000,1.61,23.93,7.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,256,1000,2.72,25.53,9.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,512,1000,2.75,30.45,13.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,1024,1000,8.91,40.22,25.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,2048,1000,22.04,43.84,30.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,4096,1000,43.38,61.15,50.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,8192,1000,56.58,84.0,68.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,16384,1000,98.57,126.91,114.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,32768,1000,177.2,205.31,190.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,65536,640,258.11,336.97,293.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,131072,320,310.37,489.03,407.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,262144,160,701.0,791.44,735.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,524288,80,969.99,1059.92,1003.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,1048576,40,1489.88,1587.71,1530.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,2097152,20,2402.07,2516.53,2451.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Reduce_scatter,288,4194304,10,3630.74,4122.22,3868.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, 50
+Scatterv,36,0,1000,1.0,2.37,1.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,1,1000,3.07,4.42,3.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,2,1000,3.12,4.54,3.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,4,1000,3.26,4.71,4.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,8,1000,3.39,4.88,4.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,16,1000,3.61,5.32,4.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,32,1000,4.21,6.04,5.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,64,1000,4.35,6.36,5.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,128,1000,4.82,7.82,6.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,256,1000,5.61,8.83,7.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,512,1000,5.54,10.93,8.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,1024,1000,6.73,13.6,10.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,2048,1000,3.05,35.44,17.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,4096,1000,3.83,50.61,24.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,8192,1000,5.28,73.96,51.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,16384,1000,7.55,98.12,70.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,32768,1000,7.4,158.49,113.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,65536,640,10.31,262.26,184.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,131072,320,16.79,293.71,175.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,262144,160,28.53,371.98,225.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,524288,80,58.95,1953.33,1659.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,1048576,40,452.15,4296.46,3740.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,2097152,20,657.5,4853.14,4161.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,36,4194304,10,1411.21,9943.52,8649.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,216,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,1,1000,12.52,19.43,14.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,2,1000,12.88,18.84,14.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,4,1000,17.91,26.32,20.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,8,1000,21.43,30.98,25.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,16,1000,19.34,33.0,24.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,32,1000,20.16,30.9,26.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,64,1000,42.06,72.97,59.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,128,1000,35.56,54.14,47.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,256,1000,68.74,105.96,96.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,512,1000,136.13,179.42,166.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,1024,1000,247.49,324.29,295.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,2048,1000,458.06,532.01,499.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,4096,1000,924.35,1036.24,1001.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,8192,1000,1202.29,1638.44,1415.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,16384,1000,1505.22,1775.11,1642.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,32768,1000,3297.59,4018.57,3647.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,65536,640,6328.4,8076.87,7194.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,131072,320,11758.98,15844.53,13538.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,262144,160,22350.48,32815.92,26792.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,524288,80,45379.2,48772.56,46965.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,1048576,40,99449.62,107826.15,103309.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,2097152,20,227230.18,242362.52,232758.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Allgather,216,4194304,10,474622.92,534171.66,498432.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3,NA
+Gatherv,36,0,1000,0.93,2.27,1.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,1,1000,1.53,8.08,3.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,2,1000,1.64,8.38,3.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,4,1000,1.74,8.82,3.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,8,1000,1.86,9.35,3.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,16,1000,1.84,9.89,3.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,32,1000,1.83,10.33,3.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,64,1000,1.89,11.44,4.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,128,1000,1.56,10.41,3.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,256,1000,4.3,14.54,9.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,512,1000,5.07,18.0,11.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,1024,1000,6.03,20.66,12.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,2048,1000,7.28,26.79,16.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,4096,1000,8.68,38.33,23.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,8192,1000,44.21,68.2,55.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,16384,1000,42.74,118.07,80.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,32768,1000,129.11,178.69,154.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,65536,640,71.16,290.94,177.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,131072,320,128.35,528.07,314.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,262144,160,215.77,998.57,584.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,524288,80,1212.81,1919.73,1587.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,1048576,40,2902.13,3621.14,3291.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,2097152,20,6459.1,7196.93,6868.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Gatherv,36,4194304,10,13872.48,14609.95,14278.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,0,1000,0.3,0.42,0.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,4,1000,0.55,3.23,1.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,8,1000,0.54,3.22,1.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,16,1000,0.55,3.35,1.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,32,1000,0.63,3.44,1.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,64,1000,0.64,3.81,1.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,128,1000,1.8,3.95,3.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,256,1000,3.12,4.0,3.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,512,1000,3.55,4.42,3.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,1024,1000,4.13,4.98,4.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,2048,1000,4.71,5.69,5.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,4096,1000,6.13,7.35,6.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,8192,1000,8.96,10.88,9.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,16384,1000,14.47,16.76,15.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,32768,1000,35.71,46.63,40.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,65536,640,57.12,68.82,63.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,131072,320,134.08,153.96,143.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,262144,160,137.84,172.14,160.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,524288,80,211.91,261.67,245.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,1048576,40,417.04,498.56,477.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,2097152,20,805.89,872.85,838.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,36,4194304,10,1648.72,1748.81,1694.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce,144,0,1000,0.06,0.09,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,4,1000,0.35,7.89,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,8,1000,0.35,8.14,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,16,1000,0.36,7.89,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,32,1000,0.35,8.44,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,64,1000,0.36,9.91,0.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,128,1000,0.35,9.62,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,256,1000,0.35,12.71,0.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,512,1000,0.39,13.5,1.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,1024,1000,0.4,23.25,1.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,2048,1000,0.38,28.45,1.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,4096,1000,0.43,19.58,1.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,8192,1000,2.38,29.48,5.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,16384,1000,6.81,43.15,12.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,32768,1000,13.09,60.3,20.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,65536,640,24.27,114.77,81.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,131072,320,59.81,195.68,148.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,262144,160,73.05,423.0,254.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,524288,80,104.57,649.25,388.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,1048576,40,237.54,1147.16,707.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,2097152,20,357.42,2140.04,1210.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Reduce,144,4194304,10,707.8,3351.14,2003.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allreduce,36,0,1000,0.05,0.05,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,4,1000,1.77,2.13,1.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,8,1000,1.8,2.59,2.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,16,1000,1.9,2.48,2.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,32,1000,2.09,2.97,2.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,64,1000,2.61,3.96,2.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,128,1000,3.37,5.09,3.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,256,1000,3.77,5.59,4.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,512,1000,3.97,6.04,4.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,1024,1000,5.44,7.68,5.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,2048,1000,7.13,9.35,7.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,4096,1000,10.12,11.95,10.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,8192,1000,13.15,18.22,17.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,16384,1000,21.94,29.28,28.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,32768,1000,53.69,55.66,54.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,65536,640,47.05,48.31,47.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,131072,320,57.5,59.37,58.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,262144,160,96.59,102.42,99.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,524288,80,173.91,191.16,185.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,1048576,40,377.23,426.28,406.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,2097152,20,826.49,927.58,894.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,36,4194304,10,1843.15,1999.73,1955.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,216,0,1000,7.93,15.35,11.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,1,1000,7.74,15.49,11.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,2,1000,7.86,15.53,11.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,4,1000,7.93,16.17,11.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,8,1000,7.31,14.7,10.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,16,1000,7.7,15.96,11.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,32,1000,8.1,16.28,11.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,64,1000,9.61,18.5,13.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,128,1000,11.22,21.21,15.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,256,1000,13.93,26.5,19.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,512,1000,18.41,34.73,28.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,1024,1000,17.44,46.86,35.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,2048,1000,22.82,69.71,53.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,4096,1000,14.67,157.82,96.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,8192,1000,37.62,277.31,162.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,16384,1000,50.48,544.53,304.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,32768,1000,61.11,953.86,535.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,65536,640,84.88,2313.57,1227.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,131072,320,88.14,3228.69,1760.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,262144,160,365.87,8492.77,4366.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,524288,80,640.19,17177.35,9606.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,1048576,40,1130.95,36827.29,20919.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,2097152,20,1436.51,77033.22,44250.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Scatterv,216,4194304,10,3992.76,155110.46,89553.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, 50
+Allgather,144,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,1,1000,9.35,12.65,11.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,2,1000,9.09,14.15,11.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,4,1000,10.0,16.49,12.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,8,1000,11.36,18.73,14.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,16,1000,15.5,22.36,18.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,32,1000,18.69,31.95,25.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,64,1000,21.94,34.56,29.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,128,1000,27.77,68.62,49.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,256,1000,48.22,84.8,76.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,512,1000,86.54,150.69,137.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,1024,1000,188.32,258.95,239.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,2048,1000,265.5,312.77,297.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,4096,1000,462.32,485.17,479.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,8192,1000,908.43,930.48,925.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,16384,1000,1088.94,1378.81,1225.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,32768,1000,2061.9,2676.54,2377.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,65536,640,4132.38,5415.56,4757.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,131072,320,8070.33,10372.25,9327.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,262144,160,14999.32,20631.63,18081.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,524288,80,29433.72,30378.78,29977.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,1048576,40,64858.95,66141.28,65576.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,2097152,20,150109.53,155486.0,152949.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgather,144,4194304,10,306648.66,316330.45,310944.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatter,72,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,1,1000,1.12,2.52,1.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,2,1000,1.11,2.57,1.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,4,1000,1.12,2.61,2.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,8,1000,1.17,2.79,2.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,16,1000,1.26,3.09,2.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,32,1000,1.26,3.9,2.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,64,1000,1.47,4.22,3.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,128,1000,1.64,6.06,4.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,256,1000,2.04,6.89,5.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,512,1000,2.88,9.23,7.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,1024,1000,4.44,13.3,10.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,2048,1000,6.11,23.45,18.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,4096,1000,3.89,108.92,52.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,8192,1000,25.94,237.58,147.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,16384,1000,29.2,269.17,191.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,32768,1000,33.68,451.03,351.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,65536,640,57.52,1011.91,873.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,131072,320,89.81,1389.35,1152.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,262144,160,185.03,2753.28,2373.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,524288,80,422.41,16324.47,15561.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,1048576,40,656.36,10912.79,10039.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,2097152,20,1222.2,12026.56,10360.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Scatter,72,4194304,10,1830.05,21817.01,18919.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,216,0,1000,2.9,8.85,3.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,1,1000,40.92,82.73,61.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,2,1000,21.2,33.27,25.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,4,1000,23.2,30.83,26.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,8,1000,24.23,32.77,27.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,16,1000,30.53,41.57,36.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,32,1000,52.5,126.49,104.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,64,1000,90.08,107.84,103.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,128,1000,117.13,151.82,138.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,256,1000,114.84,164.44,157.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,512,1000,202.04,248.03,239.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,1024,1000,317.39,422.85,392.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,2048,1000,394.33,478.98,444.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,4096,1000,590.7,753.97,678.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,8192,1000,949.35,1061.33,1002.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,16384,1000,1732.94,2022.95,1879.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,32768,1000,3395.26,4066.98,3740.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,65536,640,6065.45,7488.15,6817.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,131072,320,11297.77,13511.44,12462.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,262144,160,21485.51,25582.03,23625.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,524288,80,45139.57,46150.92,45637.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,1048576,40,99168.6,100525.82,100008.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,2097152,20,226835.68,234551.4,230410.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Allgatherv,216,4194304,10,470686.86,488158.56,479419.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Gather,144,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,1,1000,0.57,38.2,2.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,2,1000,0.57,23.75,2.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,4,1000,0.57,14.93,1.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,8,1000,0.58,16.18,1.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,16,1000,0.49,13.79,1.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,32,1000,0.5,15.58,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,64,1000,0.48,15.95,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,128,1000,0.49,20.63,1.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,256,1000,0.51,37.75,2.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,512,1000,0.67,40.73,2.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,1024,1000,0.88,98.19,5.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,2048,1000,1.35,178.67,8.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,4096,1000,2.15,276.07,11.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,8192,1000,3.49,313.0,8.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,16384,1000,7.0,538.55,13.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,32768,1000,13.61,927.82,24.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,65536,640,46.84,2926.68,999.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,131072,320,92.67,2213.22,1129.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,262144,160,179.88,3556.83,1896.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,524288,80,345.37,6700.18,3575.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,1048576,40,229.84,17950.6,9106.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,2097152,20,1887.83,27661.81,16710.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,144,4194304,10,12649.16,52520.94,32083.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,1,1000,0.7,1.76,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,2,1000,0.71,1.78,1.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,4,1000,0.7,1.78,1.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,8,1000,0.47,1.38,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,16,1000,0.44,0.84,0.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,32,1000,0.45,0.85,0.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,64,1000,0.52,1.36,0.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,128,1000,0.72,1.58,0.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,256,1000,0.65,1.57,0.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,512,1000,0.81,1.69,0.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,1024,1000,1.08,2.03,1.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,2048,1000,1.46,2.45,1.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,4096,1000,2.19,3.23,2.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,8192,1000,3.78,4.89,4.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,16384,1000,7.44,8.66,7.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,32768,1000,12.93,14.21,13.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,65536,640,24.78,26.25,25.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,131072,320,45.91,47.38,46.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,262144,160,88.02,89.53,88.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,524288,80,172.4,173.92,172.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,1048576,40,202.8,203.95,203.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,2097152,20,399.99,402.57,400.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,18,4194304,10,1074.55,1075.95,1074.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,18,0,1000,0.25,0.28,0.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,4,1000,0.67,3.33,1.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,8,1000,0.68,3.39,1.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,16,1000,0.71,3.5,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,32,1000,0.75,3.89,2.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,64,1000,2.06,4.11,3.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,128,1000,3.33,4.43,3.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,256,1000,3.62,4.78,3.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,512,1000,4.52,5.68,4.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,1024,1000,4.3,5.33,4.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,2048,1000,5.01,6.27,5.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,4096,1000,6.57,7.91,6.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,8192,1000,9.33,11.21,9.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,16384,1000,14.91,17.67,15.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,32768,1000,26.46,30.49,27.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,65536,640,47.95,54.51,49.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,131072,320,85.21,94.61,87.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,262144,160,144.34,168.83,160.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,524288,80,259.24,260.52,259.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,1048576,40,496.84,501.82,499.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,2097152,20,982.9,990.78,987.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Reduce_scatter,18,4194304,10,2040.38,2064.08,2051.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,36,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,1,1000,10.47,11.12,10.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,2,1000,10.56,11.23,10.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,4,1000,11.26,12.12,11.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,8,1000,11.94,12.94,12.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,16,1000,12.33,13.3,12.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,32,1000,15.37,16.6,16.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,64,1000,14.66,15.31,15.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,128,1000,18.48,19.24,18.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,256,1000,26.88,29.22,28.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,512,1000,34.22,35.56,34.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,1024,1000,48.45,49.76,48.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,2048,1000,75.43,77.23,76.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,4096,1000,132.31,134.12,133.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,8192,1000,244.6,248.45,246.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,16384,1000,469.59,474.04,471.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,32768,1000,927.61,937.71,933.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,65536,640,1572.01,1607.79,1590.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,131072,320,2771.74,2822.89,2806.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,262144,160,5115.38,5151.4,5129.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,524288,80,10297.74,10594.55,10492.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,1048576,40,20426.62,20782.57,20657.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,2097152,20,42617.69,43064.06,42797.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,36,4194304,10,79391.57,80386.64,79954.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,1,1000,0.79,1.84,1.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,2,1000,0.81,1.91,1.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,4,1000,0.8,1.89,1.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,8,1000,0.49,0.86,0.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,16,1000,0.47,0.84,0.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,32,1000,0.51,0.92,0.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,64,1000,0.34,1.16,0.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,128,1000,0.47,1.33,0.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,256,1000,0.59,1.49,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,512,1000,0.73,1.64,0.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,1024,1000,0.6,1.38,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,2048,1000,1.14,2.43,1.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,4096,1000,1.64,3.52,2.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,8192,1000,3.53,5.83,4.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,16384,1000,7.85,10.56,8.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,32768,1000,13.58,16.13,14.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,65536,640,25.81,28.36,26.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,131072,320,47.29,49.35,47.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,262144,160,92.25,94.29,92.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,524288,80,180.19,182.46,180.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,1048576,40,360.54,370.72,362.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,2097152,20,733.63,736.42,734.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Bcast,18,4194304,10,1429.31,1430.86,1429.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Reduce,54,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,4,1000,0.28,2.67,0.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,8,1000,0.28,2.92,0.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,16,1000,0.28,3.23,0.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,32,1000,0.28,3.8,0.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,64,1000,0.29,4.66,0.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,128,1000,0.28,4.94,0.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,256,1000,0.28,4.83,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,512,1000,0.28,5.19,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,1024,1000,0.31,6.07,0.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,2048,1000,0.33,7.6,1.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,4096,1000,0.37,10.31,1.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,8192,1000,0.89,16.0,2.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,16384,1000,4.76,24.95,12.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,32768,1000,8.13,36.73,20.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,65536,640,30.7,66.75,43.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,131072,320,39.49,70.03,49.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,262144,160,95.2,154.63,116.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,524288,80,156.3,266.14,210.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,1048576,40,188.23,386.84,251.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,2097152,20,326.4,702.2,495.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,54,4194304,10,668.42,1693.81,1232.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,1,1000,0.86,2.38,1.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,2,1000,0.88,2.42,1.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,4,1000,0.95,2.43,1.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,8,1000,0.57,1.27,0.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,16,1000,0.59,1.29,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,32,1000,0.62,1.51,0.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,64,1000,0.89,2.42,1.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,128,1000,1.25,2.91,1.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,256,1000,0.99,2.8,1.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,512,1000,0.96,2.75,1.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,1024,1000,2.46,4.94,4.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,2048,1000,3.33,6.33,5.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,4096,1000,2.93,4.75,3.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,8192,1000,5.32,7.14,5.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,16384,1000,9.85,11.82,10.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,32768,1000,16.71,18.57,17.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,65536,640,31.6,33.85,32.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,131072,320,30.55,31.77,30.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,262144,160,55.12,56.33,55.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,524288,80,100.34,101.52,100.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,1048576,40,189.91,191.31,190.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,2097152,20,378.61,381.1,379.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Bcast,36,4194304,10,1142.95,1144.99,1143.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce,216,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,4,1000,0.38,19.91,1.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,8,1000,0.35,17.46,0.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,16,1000,0.36,9.73,0.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,32,1000,0.36,17.79,1.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,64,1000,0.36,19.05,1.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,128,1000,0.34,11.13,0.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,256,1000,0.34,12.27,0.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,512,1000,0.32,16.27,0.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,1024,1000,0.34,13.6,0.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,2048,1000,0.4,13.47,1.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,4096,1000,0.7,16.14,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,8192,1000,2.67,25.63,4.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,16384,1000,7.39,43.2,11.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,32768,1000,42.51,128.23,81.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,65536,640,66.07,217.87,143.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,131072,320,133.53,349.23,242.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,262144,160,82.2,747.37,386.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,524288,80,143.67,939.98,506.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,1048576,40,220.71,1263.52,706.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,2097152,20,489.22,1717.99,1455.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Reduce,216,4194304,10,695.98,4002.69,2075.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,3, -1
+Alltoall,288,0,1000,0.04,0.09,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,1,1000,60.34,67.11,62.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,2,1000,63.7,72.82,66.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,4,1000,68.73,77.6,72.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,8,1000,158.08,345.65,179.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,16,1000,120.06,176.49,136.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,32,1000,118.33,147.24,134.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,64,1000,166.23,187.84,179.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,128,1000,291.79,339.86,321.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,256,1000,880.28,902.87,888.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,512,1000,1169.63,1200.31,1180.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,1024,1000,1987.34,2031.12,2006.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,2048,1000,3596.82,3639.04,3610.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,4096,1000,6344.28,6358.53,6350.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,8192,827,12828.04,12855.06,12838.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,16384,409,24180.78,24247.24,24209.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,32768,213,49489.89,49632.97,49555.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,65536,6,100056.5,101950.25,101075.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,131072,6,178760.88,179105.04,178902.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,262144,6,363300.12,364014.13,363620.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,524288,6,731401.96,737578.69,734140.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,1048576,5,1456828.29,1460317.34,1458259.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Alltoall,288,2097152,3,2902451.09,2908020.34,2904788.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4,NA
+Gather,18,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,1,1000,0.35,2.59,0.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,2,1000,0.35,2.61,0.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,4,1000,0.35,2.64,0.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,8,1000,0.36,2.71,0.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,16,1000,0.37,2.83,0.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,32,1000,0.38,2.95,0.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,64,1000,0.4,3.44,1.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,128,1000,0.44,4.42,1.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,256,1000,0.6,5.81,1.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,512,1000,0.79,7.28,2.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,1024,1000,1.51,10.22,2.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,2048,1000,2.11,13.97,3.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,4096,1000,3.24,20.24,5.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,8192,1000,5.38,31.93,8.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,16384,1000,11.38,55.43,15.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,32768,1000,17.67,95.54,27.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,65536,640,29.74,146.21,41.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,131072,320,9.82,380.08,60.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,262144,160,22.05,503.88,83.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,524288,80,64.41,978.62,148.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,1048576,40,164.84,1781.37,329.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,2097152,20,1488.18,3779.78,1806.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,18,4194304,10,5316.1,7557.24,5597.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,144,0,1000,0.79,0.87,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,4,1000,1.08,30.62,4.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,8,1000,1.08,13.97,3.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,16,1000,1.08,14.34,3.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,32,1000,1.07,14.52,4.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,64,1000,1.1,15.56,5.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,128,1000,1.7,18.69,6.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,256,1000,1.82,24.21,11.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,512,1000,6.38,29.56,23.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,1024,1000,10.98,20.82,15.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,2048,1000,13.32,23.82,18.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,4096,1000,21.24,31.31,25.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,8192,1000,30.29,44.27,36.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,16384,1000,58.23,95.68,73.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,32768,1000,144.63,214.25,172.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,65536,640,210.25,286.55,241.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,131072,320,324.05,462.34,393.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,262144,160,588.1,707.22,650.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,524288,80,821.48,917.38,861.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,1048576,40,1335.81,1461.04,1389.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,2097152,20,1783.3,2015.57,1890.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Reduce_scatter,144,4194304,10,2766.93,3273.55,2994.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,288,0,1000,7.89,14.82,10.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,1,1000,8.37,16.14,11.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,2,1000,9.34,18.37,13.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,4,1000,9.55,18.98,13.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,8,1000,8.69,16.74,12.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,16,1000,8.67,17.0,12.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,32,1000,9.58,17.13,13.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,64,1000,10.42,20.09,15.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,128,1000,12.61,23.81,18.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,256,1000,15.55,30.45,22.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,512,1000,22.04,46.08,34.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,1024,1000,21.89,62.23,46.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,2048,1000,14.78,93.72,65.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,4096,1000,14.75,136.93,91.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,8192,1000,25.31,214.66,150.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,16384,1000,30.18,402.03,279.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,32768,1000,39.67,813.91,548.45,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,65536,640,55.18,1711.51,1084.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,131072,320,238.78,2736.26,2126.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,262144,160,352.04,5884.82,4242.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,524288,80,578.86,17346.69,11410.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,1048576,40,1090.65,36193.84,24256.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,2097152,20,1393.99,72540.17,49432.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Scatterv,288,4194304,10,4012.64,151888.63,100910.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Bcast,36,0,1000,0.03,0.03,0.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,1,1000,0.68,1.81,1.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,2,1000,0.69,1.81,1.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,4,1000,0.69,1.8,1.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,8,1000,0.37,0.74,0.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,16,1000,0.37,0.75,0.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,32,1000,0.39,0.78,0.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,64,1000,0.3,1.05,0.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,128,1000,0.33,1.09,0.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,256,1000,0.26,1.03,0.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,512,1000,0.34,1.14,0.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,1024,1000,0.87,1.85,1.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,2048,1000,1.33,2.52,2.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,4096,1000,1.4,3.41,1.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,8192,1000,2.99,5.26,3.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,16384,1000,6.23,8.78,6.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,32768,1000,11.65,13.8,12.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,65536,640,23.23,25.65,23.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,131072,320,44.47,46.95,45.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,262144,160,86.9,89.38,87.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,524288,80,172.74,178.78,173.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,1048576,40,345.83,347.94,346.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,2097152,20,679.25,681.56,680.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Bcast,36,4194304,10,1357.5,1359.26,1358.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,0,1000,0.06,0.08,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,4,1000,2.73,4.16,3.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,8,1000,2.94,4.63,3.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,16,1000,3.39,5.25,4.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,32,1000,4.05,6.13,4.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,64,1000,5.53,7.97,6.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,128,1000,6.69,9.59,7.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,256,1000,6.62,9.48,7.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,512,1000,7.63,10.48,8.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,1024,1000,5.75,7.6,6.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,2048,1000,7.18,9.56,7.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,4096,1000,10.14,13.48,11.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,8192,1000,17.94,21.11,19.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,16384,1000,40.02,42.91,40.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,32768,1000,45.94,49.38,46.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,65536,640,75.83,81.51,77.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,131072,320,144.64,163.26,147.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,262144,160,242.43,250.89,244.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,524288,80,432.65,448.48,438.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,1048576,40,800.46,823.27,810.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,2097152,20,1614.63,1621.99,1615.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,54,4194304,10,3288.26,3292.86,3289.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allreduce,36,0,1000,0.05,0.06,0.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,4,1000,1.6,2.01,1.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,8,1000,1.69,2.27,1.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,16,1000,1.97,2.43,2.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,32,1000,1.81,2.43,2.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,64,1000,2.2,3.43,2.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,128,1000,2.8,4.27,3.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,256,1000,3.44,5.14,3.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,512,1000,4.12,6.28,4.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,1024,1000,3.34,4.58,3.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,2048,1000,4.55,6.48,4.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,4096,1000,7.33,9.62,7.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,8192,1000,13.39,15.42,15.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,16384,1000,23.2,25.59,25.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,32768,1000,41.79,44.63,42.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,65536,640,50.68,51.46,51.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,131072,320,91.67,93.17,92.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,262144,160,173.9,181.03,178.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,524288,80,325.14,332.02,328.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,1048576,40,649.47,662.67,657.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,2097152,20,1000.42,1041.29,1020.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allreduce,36,4194304,10,1999.97,2119.05,2064.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gatherv,144,0,1000,1.76,6.17,4.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,1,1000,17.68,94.04,53.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,2,1000,16.62,94.97,53.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,4,1000,16.77,92.19,53.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,8,1000,16.54,95.85,54.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,16,1000,17.71,103.27,54.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,32,1000,17.73,98.34,54.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,64,1000,17.6,93.35,54.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,128,1000,18.44,94.93,55.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,256,1000,18.99,97.73,55.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,512,1000,22.69,111.67,65.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,1024,1000,30.22,141.45,81.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,2048,1000,37.31,175.37,99.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,4096,1000,46.29,214.97,122.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,8192,1000,68.88,322.75,185.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,16384,1000,123.14,596.38,295.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,32768,1000,206.81,910.94,442.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,65536,640,408.12,1798.62,1147.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,131072,320,676.8,2518.15,1650.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,262144,160,1776.01,4738.02,3349.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,524288,80,4433.68,9422.68,7158.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,1048576,40,11983.89,18059.07,14905.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,2097152,20,24768.96,36886.81,30732.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gatherv,144,4194304,10,34385.08,58559.41,46356.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,54,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,1,1000,0.51,5.13,1.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,2,1000,0.55,5.67,1.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,4,1000,0.57,5.94,1.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,8,1000,0.58,6.05,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,16,1000,0.58,6.23,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,32,1000,0.48,5.27,1.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,64,1000,0.49,5.7,1.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,128,1000,0.51,7.42,1.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,256,1000,0.52,8.08,1.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,512,1000,0.64,10.41,1.74,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,1024,1000,0.62,17.6,2.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,2048,1000,0.83,41.77,4.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,4096,1000,1.61,89.36,8.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,8192,1000,1.71,83.5,9.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,16384,1000,9.74,185.71,20.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,32768,1000,18.6,260.1,37.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,65536,640,21.41,425.03,42.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,131072,320,39.95,768.91,71.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,262144,160,82.07,1493.37,139.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,524288,80,170.18,2940.41,278.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,1048576,40,358.38,5675.3,570.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,2097152,20,3761.32,11369.16,4390.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,54,4194304,10,14554.47,22202.03,15171.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,72,0,1000,0.04,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,1,1000,0.37,4.15,0.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,2,1000,0.38,4.25,1.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,4,1000,0.38,4.49,1.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,8,1000,0.39,4.89,1.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,16,1000,0.41,6.0,1.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,32,1000,0.42,8.43,1.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,64,1000,0.44,9.27,1.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,128,1000,0.46,10.38,1.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,256,1000,0.48,12.81,1.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,512,1000,0.78,26.13,2.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,1024,1000,0.92,30.3,3.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,2048,1000,0.97,44.22,4.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,4096,1000,1.35,72.81,7.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,8192,1000,4.45,139.3,16.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,16384,1000,4.32,182.47,18.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,32768,1000,5.56,332.47,30.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,65536,640,6.19,553.23,32.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,131072,320,9.66,998.87,54.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,262144,160,16.96,1886.1,102.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,524288,80,34.44,3662.51,211.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,1048576,40,164.43,7374.23,502.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,2097152,20,4713.18,15395.91,5631.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gather,72,4194304,10,19515.11,30162.66,20404.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,0,1000,0.92,2.36,1.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,1,1000,1.52,7.79,3.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,2,1000,1.53,7.95,3.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,4,1000,1.56,8.1,3.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,8,1000,1.63,8.19,3.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,16,1000,1.71,8.54,3.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,32,1000,1.8,9.97,3.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,64,1000,1.91,11.47,4.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,128,1000,1.94,12.65,4.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,256,1000,4.6,16.15,9.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,512,1000,5.38,19.5,11.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,1024,1000,7.39,24.33,14.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,2048,1000,9.58,30.33,18.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,4096,1000,11.46,43.38,26.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,8192,1000,55.34,71.65,63.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,16384,1000,60.8,117.6,89.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,32768,1000,69.7,177.47,127.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,65536,640,69.72,286.69,173.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,131072,320,105.31,516.24,303.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,262144,160,200.93,967.52,554.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,524288,80,1120.17,1834.22,1503.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,1048576,40,2733.12,3525.29,3187.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,2097152,20,6532.72,7351.23,7020.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Gatherv,36,4194304,10,14190.75,14961.25,14631.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgather,144,0,1000,0.04,0.08,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,1,1000,9.98,13.6,11.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,2,1000,9.07,13.47,11.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,4,1000,10.12,15.71,12.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,8,1000,11.49,17.55,14.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,16,1000,15.59,23.71,19.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,32,1000,17.62,33.21,26.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,64,1000,30.02,41.85,36.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,128,1000,33.17,77.02,57.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,256,1000,46.31,73.56,65.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,512,1000,81.04,123.53,111.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,1024,1000,163.22,211.39,194.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,2048,1000,322.76,352.78,343.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,4096,1000,646.76,678.38,663.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,8192,1000,1362.24,1398.37,1386.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,16384,1000,800.61,985.9,888.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,32768,1000,1892.37,2467.01,2197.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,65536,640,3933.28,5134.18,4591.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,131072,320,7931.13,10221.36,9243.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,262144,160,14710.55,20411.9,17788.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,524288,80,31313.28,32408.48,31846.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,1048576,40,64608.01,66049.33,65534.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,2097152,20,150414.32,157069.93,153758.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgather,144,4194304,10,306870.8,319840.83,312599.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,72,0,1000,1.21,11.88,2.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,1,1000,4.63,14.7,6.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,2,1000,5.19,7.97,6.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,4,1000,5.97,8.96,7.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,8,1000,6.05,9.23,7.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,16,1000,6.37,9.61,8.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,32,1000,6.57,10.99,9.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,64,1000,7.7,12.07,10.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,128,1000,7.82,14.5,11.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,256,1000,8.31,19.12,13.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,512,1000,9.82,19.6,16.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,1024,1000,11.71,24.19,19.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,2048,1000,3.73,82.07,38.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,4096,1000,4.49,106.63,51.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,8192,1000,22.54,183.23,119.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,16384,1000,24.12,270.31,186.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,32768,1000,27.1,495.86,390.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,65536,640,18.64,814.3,683.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,131072,320,19.34,1358.51,1099.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,262144,160,54.52,2581.46,2136.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,524288,80,70.42,5342.59,4785.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,1048576,40,561.32,11197.72,10208.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,2097152,20,701.0,11138.15,9819.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Scatterv,72,4194304,10,1462.72,22354.64,19460.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,144,0,1000,0.06,0.11,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,4,1000,5.02,8.18,6.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,8,1000,5.12,8.27,6.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,16,1000,4.81,8.16,6.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,32,1000,4.65,8.13,6.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,64,1000,6.49,11.71,8.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,128,1000,8.28,16.79,11.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,256,1000,8.81,17.93,12.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,512,1000,7.14,15.61,10.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,1024,1000,12.49,22.37,17.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,2048,1000,10.15,17.0,13.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,4096,1000,12.88,19.27,15.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,8192,1000,28.49,34.65,30.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,16384,1000,63.35,73.23,67.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,32768,1000,48.3,60.29,53.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,65536,640,76.4,91.41,81.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,131072,320,134.57,158.07,142.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,262144,160,251.37,295.91,267.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,524288,80,520.58,604.87,540.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,1048576,40,1467.32,1559.17,1510.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,2097152,20,2723.35,2929.36,2828.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allreduce,144,4194304,10,5193.15,5211.48,5203.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Bcast,144,0,1000,0.03,0.05,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,1,1000,2.39,5.78,4.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,2,1000,0.64,5.36,4.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,4,1000,0.63,5.39,4.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,8,1000,0.64,5.35,4.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,16,1000,0.64,5.41,4.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,32,1000,0.63,5.47,4.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,64,1000,0.64,5.39,4.33,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,128,1000,0.67,6.28,4.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,256,1000,0.75,6.23,4.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,512,1000,0.79,6.35,5.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,1024,1000,0.82,7.01,3.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,2048,1000,1.28,5.56,3.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,4096,1000,2.45,8.69,5.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,8192,1000,4.81,12.86,9.6,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,16384,1000,8.09,20.12,16.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,32768,1000,12.7,30.73,26.52,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,65536,640,29.82,49.78,44.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,131072,320,61.87,89.72,83.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,262144,160,126.53,152.55,146.24,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,524288,80,265.96,291.83,285.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,1048576,40,523.47,562.02,549.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,2097152,20,1073.96,1109.47,1101.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Bcast,144,4194304,10,3457.7,3560.5,3521.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,0,1000,0.06,0.07,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,4,1000,0.33,7.38,0.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,8,1000,0.35,8.86,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,16,1000,0.35,7.95,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,32,1000,0.36,8.04,0.79,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,64,1000,0.37,9.54,0.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,128,1000,0.35,9.72,0.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,256,1000,0.34,12.68,1.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,512,1000,0.36,10.67,1.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,1024,1000,0.37,14.27,1.08,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,2048,1000,0.39,13.62,1.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,4096,1000,0.79,20.12,1.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,8192,1000,2.64,21.92,4.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,16384,1000,7.13,32.66,11.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,32768,1000,15.05,53.55,21.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,65536,640,76.84,176.74,142.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,131072,320,119.67,247.49,203.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,262144,160,76.87,462.58,276.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,524288,80,128.31,668.57,410.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,1048576,40,232.81,1041.5,654.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,2097152,20,331.4,1976.32,1157.9,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce,144,4194304,10,701.06,3362.9,2026.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Reduce_scatter,72,0,1000,0.44,0.84,0.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,4,1000,1.05,8.16,2.43,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,8,1000,1.07,8.1,2.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,16,1000,1.06,6.96,2.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,32,1000,1.08,7.19,2.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,64,1000,1.21,16.75,5.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,128,1000,1.29,8.54,4.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,256,1000,3.29,9.23,7.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,512,1000,7.94,9.75,8.63,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,1024,1000,11.85,13.53,12.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,2048,1000,9.38,11.79,10.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,4096,1000,11.58,20.43,12.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,8192,1000,14.67,18.41,16.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,16384,1000,22.6,26.26,24.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,32768,1000,35.47,40.09,37.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,65536,640,51.58,59.04,54.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,131072,320,73.98,85.6,78.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,262144,160,156.37,186.03,169.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,524288,80,342.79,349.37,345.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,1048576,40,539.53,547.68,542.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,2097152,20,1087.76,1109.18,1096.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Reduce_scatter,72,4194304,10,2378.45,2436.39,2403.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allreduce,288,0,1000,0.06,0.1,0.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,4,1000,5.99,8.38,7.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,8,1000,7.04,9.82,8.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,16,1000,9.38,12.64,10.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,32,1000,8.58,11.66,10.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,64,1000,8.88,13.79,10.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,128,1000,10.01,16.95,12.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,256,1000,10.44,18.09,13.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,512,1000,10.34,15.72,12.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,1024,1000,13.41,19.1,15.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,2048,1000,14.05,21.91,16.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,4096,1000,17.99,22.55,19.67,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,8192,1000,46.41,58.01,49.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,16384,1000,94.38,104.6,98.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,32768,1000,130.18,152.77,139.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,65536,640,103.38,126.36,112.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,131072,320,163.03,201.21,176.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,262144,160,302.55,365.51,323.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,524288,80,598.02,739.65,638.65,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,1048576,40,1944.49,2413.15,2171.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,2097152,20,3219.05,3260.74,3249.18,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Allreduce,288,4194304,10,5315.33,5371.77,5351.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,4, -1
+Alltoall,54,0,1000,0.04,0.06,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,1,1000,13.89,14.53,14.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,2,1000,15.18,15.88,15.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,4,1000,16.34,17.42,16.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,8,1000,16.76,17.75,17.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,16,1000,16.42,17.08,16.76,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,32,1000,20.38,23.01,21.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,64,1000,21.43,23.73,22.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,128,1000,26.05,28.2,27.05,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,256,1000,35.1,37.3,36.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,512,1000,58.84,66.65,62.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,1024,1000,88.4,96.19,92.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,2048,1000,143.83,146.25,144.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,4096,1000,243.6,247.6,245.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,8192,1000,428.26,470.53,447.0,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,16384,1000,874.3,891.02,885.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,32768,1000,1750.77,1770.96,1760.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,65536,640,2245.06,2261.55,2251.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,131072,320,6030.87,6103.24,6069.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,262144,160,9945.18,10149.85,10069.89,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,524288,80,19477.84,20320.12,19986.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,1048576,40,30514.53,30797.36,30716.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,2097152,20,63347.82,64334.31,63938.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Alltoall,54,4194304,10,120744.59,125742.45,123953.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,72,0,1000,0.6,0.81,0.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,1,1000,7.56,9.27,8.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,2,1000,7.83,9.65,8.48,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,4,1000,7.93,9.27,8.38,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,8,1000,8.73,18.4,17.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,16,1000,11.67,13.75,12.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,32,1000,21.28,24.65,21.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,64,1000,20.23,22.36,20.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,128,1000,23.94,26.11,24.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,256,1000,44.63,47.43,45.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,512,1000,71.0,91.57,72.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,1024,1000,70.36,72.33,71.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,2048,1000,105.06,107.19,106.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,4096,1000,196.81,228.81,214.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,8192,1000,299.43,302.73,300.84,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,16384,1000,433.78,443.47,436.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,32768,1000,838.13,895.28,867.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,65536,640,1625.54,1775.92,1703.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,131072,320,3238.92,3551.89,3392.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,262144,160,6561.6,7116.86,6849.5,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,524288,80,15893.42,16337.88,16141.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,1048576,40,35872.95,35877.77,35874.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,2097152,20,71883.36,71892.41,71884.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,72,4194304,10,145531.27,145537.28,145532.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Scatter,144,0,1000,0.04,0.07,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,1,1000,2.92,6.52,4.94,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,2,1000,1.24,5.09,3.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,4,1000,3.33,7.46,5.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,8,1000,3.35,6.78,5.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,16,1000,1.81,6.96,4.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,32,1000,2.78,8.05,5.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,64,1000,5.55,18.86,8.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,128,1000,7.72,15.58,12.11,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,256,1000,11.18,23.94,18.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,512,1000,10.05,34.32,24.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,1024,1000,14.14,53.97,43.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,2048,1000,23.37,101.19,85.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,4096,1000,31.23,179.08,156.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,8192,1000,51.99,337.1,277.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,16384,1000,97.23,500.3,423.53,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,32768,1000,45.73,750.13,352.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,65536,640,62.93,1737.33,684.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,131072,320,74.42,1034.21,538.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,262144,160,136.32,1595.56,859.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,524288,80,1131.49,3152.35,2800.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,1048576,40,562.78,6298.88,3882.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,2097152,20,9624.91,12555.35,11723.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Scatter,144,4194304,10,12783.94,25350.56,24509.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, 50
+Gather,18,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,1,1000,0.34,2.44,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,2,1000,0.34,2.5,0.82,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,4,1000,0.34,2.49,0.81,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,8,1000,0.35,2.56,0.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,16,1000,0.36,2.72,0.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,32,1000,0.36,2.82,0.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,64,1000,0.4,3.29,0.99,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,128,1000,0.43,4.04,1.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,256,1000,0.44,5.7,0.85,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,512,1000,0.6,5.46,1.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,1024,1000,1.17,10.31,1.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,2048,1000,1.79,13.77,2.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,4096,1000,3.08,21.53,4.61,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,8192,1000,4.15,34.6,7.06,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,16384,1000,8.68,60.74,13.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,32768,1000,16.01,107.43,24.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,65536,640,32.69,150.29,44.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,131072,320,29.14,276.65,62.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,262144,160,66.75,543.22,119.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,524288,80,147.5,993.13,229.95,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,1048576,40,300.65,1905.45,455.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,2097152,20,1562.85,3785.26,1831.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Gather,18,4194304,10,5357.4,7579.34,5615.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,144,0,1000,2.18,5.81,2.28,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,1,1000,13.77,27.46,23.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,2,1000,14.78,21.12,17.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,4,1000,14.52,23.54,18.54,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,8,1000,17.4,25.63,20.49,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,16,1000,21.1,29.53,24.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,32,1000,26.29,38.21,32.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,64,1000,31.01,51.56,42.12,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,128,1000,71.48,88.5,82.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,256,1000,89.55,116.88,108.55,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,512,1000,112.29,156.37,143.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,1024,1000,180.54,231.68,213.58,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,2048,1000,307.38,337.88,328.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,4096,1000,313.08,381.41,348.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,8192,1000,496.43,573.75,529.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,16384,1000,918.25,1171.08,1042.16,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,32768,1000,1891.99,2522.66,2231.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,65536,640,3593.11,4708.47,4193.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,131072,320,7122.95,9088.64,8276.73,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,262144,160,13301.21,16716.13,15109.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,524288,80,30133.33,31217.16,30645.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,1048576,40,66772.39,69259.41,67952.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,2097152,20,155832.04,168588.65,161602.23,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Allgatherv,144,4194304,10,307214.88,319433.99,312558.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2,NA
+Scatterv,144,0,1000,5.25,9.92,7.41,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,1,1000,6.36,12.33,9.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,2,1000,6.71,12.79,9.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,4,1000,6.75,12.76,9.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,8,1000,6.9,13.35,10.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,16,1000,6.81,13.77,9.21,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,32,1000,7.26,12.32,9.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,64,1000,7.85,13.53,10.42,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,128,1000,7.92,14.83,11.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,256,1000,9.32,17.73,13.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,512,1000,10.33,27.9,20.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,1024,1000,12.41,34.61,26.4,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,2048,1000,15.79,56.04,44.07,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,4096,1000,13.12,151.41,99.78,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,8192,1000,37.04,279.81,176.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,16384,1000,43.19,496.24,311.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,32768,1000,59.81,856.52,522.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,65536,640,85.59,1266.54,752.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,131072,320,121.11,2376.83,1307.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,262144,160,680.88,10789.93,7481.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,524288,80,622.28,19236.08,9735.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,1048576,40,1118.85,35064.98,18287.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,2097152,20,1821.78,79703.72,42053.57,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Scatterv,144,4194304,10,4004.78,155584.22,82137.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,2, -1
+Allgatherv,18,0,1000,0.28,0.39,0.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,1,1000,3.51,4.0,3.66,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,2,1000,3.52,4.05,3.72,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,4,1000,3.62,4.19,3.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,8,1000,3.74,4.41,3.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,16,1000,3.97,4.72,4.22,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,32,1000,4.37,5.12,4.62,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,64,1000,5.1,6.04,5.37,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,128,1000,9.82,11.23,10.09,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,256,1000,10.74,12.14,11.02,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,512,1000,14.33,15.34,14.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,1024,1000,16.58,17.63,16.98,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,2048,1000,20.74,21.86,21.2,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,4096,1000,28.01,29.09,28.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,8192,1000,41.46,42.14,41.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,16384,1000,64.56,65.38,64.88,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,32768,1000,76.08,77.61,76.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,65536,640,164.75,168.66,166.71,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,131072,320,496.51,513.56,503.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,262144,160,1312.73,1336.07,1329.32,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,524288,80,3279.3,3282.65,3281.44,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,1048576,40,8232.36,8347.87,8293.26,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,2097152,20,18891.7,19058.96,19004.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Allgatherv,18,4194304,10,38684.03,38954.89,38845.27,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1,NA
+Alltoall,72,0,1000,0.04,0.04,0.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,1,1000,17.33,28.72,27.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,2,1000,18.43,20.06,19.13,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,4,1000,19.52,21.25,20.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,8,1000,20.02,21.74,20.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,16,1000,25.09,28.34,26.47,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,32,1000,22.04,23.5,22.64,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,64,1000,26.97,28.05,27.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,128,1000,40.27,42.34,41.25,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,256,1000,61.97,67.76,65.59,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,512,1000,79.56,85.99,82.34,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,1024,1000,113.71,119.21,115.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,2048,1000,176.86,183.37,179.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,4096,1000,304.33,312.82,308.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,8192,1000,583.94,602.93,595.01,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,16384,1000,1124.84,1140.82,1132.46,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,32768,1000,2036.78,2095.65,2060.8,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,65536,640,3151.19,3172.66,3162.69,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,131072,320,6141.65,6175.16,6160.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,262144,160,11071.52,11121.33,11095.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,524288,80,20818.64,21295.95,20954.97,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,1048576,40,41250.95,41575.33,41411.36,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,2097152,20,82134.06,83120.98,82626.19,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Alltoall,72,4194304,10,181957.42,182602.61,182280.87,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, 50
+Allgatherv,36,0,1000,0.38,0.51,0.39,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,1,1000,4.5,5.2,4.77,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,2,1000,4.63,5.41,4.91,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,4,1000,5.0,5.91,5.35,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,8,1000,5.33,6.33,5.7,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,16,1000,5.69,6.74,6.17,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,32,1000,6.61,7.87,7.31,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,64,1000,16.19,17.62,16.51,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,128,1000,18.54,20.06,18.86,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,256,1000,25.33,26.71,25.93,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,512,1000,29.43,31.68,29.92,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,1024,1000,34.17,34.82,34.56,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,2048,1000,51.57,52.45,52.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,4096,1000,83.71,84.67,84.1,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,8192,1000,144.41,146.09,145.15,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,16384,1000,193.16,195.02,194.14,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,32768,1000,373.26,377.77,375.83,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,65536,640,733.04,741.39,737.68,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,131072,320,1477.57,1499.73,1490.96,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,262144,160,3016.52,3050.5,3032.3,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,524288,80,6188.79,6261.33,6231.03,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,1048576,40,15839.66,16299.55,16102.75,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,2097152,20,33179.37,33182.0,33180.04,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
+Allgatherv,36,4194304,10,65257.03,65260.4,65258.29,MPI_BYTE,MPI_FLOAT,MPI_SUM,25_06_01_22-03-11,1, -1
diff --git a/results-and-plotting/docs/MPI1-Benchmark-Analysis.pdf b/results-and-plotting/docs/MPI1-Benchmark-Analysis.pdf
new file mode 100644
index 0000000..7af72f4
Binary files /dev/null and b/results-and-plotting/docs/MPI1-Benchmark-Analysis.pdf differ
diff --git a/results-and-plotting/plots/allgather_surface.png b/results-and-plotting/plots/allgather_surface.png
new file mode 100644
index 0000000..6420d9e
Binary files /dev/null and b/results-and-plotting/plots/allgather_surface.png differ
diff --git a/results-and-plotting/plots/allreduce_surface.png b/results-and-plotting/plots/allreduce_surface.png
new file mode 100644
index 0000000..5172490
Binary files /dev/null and b/results-and-plotting/plots/allreduce_surface.png differ
diff --git a/results-and-plotting/plots/alltoall_surface.png b/results-and-plotting/plots/alltoall_surface.png
new file mode 100644
index 0000000..8edf45d
Binary files /dev/null and b/results-and-plotting/plots/alltoall_surface.png differ
diff --git a/results-and-plotting/plots/analysis_old/allgather2_analysis.png b/results-and-plotting/plots/analysis_old/allgather2_analysis.png
new file mode 100644
index 0000000..e8ad860
Binary files /dev/null and b/results-and-plotting/plots/analysis_old/allgather2_analysis.png differ
diff --git a/results-and-plotting/plots/analysis_old/allgather_analysis.png b/results-and-plotting/plots/analysis_old/allgather_analysis.png
new file mode 100644
index 0000000..40b68dd
Binary files /dev/null and b/results-and-plotting/plots/analysis_old/allgather_analysis.png differ
diff --git a/results-and-plotting/plots/analysis_old/alltoall_analysis.png b/results-and-plotting/plots/analysis_old/alltoall_analysis.png
new file mode 100644
index 0000000..31783ce
Binary files /dev/null and b/results-and-plotting/plots/analysis_old/alltoall_analysis.png differ
diff --git a/results-and-plotting/plots/analysis_old/off_cache_flag_effect0.png b/results-and-plotting/plots/analysis_old/off_cache_flag_effect0.png
new file mode 100644
index 0000000..ad66ce6
Binary files /dev/null and b/results-and-plotting/plots/analysis_old/off_cache_flag_effect0.png differ
diff --git a/results-and-plotting/plots/analysis_old/off_cache_flag_effect1.png b/results-and-plotting/plots/analysis_old/off_cache_flag_effect1.png
new file mode 100644
index 0000000..f06a599
Binary files /dev/null and b/results-and-plotting/plots/analysis_old/off_cache_flag_effect1.png differ
diff --git a/results-and-plotting/plots/benchmark_avg_time_barplot.png b/results-and-plotting/plots/benchmark_avg_time_barplot.png
new file mode 100644
index 0000000..94ed538
Binary files /dev/null and b/results-and-plotting/plots/benchmark_avg_time_barplot.png differ
diff --git a/results-and-plotting/plots/benchmark_avg_time_barplot_log.png b/results-and-plotting/plots/benchmark_avg_time_barplot_log.png
new file mode 100644
index 0000000..a2ea0f9
Binary files /dev/null and b/results-and-plotting/plots/benchmark_avg_time_barplot_log.png differ
diff --git a/results-and-plotting/plots/fbenchmarks_avg_time_barplot.png b/results-and-plotting/plots/fbenchmarks_avg_time_barplot.png
new file mode 100644
index 0000000..2588b8c
Binary files /dev/null and b/results-and-plotting/plots/fbenchmarks_avg_time_barplot.png differ
diff --git a/results-and-plotting/plots/gather_surface.png b/results-and-plotting/plots/gather_surface.png
new file mode 100644
index 0000000..b3e5880
Binary files /dev/null and b/results-and-plotting/plots/gather_surface.png differ
diff --git a/results-and-plotting/plots/mbenchmarks_avg_time_barplot.png b/results-and-plotting/plots/mbenchmarks_avg_time_barplot.png
new file mode 100644
index 0000000..adf72bc
Binary files /dev/null and b/results-and-plotting/plots/mbenchmarks_avg_time_barplot.png differ
diff --git a/results-and-plotting/plots/sbenchmarks_avg_time_barplot.png b/results-and-plotting/plots/sbenchmarks_avg_time_barplot.png
new file mode 100644
index 0000000..fc95948
Binary files /dev/null and b/results-and-plotting/plots/sbenchmarks_avg_time_barplot.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Allgather.png b/results-and-plotting/plots/scatter/scatter_plot_Allgather.png
new file mode 100644
index 0000000..339629a
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Allgather.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Allgatherv.png b/results-and-plotting/plots/scatter/scatter_plot_Allgatherv.png
new file mode 100644
index 0000000..5c95f73
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Allgatherv.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Allreduce.png b/results-and-plotting/plots/scatter/scatter_plot_Allreduce.png
new file mode 100644
index 0000000..cbe6688
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Allreduce.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Alltoall.png b/results-and-plotting/plots/scatter/scatter_plot_Alltoall.png
new file mode 100644
index 0000000..dba4380
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Alltoall.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Bcast.png b/results-and-plotting/plots/scatter/scatter_plot_Bcast.png
new file mode 100644
index 0000000..d4d9f3b
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Bcast.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Gather.png b/results-and-plotting/plots/scatter/scatter_plot_Gather.png
new file mode 100644
index 0000000..ef782a7
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Gather.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Gatherv.png b/results-and-plotting/plots/scatter/scatter_plot_Gatherv.png
new file mode 100644
index 0000000..d7d379d
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Gatherv.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Reduce.png b/results-and-plotting/plots/scatter/scatter_plot_Reduce.png
new file mode 100644
index 0000000..5782b2c
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Reduce.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Reduce_scatter.png b/results-and-plotting/plots/scatter/scatter_plot_Reduce_scatter.png
new file mode 100644
index 0000000..1c49618
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Reduce_scatter.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Scatter.png b/results-and-plotting/plots/scatter/scatter_plot_Scatter.png
new file mode 100644
index 0000000..1af20ec
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Scatter.png differ
diff --git a/results-and-plotting/plots/scatter/scatter_plot_Scatterv.png b/results-and-plotting/plots/scatter/scatter_plot_Scatterv.png
new file mode 100644
index 0000000..b13653c
Binary files /dev/null and b/results-and-plotting/plots/scatter/scatter_plot_Scatterv.png differ
diff --git a/results-and-plotting/python/notebooks/allgather_analysis.ipynb b/results-and-plotting/python/notebooks/allgather_analysis.ipynb
new file mode 100644
index 0000000..62fde5c
--- /dev/null
+++ b/results-and-plotting/python/notebooks/allgather_analysis.ipynb
@@ -0,0 +1,318 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "da7c16b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from scipy.optimize import curve_fit\n",
+    "from matplotlib.cm import get_cmap"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47341b1d",
+   "metadata": {},
+   "source": [
+    "# Allgather "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "1cc39aab",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_10800/1470334786.py:3: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_allgather = df_multinode[df_multinode[\"benchmark_type\"]==\"Allgather\"][df_multinode['off_cache_flag']==-1][df_multinode['msg_size_bytes']>1024][df_multinode['proc_num']>0]\n",
+      "/tmp/ipykernel_10800/1470334786.py:3: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_allgather = df_multinode[df_multinode[\"benchmark_type\"]==\"Allgather\"][df_multinode['off_cache_flag']==-1][df_multinode['msg_size_bytes']>1024][df_multinode['proc_num']>0]\n",
+      "/tmp/ipykernel_10800/1470334786.py:3: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_allgather = df_multinode[df_multinode[\"benchmark_type\"]==\"Allgather\"][df_multinode['off_cache_flag']==-1][df_multinode['msg_size_bytes']>1024][df_multinode['proc_num']>0]\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_multinode = pd.read_csv(\"data/data-multi-defand100cflag.csv\",delimiter = \",\")\n",
+    "df_multinode['benchmark_type'].unique()\n",
+    "df_allgather = df_multinode[df_multinode[\"benchmark_type\"]==\"Allgather\"][df_multinode['off_cache_flag']==-1][df_multinode['msg_size_bytes']>1024][df_multinode['proc_num']>0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "4336d3c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_10800/119527997.py:9: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.\n",
+      "  cmap = get_cmap('tab10')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1500x1600 with 12 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    msg_size_bytes     alpha      beta  inv_alpha\n",
+      "0             2048  1.552236  0.000150   0.644232\n",
+      "1             4096  1.000317  0.000317   0.999684\n",
+      "2             8192  1.000374  0.000374   0.999626\n",
+      "3            16384  1.000750  0.000750   0.999250\n",
+      "4            32768  1.001409  0.001408   0.998593\n",
+      "5            65536  1.002759  0.002759   0.997249\n",
+      "6           131072  1.005332  0.005332   0.994696\n",
+      "7           262144  1.429840  0.010007   0.699379\n",
+      "8           524288  1.016241  0.016955   0.984018\n",
+      "9          1048576  1.079597  0.038522   0.926272\n",
+      "10         2097152  1.089258  0.089258   0.918056\n",
+      "11         4194304  1.171323  0.171323   0.853735\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "def model(proc_num, alpha, beta, msg_size):\n",
+    "   return (proc_num/72-1)*((alpha*(msg_size)*72)/(12500)+1e6*beta) \n",
+    "\n",
+    "results = []\n",
+    "msg_sizes = sorted(df_allgather['msg_size_bytes'].unique())\n",
+    "n_rows = int(np.ceil(len(msg_sizes) / 3))\n",
+    "n_cols = min(len(msg_sizes), 3)\n",
+    "fig, axes = plt.subplots(n_rows, n_cols, figsize=(5*n_cols, 4*n_rows), squeeze=False)\n",
+    "cmap = get_cmap('tab10')\n",
+    "\n",
+    "for idx, (msg_size, group) in enumerate(df_allgather.groupby('msg_size_bytes')):\n",
+    "    x = group['proc_num'].values\n",
+    "    y = group['t_avg_usec'].values\n",
+    "\n",
+    "    fit_func = lambda proc_num, alpha, beta: model(proc_num, alpha, beta, msg_size)\n",
+    "    popt, _ = curve_fit(fit_func, x, y, bounds=([1, 0], [np.inf, np.inf]))\n",
+    "    alpha, beta = popt\n",
+    "    results.append({'msg_size_bytes': msg_size, 'alpha': alpha, 'beta': beta})\n",
+    "\n",
+    "    x_fit = np.linspace(min(x), max(x), 100)\n",
+    "    y_fit = fit_func(x_fit, alpha, beta)\n",
+    "    y_speed = model(x_fit,1,0,msg_size)\n",
+    "    row, col = divmod(idx, n_cols)\n",
+    "    ax = axes[row][col]\n",
+    "\n",
+    "    color = cmap(idx % 10)\n",
+    "    ax.scatter(x, y/1e6, label='Data', color=color)\n",
+    "    ax.plot(x_fit, y_fit/1e6, linestyle='--', color=color, alpha=0.5, label='Fit')\n",
+    "    ax.plot(x_fit, y_speed/1e6, linestyle='--', color='red', alpha=0.2, label='Fit')\n",
+    "    ax.set_title(f'msg_size: {msg_size} bytes')\n",
+    "    ax.set_xlabel('num. proc.')\n",
+    "    ax.set_ylabel('Average Time [s]')\n",
+    "    ax.set_xticks(x)\n",
+    "    ax.grid(True)\n",
+    "    max_data =(x[-1]-72)*msg_size\n",
+    "    min_data =(x[0]-72)*msg_size\n",
+    "\n",
+    "    textstr = \"\"\n",
+    "    if(max_data > 1e9):\n",
+    "        textstr+=f\"max data = {max_data/1e9:0.2f}GB\\n\" \n",
+    "    else:\n",
+    "        textstr+=f\"max data = {max_data/1e6:0.2f}MB\\n\" \n",
+    "\n",
+    "    if(min_data > 1e9):\n",
+    "        textstr+=f\"min data = {min_data/1e9:0.2f}GB\\n\" \n",
+    "    else:\n",
+    "        textstr+=f\"min data = {min_data/1e6:0.2f}MB\\n\" \n",
+    "    textstr += r\"$\\alpha$\" +f\"= {alpha:.3e}\\n\"+r\"$b_{eff}=$\"+f\"{12.5/alpha:0.3f}Gbps\\n\"+\\\n",
+    "               r\"$\\beta$\"+f\"= {beta:.3e} s\"\n",
+    "    ax.text(0.95, 0.05, textstr, transform=ax.transAxes,\n",
+    "            fontsize=10, verticalalignment='bottom',\n",
+    "            horizontalalignment='right',\n",
+    "            bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))\n",
+    "\n",
+    "fig.suptitle('Allgather Time Fit per Message Size\\nDots = Data Points | Dashed Lines = Fits | off_mem=-1', fontsize=14)\n",
+    "fig.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
+    "plt.savefig(\"plots/allgather_analysis.png\",dpi=300)\n",
+    "plt.show()\n",
+    "\n",
+    "fit_results = pd.DataFrame(results)\n",
+    "fit_results['inv_alpha'] = 1 / fit_results['alpha']\n",
+    "print(fit_results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "ce632d6f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_10800/695385123.py:2: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_allgather_2 = df_multinode_2[df_multinode_2[\"benchmark_type\"]==\"Allgather\"][df_multinode_2['off_cache_flag']==100][df_multinode_2['msg_size_bytes']>1024][df_multinode_2['proc_num']>0]\n",
+      "/tmp/ipykernel_10800/695385123.py:2: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_allgather_2 = df_multinode_2[df_multinode_2[\"benchmark_type\"]==\"Allgather\"][df_multinode_2['off_cache_flag']==100][df_multinode_2['msg_size_bytes']>1024][df_multinode_2['proc_num']>0]\n",
+      "/tmp/ipykernel_10800/695385123.py:2: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_allgather_2 = df_multinode_2[df_multinode_2[\"benchmark_type\"]==\"Allgather\"][df_multinode_2['off_cache_flag']==100][df_multinode_2['msg_size_bytes']>1024][df_multinode_2['proc_num']>0]\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_multinode_2 = pd.read_csv(\"data/data-multi-MPIF-100cflag-complete.csv\",delimiter = \",\")\n",
+    "df_allgather_2 = df_multinode_2[df_multinode_2[\"benchmark_type\"]==\"Allgather\"][df_multinode_2['off_cache_flag']==100][df_multinode_2['msg_size_bytes']>1024][df_multinode_2['proc_num']>0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "3532b67e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_10800/1198317908.py:9: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.\n",
+      "  cmap = get_cmap('tab10')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1500x1600 with 12 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    msg_size_bytes     alpha      beta  inv_alpha\n",
+      "0             2048  1.000157  0.000157   0.999843\n",
+      "1             4096  1.000257  0.000257   0.999743\n",
+      "2             8192  1.000389  0.000389   0.999611\n",
+      "3            16384  1.000718  0.000718   0.999283\n",
+      "4            32768  1.001514  0.001514   0.998488\n",
+      "5            65536  1.000996  0.002762   0.999005\n",
+      "6           131072  1.005062  0.005062   0.994964\n",
+      "7           262144  1.012598  0.009937   0.987559\n",
+      "8           524288  1.020122  0.020125   0.980275\n",
+      "9          1048576  1.062741  0.062742   0.940963\n",
+      "10         2097152  1.178951  0.179023   0.848211\n",
+      "11         4194304  1.537594  0.537920   0.650367\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "def model_2(proc_num, alpha, beta, msg_size):\n",
+    "   return (proc_num/72-1)*((alpha*(msg_size)*72)/(12500)+1e6*beta) \n",
+    "\n",
+    "results = []\n",
+    "msg_sizes = sorted(df_allgather_2['msg_size_bytes'].unique())\n",
+    "n_rows = int(np.ceil(len(msg_sizes) / 3))\n",
+    "n_cols = min(len(msg_sizes), 3)\n",
+    "fig, axes = plt.subplots(n_rows, n_cols, figsize=(5*n_cols, 4*n_rows), squeeze=False)\n",
+    "cmap = get_cmap('tab10')\n",
+    "\n",
+    "for idx, (msg_size, group) in enumerate(df_allgather_2.groupby('msg_size_bytes')):\n",
+    "    x = group['proc_num'].values\n",
+    "    y = group['t_avg_usec'].values\n",
+    "\n",
+    "    fit_func = lambda proc_num, alpha, beta: model_2(proc_num, alpha, beta, msg_size)\n",
+    "    popt, _ = curve_fit(fit_func, x, y, bounds=([1, 0], [np.inf, np.inf]))\n",
+    "    alpha, beta = popt\n",
+    "    results.append({'msg_size_bytes': msg_size, 'alpha': alpha, 'beta': beta})\n",
+    "\n",
+    "    x_fit = np.linspace(min(x), max(x), 100)\n",
+    "    y_fit = fit_func(x_fit, alpha, beta)\n",
+    "    y_speed = model_2(x_fit,1,0,msg_size)\n",
+    "    row, col = divmod(idx, n_cols)\n",
+    "    ax = axes[row][col]\n",
+    "\n",
+    "    color = cmap(idx % 10)\n",
+    "    ax.scatter(x, y/1e6, label='Data', color=color)\n",
+    "    ax.plot(x_fit, y_fit/1e6, linestyle='--', color=color, alpha=0.5, label='Fit')\n",
+    "    ax.plot(x_fit, y_speed/1e6, linestyle='--', color='red', alpha=0.2, label='Fit')\n",
+    "    ax.set_title(f'msg_size: {msg_size} bytes')\n",
+    "    ax.set_xlabel('num. proc.')\n",
+    "    ax.set_ylabel('Average Time [s]')\n",
+    "    ax.set_xticks(x)\n",
+    "    ax.grid(True)\n",
+    "    max_data =(x[-1]-72)*msg_size\n",
+    "    min_data =(x[0]-72)*msg_size\n",
+    "\n",
+    "    textstr = \"\"\n",
+    "    if(max_data > 1e9):\n",
+    "        textstr+=f\"max data = {max_data/1e9:0.2f}GB\\n\" \n",
+    "    else:\n",
+    "        textstr+=f\"max data = {max_data/1e6:0.2f}MB\\n\" \n",
+    "\n",
+    "    if(min_data > 1e9):\n",
+    "        textstr+=f\"min data = {min_data/1e9:0.2f}GB\\n\" \n",
+    "    else:\n",
+    "        textstr+=f\"min data = {min_data/1e6:0.2f}MB\\n\" \n",
+    "    textstr += r\"$\\alpha$\" +f\"= {alpha:.3e}\\n\"+r\"$b_{eff}=$\"+f\"{12.5/alpha:0.3f}Gbps\\n\"+\\\n",
+    "               r\"$\\beta$\"+f\"= {beta:.3e} s\"\n",
+    "    ax.text(0.95, 0.05, textstr, transform=ax.transAxes,\n",
+    "            fontsize=10, verticalalignment='bottom',\n",
+    "            horizontalalignment='right',\n",
+    "            bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))\n",
+    "\n",
+    "\n",
+    "fig.suptitle('Allgather Time Fit per Message Size\\nDots = Data Points | Dashed Lines = Fits \\n off_mem = 100 |I_MPI_TUNING=on | I_MPI_TUNING_MODE=auto', fontsize=14)\n",
+    "fig.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
+    "plt.savefig(\"plots/allgather2_analysis.png\",dpi=300)\n",
+    "plt.show()\n",
+    "\n",
+    "fit_results = pd.DataFrame(results)\n",
+    "fit_results['inv_alpha'] = 1 / fit_results['alpha']\n",
+    "print(fit_results)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "data",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/results-and-plotting/python/notebooks/alltoall_analysis.ipynb b/results-and-plotting/python/notebooks/alltoall_analysis.ipynb
new file mode 100644
index 0000000..0db0b54
--- /dev/null
+++ b/results-and-plotting/python/notebooks/alltoall_analysis.ipynb
@@ -0,0 +1,593 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "da7c16b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from scipy.optimize import curve_fit\n",
+    "from matplotlib.cm import get_cmap"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47341b1d",
+   "metadata": {},
+   "source": [
+    "# Alltoall "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "1cc39aab",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_7900/2058266473.py:3: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_alltoall = df_multinode[df_multinode[\"benchmark_type\"]==\"Alltoall\"][df_multinode['msg_size_bytes']>1024][df_multinode['off_cache_flag']==-1]\n",
+      "/tmp/ipykernel_7900/2058266473.py:3: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_alltoall = df_multinode[df_multinode[\"benchmark_type\"]==\"Alltoall\"][df_multinode['msg_size_bytes']>1024][df_multinode['off_cache_flag']==-1]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "['benchmark_type',\n",
+       " 'proc_num',\n",
+       " 'msg_size_bytes',\n",
+       " 'repetitions',\n",
+       " 't_min_usec',\n",
+       " 't_max_usec',\n",
+       " 't_avg_usec',\n",
+       " 'mpi_datatype',\n",
+       " 'mpi_red_datatype',\n",
+       " 'mpi_red_op',\n",
+       " 'creation_time',\n",
+       " 'n_nodes',\n",
+       " 'off_cache_flag']"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_multinode = pd.read_csv(\"data/data-multi-defand100cflag.csv\",delimiter = \",\")\n",
+    "df_multinode['benchmark_type'].unique()\n",
+    "df_alltoall = df_multinode[df_multinode[\"benchmark_type\"]==\"Alltoall\"][df_multinode['msg_size_bytes']>1024][df_multinode['off_cache_flag']==-1]\n",
+    "df_alltoall.columns.tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "4336d3c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_7900/4021581818.py:9: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.\n",
+      "  cmap = get_cmap('tab10')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1500x1600 with 12 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    msg_size_bytes     alpha          beta  inv_alpha\n",
+      "0             2048  1.350220  7.950002e-22   0.740620\n",
+      "1             4096  1.153722  7.345616e-19   0.866760\n",
+      "2             8192  1.316655  7.685776e-24   0.759501\n",
+      "3            16384  1.205501  5.440666e-23   0.829531\n",
+      "4            32768  1.197387  1.048284e-22   0.835152\n",
+      "5            65536  1.338850  8.987548e-20   0.746910\n",
+      "6           131072  1.190638  2.825286e-19   0.839886\n",
+      "7           262144  1.132900  8.001526e-04   0.882691\n",
+      "8           524288  1.129881  3.119047e-17   0.885049\n",
+      "9          1048576  1.090405  1.674706e-16   0.917091\n",
+      "10         2097152  1.067311  5.849285e-03   0.936934\n",
+      "11         4194304  1.057813  2.218755e-02   0.945346\n"
+     ]
+    }
+   ],
+   "source": [
+    "def model(proc_num, alpha, beta, msg_size):\n",
+    "    return (alpha * msg_size * (proc_num - 72) * 72) / (12.5 * 1e3) + 1e6*beta\n",
+    "\n",
+    "results = []\n",
+    "msg_sizes = sorted(df_alltoall['msg_size_bytes'].unique())\n",
+    "n_rows = int(np.ceil(len(msg_sizes) / 3))\n",
+    "n_cols = min(len(msg_sizes), 3)\n",
+    "fig, axes = plt.subplots(n_rows, n_cols, figsize=(5*n_cols, 4*n_rows), squeeze=False)\n",
+    "cmap = get_cmap('tab10')\n",
+    "\n",
+    "for idx, (msg_size, group) in enumerate(df_alltoall.groupby('msg_size_bytes')):\n",
+    "    x = group['proc_num'].values\n",
+    "    y = group['t_avg_usec'].values\n",
+    "\n",
+    "    fit_func = lambda proc_num, alpha, beta: model(proc_num, alpha, beta, msg_size)\n",
+    "    popt, _ = curve_fit(fit_func, x, y, bounds=([1, 0], [np.inf, np.inf]))\n",
+    "    alpha, beta = popt\n",
+    "    results.append({'msg_size_bytes': msg_size, 'alpha': alpha, 'beta': beta})\n",
+    "\n",
+    "    x_fit = np.linspace(min(x), max(x), 100)\n",
+    "    y_fit = fit_func(x_fit, alpha, beta)\n",
+    "    y_speed = model(x_fit,1,0,msg_size)\n",
+    "    row, col = divmod(idx, n_cols)\n",
+    "    ax = axes[row][col]\n",
+    "\n",
+    "    color = cmap(idx % 10)\n",
+    "    ax.scatter(x, y/1e6, label='Data', color=color)\n",
+    "    ax.plot(x_fit, y_fit/1e6, linestyle='--', color=color, alpha=0.5, label='Fit')\n",
+    "    ax.plot(x_fit, y_speed/1e6, linestyle='--', color='red', alpha=0.1, label='Fit')\n",
+    "    ax.set_title(f'msg_size: {msg_size} bytes')\n",
+    "    ax.set_xlabel('num. proc.')\n",
+    "    ax.set_ylabel('Average Time [s]')\n",
+    "    ax.set_xticks(x)\n",
+    "    ax.grid(True)\n",
+    "    max_data =(x[-1]-72)*72*msg_size\n",
+    "    min_data =(x[0]-72)*72*msg_size\n",
+    "\n",
+    "    textstr = \"\"\n",
+    "    if(max_data > 1e9):\n",
+    "        textstr+=f\"max data = {max_data/1e9:0.2f}GB\\n\" \n",
+    "    else:\n",
+    "        textstr+=f\"max data = {max_data/1e6:0.2f}MB\\n\" \n",
+    "\n",
+    "    if(min_data > 1e9):\n",
+    "        textstr+=f\"min data = {min_data/1e9:0.2f}GB\\n\" \n",
+    "    else:\n",
+    "        textstr+=f\"min data = {min_data/1e6:0.2f}MB\\n\" \n",
+    "    textstr += r\"$\\alpha$\" +f\"= {alpha:.3e}\\n\"+r\"$b_{eff}=$\"+f\"{12.5/alpha:0.3f}Gbps\\n\"+\\\n",
+    "               r\"$\\beta$\"+f\"= {beta:.3e} s\"\n",
+    "    ax.text(0.95, 0.05, textstr, transform=ax.transAxes,\n",
+    "            fontsize=10, verticalalignment='bottom',\n",
+    "            horizontalalignment='right',\n",
+    "            bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))\n",
+    "\n",
+    "fig.suptitle('Alltoall Time Fit per Message Size\\nDots = Data Points | Dashed Lines = Fits\\n off_mem=-1', fontsize=14)\n",
+    "fig.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
+    "plt.savefig(\"plots/alltoall_analysis.png\",dpi=300)\n",
+    "plt.show()\n",
+    "\n",
+    "fit_results = pd.DataFrame(results)\n",
+    "fit_results['inv_alpha'] = 1 / fit_results['alpha']\n",
+    "print(fit_results)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "ce632d6f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
+       "columns": [
+        {
+         "name": "index",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "benchmark_type",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "proc_num",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "msg_size_bytes",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "repetitions",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "t_min_usec",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "t_max_usec",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "t_avg_usec",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "mpi_datatype",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "mpi_red_datatype",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "mpi_red_op",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "creation_time",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "n_nodes",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "off_cache_flag",
+         "rawType": "int64",
+         "type": "integer"
+        }
+       ],
+       "ref": "f5133b3a-2bed-4ac7-959c-54512c43b584",
+       "rows": [
+        [
+         "21",
+         "Alltoall",
+         "360",
+         "1048576",
+         "12",
+         "1887068.02",
+         "1888622.38",
+         "1887741.99",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_27_02-42-36",
+         "5",
+         "100"
+        ],
+        [
+         "69",
+         "Alltoall",
+         "576",
+         "1048576",
+         "12",
+         "3401545.19",
+         "3413244.99",
+         "3406651.76",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_27_02-42-36",
+         "8",
+         "100"
+        ],
+        [
+         "678",
+         "Alltoall",
+         "432",
+         "1048576",
+         "17",
+         "2400724.43",
+         "2407984.77",
+         "2404588.58",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_27_02-42-36",
+         "6",
+         "100"
+        ],
+        [
+         "906",
+         "Alltoall",
+         "216",
+         "1048576",
+         "15",
+         "979838.29",
+         "985415.98",
+         "982015.14",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_27_02-42-36",
+         "3",
+         "100"
+        ],
+        [
+         "2091",
+         "Alltoall",
+         "504",
+         "1048576",
+         "10",
+         "2855777.71",
+         "2866473.68",
+         "2857525.23",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_27_02-42-36",
+         "7",
+         "100"
+        ],
+        [
+         "2810",
+         "Alltoall",
+         "288",
+         "1048576",
+         "27",
+         "1414477.5",
+         "1419906.99",
+         "1417331.44",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_27_02-42-36",
+         "4",
+         "100"
+        ],
+        [
+         "3323",
+         "Alltoall",
+         "144",
+         "1048576",
+         "19",
+         "444484.16",
+         "445342.6",
+         "444940.26",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_27_02-42-36",
+         "2",
+         "100"
+        ]
+       ],
+       "shape": {
+        "columns": 13,
+        "rows": 7
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>benchmark_type</th>\n",
+       "      <th>proc_num</th>\n",
+       "      <th>msg_size_bytes</th>\n",
+       "      <th>repetitions</th>\n",
+       "      <th>t_min_usec</th>\n",
+       "      <th>t_max_usec</th>\n",
+       "      <th>t_avg_usec</th>\n",
+       "      <th>mpi_datatype</th>\n",
+       "      <th>mpi_red_datatype</th>\n",
+       "      <th>mpi_red_op</th>\n",
+       "      <th>creation_time</th>\n",
+       "      <th>n_nodes</th>\n",
+       "      <th>off_cache_flag</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>Alltoall</td>\n",
+       "      <td>360</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>12</td>\n",
+       "      <td>1887068.02</td>\n",
+       "      <td>1888622.38</td>\n",
+       "      <td>1887741.99</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_27_02-42-36</td>\n",
+       "      <td>5</td>\n",
+       "      <td>100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>69</th>\n",
+       "      <td>Alltoall</td>\n",
+       "      <td>576</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>12</td>\n",
+       "      <td>3401545.19</td>\n",
+       "      <td>3413244.99</td>\n",
+       "      <td>3406651.76</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_27_02-42-36</td>\n",
+       "      <td>8</td>\n",
+       "      <td>100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678</th>\n",
+       "      <td>Alltoall</td>\n",
+       "      <td>432</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>17</td>\n",
+       "      <td>2400724.43</td>\n",
+       "      <td>2407984.77</td>\n",
+       "      <td>2404588.58</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_27_02-42-36</td>\n",
+       "      <td>6</td>\n",
+       "      <td>100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>906</th>\n",
+       "      <td>Alltoall</td>\n",
+       "      <td>216</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>15</td>\n",
+       "      <td>979838.29</td>\n",
+       "      <td>985415.98</td>\n",
+       "      <td>982015.14</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_27_02-42-36</td>\n",
+       "      <td>3</td>\n",
+       "      <td>100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2091</th>\n",
+       "      <td>Alltoall</td>\n",
+       "      <td>504</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>10</td>\n",
+       "      <td>2855777.71</td>\n",
+       "      <td>2866473.68</td>\n",
+       "      <td>2857525.23</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_27_02-42-36</td>\n",
+       "      <td>7</td>\n",
+       "      <td>100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2810</th>\n",
+       "      <td>Alltoall</td>\n",
+       "      <td>288</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>27</td>\n",
+       "      <td>1414477.50</td>\n",
+       "      <td>1419906.99</td>\n",
+       "      <td>1417331.44</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_27_02-42-36</td>\n",
+       "      <td>4</td>\n",
+       "      <td>100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3323</th>\n",
+       "      <td>Alltoall</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>19</td>\n",
+       "      <td>444484.16</td>\n",
+       "      <td>445342.60</td>\n",
+       "      <td>444940.26</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_27_02-42-36</td>\n",
+       "      <td>2</td>\n",
+       "      <td>100</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     benchmark_type  proc_num  msg_size_bytes  repetitions  t_min_usec  \\\n",
+       "21         Alltoall       360         1048576           12  1887068.02   \n",
+       "69         Alltoall       576         1048576           12  3401545.19   \n",
+       "678        Alltoall       432         1048576           17  2400724.43   \n",
+       "906        Alltoall       216         1048576           15   979838.29   \n",
+       "2091       Alltoall       504         1048576           10  2855777.71   \n",
+       "2810       Alltoall       288         1048576           27  1414477.50   \n",
+       "3323       Alltoall       144         1048576           19   444484.16   \n",
+       "\n",
+       "      t_max_usec  t_avg_usec mpi_datatype mpi_red_datatype mpi_red_op  \\\n",
+       "21    1888622.38  1887741.99     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "69    3413244.99  3406651.76     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "678   2407984.77  2404588.58     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "906    985415.98   982015.14     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "2091  2866473.68  2857525.23     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "2810  1419906.99  1417331.44     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "3323   445342.60   444940.26     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "\n",
+       "          creation_time  n_nodes  off_cache_flag  \n",
+       "21    25_07_27_02-42-36        5             100  \n",
+       "69    25_07_27_02-42-36        8             100  \n",
+       "678   25_07_27_02-42-36        6             100  \n",
+       "906   25_07_27_02-42-36        3             100  \n",
+       "2091  25_07_27_02-42-36        7             100  \n",
+       "2810  25_07_27_02-42-36        4             100  \n",
+       "3323  25_07_27_02-42-36        2             100  "
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_alltoall[df_alltoall['msg_size_bytes']==1048576]"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "data",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/results-and-plotting/python/notebooks/bcast_analysis.ipynb b/results-and-plotting/python/notebooks/bcast_analysis.ipynb
new file mode 100644
index 0000000..7c7cca5
--- /dev/null
+++ b/results-and-plotting/python/notebooks/bcast_analysis.ipynb
@@ -0,0 +1,175 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "da7c16b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from scipy.optimize import curve_fit\n",
+    "from matplotlib.cm import get_cmap"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47341b1d",
+   "metadata": {},
+   "source": [
+    "# Alltoall "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1cc39aab",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31mnotebook controller is DISPOSED. \n",
+      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
+     ]
+    }
+   ],
+   "source": [
+    "df_multinode = pd.read_csv(\"../data/data-multi-defand100cflag.csv\",delimiter = \",\")\n",
+    "df_multinode['benchmark_type'].unique()\n",
+    "df_gather = df_multinode[df_multinode[\"benchmark_type\"]==\"Bcast\"][df_multinode['msg_size_bytes']>1024][df_multinode['off_cache_flag']==-1]\n",
+    "df_gather.columns.tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4336d3c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31mnotebook controller is DISPOSED. \n",
+      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
+     ]
+    }
+   ],
+   "source": [
+    "def model(proc_num, alpha, beta, msg_size):\n",
+    "    return (alpha * msg_size * (proc_num - 72) * 72) / (12.5 * 1e3) + 1e6*beta\n",
+    "\n",
+    "results = []\n",
+    "msg_sizes = sorted(df_gather['msg_size_bytes'].unique())\n",
+    "n_rows = int(np.ceil(len(msg_sizes) / 3))\n",
+    "n_cols = min(len(msg_sizes), 3)\n",
+    "fig, axes = plt.subplots(n_rows, n_cols, figsize=(5*n_cols, 4*n_rows), squeeze=False)\n",
+    "cmap = get_cmap('tab10')\n",
+    "\n",
+    "for idx, (msg_size, group) in enumerate(df_gather.groupby('msg_size_bytes')):\n",
+    "    x = group['proc_num'].values.copy()\n",
+    "    y = group['t_avg_usec'].values.copy()\n",
+    "    sorted_indices = np.argsort(x)\n",
+    "    x = x[sorted_indices]\n",
+    "    y = y[sorted_indices]\n",
+    "    fit_func = lambda proc_num, alpha, beta: model(proc_num, alpha, beta, msg_size)\n",
+    "    popt, _ = curve_fit(fit_func, x, y, bounds=([1, 0], [np.inf, np.inf]))\n",
+    "    alpha, beta = popt\n",
+    "    results.append({'msg_size_bytes': msg_size, 'alpha': alpha, 'beta': beta})\n",
+    "\n",
+    "    x_fit = np.linspace(min(x), max(x), 100)\n",
+    "    y_fit = fit_func(x_fit, alpha, beta)\n",
+    "    y_speed = model(x_fit,1,0,msg_size)\n",
+    "    row, col = divmod(idx, n_cols)\n",
+    "    ax = axes[row][col]\n",
+    "\n",
+    "    color = cmap(idx % 10)\n",
+    "    # ax.scatter(x, y/1e6, label='Data', color=color)\n",
+    "    ax.plot(x, y/1e6, label='Data', color=color)\n",
+    "    # ax.plot(x_fit, y_fit/1e6, linestyle='--', color=color, alpha=0.5, label='Fit')\n",
+    "    # ax.plot(x_fit, y_speed/1e6, linestyle='--', color='red', alpha=0.1, label='Fit')\n",
+    "    ax.set_title(f'msg_size: {msg_size} bytes')\n",
+    "    ax.set_xlabel('num. proc.')\n",
+    "    ax.set_ylabel('Average Time [s]')\n",
+    "    ax.set_xticks(x)\n",
+    "    ax.grid(True)\n",
+    "    max_data =(x[-1]-72)*72*msg_size\n",
+    "    min_data =(x[0]-72)*72*msg_size\n",
+    "\n",
+    "    textstr = \"\"\n",
+    "    # if(max_data > 1e9):\n",
+    "    #     textstr+=f\"max data = {max_data/1e9:0.2f}GB\\n\" \n",
+    "    # else:\n",
+    "    #     textstr+=f\"max data = {max_data/1e6:0.2f}MB\\n\" \n",
+    "\n",
+    "    # if(min_data > 1e9):\n",
+    "    #     textstr+=f\"min data = {min_data/1e9:0.2f}GB\\n\" \n",
+    "    # else:\n",
+    "    #     textstr+=f\"min data = {min_data/1e6:0.2f}MB\\n\" \n",
+    "    # textstr += r\"$\\alpha$\" +f\"= {alpha:.3e}\\n\"+r\"$b_{eff}=$\"+f\"{12.5/alpha:0.3f}Gbps\\n\"+\\\n",
+    "    #            r\"$\\beta$\"+f\"= {beta:.3e} s\"\n",
+    "    # ax.text(0.95, 0.05, textstr, transform=ax.transAxes,\n",
+    "    #         fontsize=10, verticalalignment='bottom',\n",
+    "    #         horizontalalignment='right',\n",
+    "    #         bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))\n",
+    "\n",
+    "fig.suptitle('Alltoall Time Fit per Message Size\\nDots = Data Points | Dashed Lines = Fits\\n off_mem=-1', fontsize=14)\n",
+    "fig.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
+    "# plt.savefig(\"plots/alltoall_analysis.png\",dpi=300)\n",
+    "plt.show()\n",
+    "\n",
+    "fit_results = pd.DataFrame(results)\n",
+    "fit_results['inv_alpha'] = 1 / fit_results['alpha']\n",
+    "print(fit_results)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ce632d6f",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31mnotebook controller is DISPOSED. \n",
+      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
+     ]
+    }
+   ],
+   "source": [
+    "df_gather[df_gather['msg_size_bytes']==1048576]"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "data",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/results-and-plotting/python/notebooks/gather_analysis.ipynb b/results-and-plotting/python/notebooks/gather_analysis.ipynb
new file mode 100644
index 0000000..98f8f34
--- /dev/null
+++ b/results-and-plotting/python/notebooks/gather_analysis.ipynb
@@ -0,0 +1,588 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "da7c16b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from scipy.optimize import curve_fit\n",
+    "from matplotlib.cm import get_cmap"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47341b1d",
+   "metadata": {},
+   "source": [
+    "# Alltoall "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1cc39aab",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_4897/23514614.py:3: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_gather = df_multinode[df_multinode[\"benchmark_type\"]==\"Gather\"][df_multinode['msg_size_bytes']>1024][df_multinode['off_cache_flag']==-1]\n",
+      "/tmp/ipykernel_4897/23514614.py:3: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_gather = df_multinode[df_multinode[\"benchmark_type\"]==\"Gather\"][df_multinode['msg_size_bytes']>1024][df_multinode['off_cache_flag']==-1]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "['benchmark_type',\n",
+       " 'proc_num',\n",
+       " 'msg_size_bytes',\n",
+       " 'repetitions',\n",
+       " 't_min_usec',\n",
+       " 't_max_usec',\n",
+       " 't_avg_usec',\n",
+       " 'mpi_datatype',\n",
+       " 'mpi_red_datatype',\n",
+       " 'mpi_red_op',\n",
+       " 'creation_time',\n",
+       " 'n_nodes',\n",
+       " 'off_cache_flag']"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "ename": "",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31mnotebook controller is DISPOSED. \n",
+      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
+     ]
+    }
+   ],
+   "source": [
+    "df_multinode = pd.read_csv(\"../data/data-multi-defand100cflag.csv\",delimiter = \",\")\n",
+    "df_multinode['benchmark_type'].unique()\n",
+    "df_gather = df_multinode[df_multinode[\"benchmark_type\"]==\"Gather\"][df_multinode['msg_size_bytes']>1024][df_multinode['off_cache_flag']==-1]\n",
+    "df_gather.columns.tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4336d3c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_4897/866829124.py:9: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.\n",
+      "  cmap = get_cmap('tab10')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1500x1600 with 12 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    msg_size_bytes  alpha          beta  inv_alpha\n",
+      "0             2048    1.0  2.453824e-24        1.0\n",
+      "1             4096    1.0  6.552190e-24        1.0\n",
+      "2             8192    1.0  1.941168e-23        1.0\n",
+      "3            16384    1.0  8.454933e-23        1.0\n",
+      "4            32768    1.0  6.710026e-22        1.0\n",
+      "5            65536    1.0  2.678877e-20        1.0\n",
+      "6           131072    1.0  3.818473e-18        1.0\n",
+      "7           262144    1.0  3.023451e-25        1.0\n",
+      "8           524288    1.0  1.541516e-21        1.0\n",
+      "9          1048576    1.0  1.240501e-16        1.0\n",
+      "10         2097152    1.0  1.165495e-16        1.0\n",
+      "11         4194304    1.0  3.834525e-18        1.0\n"
+     ]
+    },
+    {
+     "ename": "",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31mnotebook controller is DISPOSED. \n",
+      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
+     ]
+    }
+   ],
+   "source": [
+    "def model(proc_num, alpha, beta, msg_size):\n",
+    "    return (alpha * msg_size * (proc_num - 72) * 72) / (12.5 * 1e3) + 1e6*beta\n",
+    "\n",
+    "results = []\n",
+    "msg_sizes = sorted(df_gather['msg_size_bytes'].unique())\n",
+    "n_rows = int(np.ceil(len(msg_sizes) / 3))\n",
+    "n_cols = min(len(msg_sizes), 3)\n",
+    "fig, axes = plt.subplots(n_rows, n_cols, figsize=(5*n_cols, 4*n_rows), squeeze=False)\n",
+    "cmap = get_cmap('tab10')\n",
+    "\n",
+    "for idx, (msg_size, group) in enumerate(df_gather.groupby('msg_size_bytes')):\n",
+    "    x = group['proc_num'].values.copy()\n",
+    "    y = group['t_avg_usec'].values.copy()\n",
+    "    sorted_indices = np.argsort(x)\n",
+    "    x = x[sorted_indices]\n",
+    "    y = y[sorted_indices]\n",
+    "    fit_func = lambda proc_num, alpha, beta: model(proc_num, alpha, beta, msg_size)\n",
+    "    popt, _ = curve_fit(fit_func, x, y, bounds=([1, 0], [np.inf, np.inf]))\n",
+    "    alpha, beta = popt\n",
+    "    results.append({'msg_size_bytes': msg_size, 'alpha': alpha, 'beta': beta})\n",
+    "\n",
+    "    x_fit = np.linspace(min(x), max(x), 100)\n",
+    "    y_fit = fit_func(x_fit, alpha, beta)\n",
+    "    y_speed = model(x_fit,1,0,msg_size)\n",
+    "    row, col = divmod(idx, n_cols)\n",
+    "    ax = axes[row][col]\n",
+    "\n",
+    "    color = cmap(idx % 10)\n",
+    "    # ax.scatter(x, y/1e6, label='Data', color=color)\n",
+    "    ax.plot(x, y/1e6, label='Data', color=color)\n",
+    "    # ax.plot(x_fit, y_fit/1e6, linestyle='--', color=color, alpha=0.5, label='Fit')\n",
+    "    # ax.plot(x_fit, y_speed/1e6, linestyle='--', color='red', alpha=0.1, label='Fit')\n",
+    "    ax.set_title(f'msg_size: {msg_size} bytes')\n",
+    "    ax.set_xlabel('num. proc.')\n",
+    "    ax.set_ylabel('Average Time [s]')\n",
+    "    ax.set_xticks(x)\n",
+    "    ax.grid(True)\n",
+    "    max_data =(x[-1]-72)*72*msg_size\n",
+    "    min_data =(x[0]-72)*72*msg_size\n",
+    "\n",
+    "    textstr = \"\"\n",
+    "    # if(max_data > 1e9):\n",
+    "    #     textstr+=f\"max data = {max_data/1e9:0.2f}GB\\n\" \n",
+    "    # else:\n",
+    "    #     textstr+=f\"max data = {max_data/1e6:0.2f}MB\\n\" \n",
+    "\n",
+    "    # if(min_data > 1e9):\n",
+    "    #     textstr+=f\"min data = {min_data/1e9:0.2f}GB\\n\" \n",
+    "    # else:\n",
+    "    #     textstr+=f\"min data = {min_data/1e6:0.2f}MB\\n\" \n",
+    "    # textstr += r\"$\\alpha$\" +f\"= {alpha:.3e}\\n\"+r\"$b_{eff}=$\"+f\"{12.5/alpha:0.3f}Gbps\\n\"+\\\n",
+    "    #            r\"$\\beta$\"+f\"= {beta:.3e} s\"\n",
+    "    # ax.text(0.95, 0.05, textstr, transform=ax.transAxes,\n",
+    "    #         fontsize=10, verticalalignment='bottom',\n",
+    "    #         horizontalalignment='right',\n",
+    "    #         bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))\n",
+    "\n",
+    "fig.suptitle('Alltoall Time Fit per Message Size\\nDots = Data Points | Dashed Lines = Fits\\n off_mem=-1', fontsize=14)\n",
+    "fig.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
+    "# plt.savefig(\"plots/alltoall_analysis.png\",dpi=300)\n",
+    "plt.show()\n",
+    "\n",
+    "fit_results = pd.DataFrame(results)\n",
+    "fit_results['inv_alpha'] = 1 / fit_results['alpha']\n",
+    "print(fit_results)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ce632d6f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
+       "columns": [
+        {
+         "name": "index",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "benchmark_type",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "proc_num",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "msg_size_bytes",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "repetitions",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "t_min_usec",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "t_max_usec",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "t_avg_usec",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "mpi_datatype",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "mpi_red_datatype",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "mpi_red_op",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "creation_time",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "n_nodes",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "off_cache_flag",
+         "rawType": "int64",
+         "type": "integer"
+        }
+       ],
+       "ref": "606abcbf-7b0e-4a04-9beb-0d5b3e056654",
+       "rows": [
+        [
+         "470",
+         "Gather",
+         "360",
+         "1048576",
+         "40",
+         "233.94",
+         "36747.9",
+         "19914.01",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "5",
+         "-1"
+        ],
+        [
+         "608",
+         "Gather",
+         "432",
+         "1048576",
+         "40",
+         "232.5",
+         "42935.8",
+         "23389.38",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "6",
+         "-1"
+        ],
+        [
+         "1096",
+         "Gather",
+         "504",
+         "1048576",
+         "40",
+         "229.7",
+         "48937.39",
+         "26558.04",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "7",
+         "-1"
+        ],
+        [
+         "1349",
+         "Gather",
+         "144",
+         "1048576",
+         "40",
+         "235.39",
+         "17983.16",
+         "9125.46",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "2",
+         "-1"
+        ],
+        [
+         "2228",
+         "Gather",
+         "288",
+         "1048576",
+         "40",
+         "237.25",
+         "31719.94",
+         "16419.63",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "4",
+         "-1"
+        ],
+        [
+         "3067",
+         "Gather",
+         "216",
+         "1048576",
+         "40",
+         "223.96",
+         "24058.05",
+         "15865.52",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "3",
+         "-1"
+        ]
+       ],
+       "shape": {
+        "columns": 13,
+        "rows": 6
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>benchmark_type</th>\n",
+       "      <th>proc_num</th>\n",
+       "      <th>msg_size_bytes</th>\n",
+       "      <th>repetitions</th>\n",
+       "      <th>t_min_usec</th>\n",
+       "      <th>t_max_usec</th>\n",
+       "      <th>t_avg_usec</th>\n",
+       "      <th>mpi_datatype</th>\n",
+       "      <th>mpi_red_datatype</th>\n",
+       "      <th>mpi_red_op</th>\n",
+       "      <th>creation_time</th>\n",
+       "      <th>n_nodes</th>\n",
+       "      <th>off_cache_flag</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>470</th>\n",
+       "      <td>Gather</td>\n",
+       "      <td>360</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>233.94</td>\n",
+       "      <td>36747.90</td>\n",
+       "      <td>19914.01</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>5</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>608</th>\n",
+       "      <td>Gather</td>\n",
+       "      <td>432</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>232.50</td>\n",
+       "      <td>42935.80</td>\n",
+       "      <td>23389.38</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>6</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1096</th>\n",
+       "      <td>Gather</td>\n",
+       "      <td>504</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>229.70</td>\n",
+       "      <td>48937.39</td>\n",
+       "      <td>26558.04</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>7</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1349</th>\n",
+       "      <td>Gather</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>235.39</td>\n",
+       "      <td>17983.16</td>\n",
+       "      <td>9125.46</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>2</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2228</th>\n",
+       "      <td>Gather</td>\n",
+       "      <td>288</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>237.25</td>\n",
+       "      <td>31719.94</td>\n",
+       "      <td>16419.63</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>4</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3067</th>\n",
+       "      <td>Gather</td>\n",
+       "      <td>216</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>223.96</td>\n",
+       "      <td>24058.05</td>\n",
+       "      <td>15865.52</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>3</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     benchmark_type  proc_num  msg_size_bytes  repetitions  t_min_usec  \\\n",
+       "470          Gather       360         1048576           40      233.94   \n",
+       "608          Gather       432         1048576           40      232.50   \n",
+       "1096         Gather       504         1048576           40      229.70   \n",
+       "1349         Gather       144         1048576           40      235.39   \n",
+       "2228         Gather       288         1048576           40      237.25   \n",
+       "3067         Gather       216         1048576           40      223.96   \n",
+       "\n",
+       "      t_max_usec  t_avg_usec mpi_datatype mpi_red_datatype mpi_red_op  \\\n",
+       "470     36747.90    19914.01     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "608     42935.80    23389.38     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "1096    48937.39    26558.04     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "1349    17983.16     9125.46     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "2228    31719.94    16419.63     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "3067    24058.05    15865.52     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "\n",
+       "          creation_time  n_nodes  off_cache_flag  \n",
+       "470   25_07_26_05-44-37        5              -1  \n",
+       "608   25_07_26_05-44-37        6              -1  \n",
+       "1096  25_07_26_05-44-37        7              -1  \n",
+       "1349  25_07_26_05-44-37        2              -1  \n",
+       "2228  25_07_26_05-44-37        4              -1  \n",
+       "3067  25_07_26_05-44-37        3              -1  "
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "ename": "",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31mnotebook controller is DISPOSED. \n",
+      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
+     ]
+    }
+   ],
+   "source": [
+    "df_gather[df_gather['msg_size_bytes']==1048576]"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "data",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/results-and-plotting/python/notebooks/off_cache_analysis.ipynb b/results-and-plotting/python/notebooks/off_cache_analysis.ipynb
new file mode 100644
index 0000000..83434c2
--- /dev/null
+++ b/results-and-plotting/python/notebooks/off_cache_analysis.ipynb
@@ -0,0 +1,161 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "da7c16b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "original_df= pd.read_csv(\"data/data-single-multi-original.csv\",delimiter=\",\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "9ba9bfd9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "df = original_df.copy()\n",
+    "df = df.fillna(\"None\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "85c7c7d3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['Allreduce', 'Scatterv', 'Gather', 'Alltoall', 'Allgatherv',\n",
+       "       'Gatherv', 'Bcast', 'Reduce', 'Reduce_scatter', 'Scatter',\n",
+       "       'Allgather'], dtype=object)"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "msg_sizes = df['msg_size_bytes'].unique().copy()\n",
+    "msg_sizes.sort()\n",
+    "msg_sizes.tolist()\n",
+    "small_msg = msg_sizes[msg_sizes<4097]\n",
+    "big_msg = msg_sizes[msg_sizes>=4097]\n",
+    "small_msg,big_msg\n",
+    "sub_benchmarks = ['Allreduce','Gather','Scatter','Alltoall','Allgather']\n",
+    "df['benchmark_type'].unique()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2f2ebfba",
+   "metadata": {},
+   "source": [
+    "### Effect of OFF-CHACHE-FLAG"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "6bca1dad",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "df_subb = df[df['benchmark_type'].isin(sub_benchmarks)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "37d6731a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 2811.11x1500 with 45 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g_small = sns.FacetGrid(df_subb[df_subb['msg_size_bytes'].isin(small_msg)], row='benchmark_type', col='proc_num', hue='off_cache_flag', margin_titles=True, sharey=False,sharex=True,despine=False)\n",
+    "g_small.map_dataframe(sns.lineplot, x='msg_size_bytes', y='t_avg_usec')\n",
+    "# g_small.set(xscale=\"log2\", yscale=\"linear\")\n",
+    "for ax in g_small.axes.flat:\n",
+    "    ax.set_xscale(\"log\",base=2)\n",
+    "g_small.add_legend()\n",
+    "g_small.set_axis_labels(\"Message Size (bytes)\", r\"Avg Time ($\\mu$s)\")\n",
+    "plt.subplots_adjust(top=0.9)\n",
+    "g_small.figure.suptitle(\"MPI Benchmark: Offmem Impact on Avg Time (Message Size < 4kb)\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "ab5719ea",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 2811.11x1500 with 45 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g_big = sns.FacetGrid(df_subb[df_subb['msg_size_bytes'].isin(big_msg)], row='benchmark_type', col='proc_num', hue='off_cache_flag', margin_titles=True, sharey=False,sharex=True,despine=False)\n",
+    "g_big.map_dataframe(sns.lineplot, x='msg_size_bytes', y='t_avg_usec')\n",
+    "# g_big.set(xscale=\"linear\", yscale=\"linear\")\n",
+    "for ax in g_big.axes.flat:\n",
+    "    ax.set_xscale(\"log\",base=2)\n",
+    "g_big.add_legend()\n",
+    "g_big.set_axis_labels(\"Message Size (bytes)\", r\"Avg Time ($\\mu$s)\")\n",
+    "plt.subplots_adjust(top=0.9)\n",
+    "g_big.figure.suptitle(\"MPI Benchmark: Offmem Impact on Avg Time (Message Size > 4kb)\")\n",
+    "plt.savefig(\"plots/off_cache_flag_effect1.png\")\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "data",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/results-and-plotting/python/notebooks/scatter_analysis.ipynb b/results-and-plotting/python/notebooks/scatter_analysis.ipynb
new file mode 100644
index 0000000..5146be6
--- /dev/null
+++ b/results-and-plotting/python/notebooks/scatter_analysis.ipynb
@@ -0,0 +1,561 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "da7c16b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from scipy.optimize import curve_fit\n",
+    "from matplotlib.cm import get_cmap"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47341b1d",
+   "metadata": {},
+   "source": [
+    "# Alltoall "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1cc39aab",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_6251/1773704290.py:3: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_gather = df_multinode[df_multinode[\"benchmark_type\"]==\"Scatter\"][df_multinode['msg_size_bytes']>1024][df_multinode['off_cache_flag']==-1]\n",
+      "/tmp/ipykernel_6251/1773704290.py:3: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  df_gather = df_multinode[df_multinode[\"benchmark_type\"]==\"Scatter\"][df_multinode['msg_size_bytes']>1024][df_multinode['off_cache_flag']==-1]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "['benchmark_type',\n",
+       " 'proc_num',\n",
+       " 'msg_size_bytes',\n",
+       " 'repetitions',\n",
+       " 't_min_usec',\n",
+       " 't_max_usec',\n",
+       " 't_avg_usec',\n",
+       " 'mpi_datatype',\n",
+       " 'mpi_red_datatype',\n",
+       " 'mpi_red_op',\n",
+       " 'creation_time',\n",
+       " 'n_nodes',\n",
+       " 'off_cache_flag']"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_multinode = pd.read_csv(\"../data/data-multi-defand100cflag.csv\",delimiter = \",\")\n",
+    "df_multinode['benchmark_type'].unique()\n",
+    "df_gather = df_multinode[df_multinode[\"benchmark_type\"]==\"Scatter\"][df_multinode['msg_size_bytes']>1024][df_multinode['off_cache_flag']==-1]\n",
+    "df_gather.columns.tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "4336d3c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_6251/2016121029.py:9: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.\n",
+      "  cmap = get_cmap('tab10')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1500x1600 with 12 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    msg_size_bytes  alpha          beta  inv_alpha\n",
+      "0             2048    1.0  1.653129e-23        1.0\n",
+      "1             4096    1.0  2.784707e-23        1.0\n",
+      "2             8192    1.0  7.739935e-23        1.0\n",
+      "3            16384    1.0  2.497581e-22        1.0\n",
+      "4            32768    1.0  1.052599e-21        1.0\n",
+      "5            65536    1.0  2.254095e-20        1.0\n",
+      "6           131072    1.0  3.401592e-18        1.0\n",
+      "7           262144    1.0  2.229240e-17        1.0\n",
+      "8           524288    1.0  1.527509e-21        1.0\n",
+      "9          1048576    1.0  2.287381e-24        1.0\n",
+      "10         2097152    1.0  1.160941e-16        1.0\n",
+      "11         4194304    1.0  4.068531e-18        1.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "def model(proc_num, alpha, beta, msg_size):\n",
+    "    return (alpha * msg_size * (proc_num - 72) * 72) / (12.5 * 1e3) + 1e6*beta\n",
+    "\n",
+    "results = []\n",
+    "msg_sizes = sorted(df_gather['msg_size_bytes'].unique())\n",
+    "n_rows = int(np.ceil(len(msg_sizes) / 3))\n",
+    "n_cols = min(len(msg_sizes), 3)\n",
+    "fig, axes = plt.subplots(n_rows, n_cols, figsize=(5*n_cols, 4*n_rows), squeeze=False)\n",
+    "cmap = get_cmap('tab10')\n",
+    "\n",
+    "for idx, (msg_size, group) in enumerate(df_gather.groupby('msg_size_bytes')):\n",
+    "    x = group['proc_num'].values.copy()\n",
+    "    y = group['t_avg_usec'].values.copy()\n",
+    "    sorted_indices = np.argsort(x)\n",
+    "    x = x[sorted_indices]\n",
+    "    y = y[sorted_indices]\n",
+    "    fit_func = lambda proc_num, alpha, beta: model(proc_num, alpha, beta, msg_size)\n",
+    "    popt, _ = curve_fit(fit_func, x, y, bounds=([1, 0], [np.inf, np.inf]))\n",
+    "    alpha, beta = popt\n",
+    "    results.append({'msg_size_bytes': msg_size, 'alpha': alpha, 'beta': beta})\n",
+    "\n",
+    "    x_fit = np.linspace(min(x), max(x), 100)\n",
+    "    y_fit = fit_func(x_fit, alpha, beta)\n",
+    "    y_speed = model(x_fit,1,0,msg_size)\n",
+    "    row, col = divmod(idx, n_cols)\n",
+    "    ax = axes[row][col]\n",
+    "\n",
+    "    color = cmap(idx % 10)\n",
+    "    # ax.scatter(x, y/1e6, label='Data', color=color)\n",
+    "    ax.plot(x, y/1e6, label='Data', color=color)\n",
+    "    # ax.plot(x_fit, y_fit/1e6, linestyle='--', color=color, alpha=0.5, label='Fit')\n",
+    "    # ax.plot(x_fit, y_speed/1e6, linestyle='--', color='red', alpha=0.1, label='Fit')\n",
+    "    ax.set_title(f'msg_size: {msg_size} bytes')\n",
+    "    ax.set_xlabel('num. proc.')\n",
+    "    ax.set_ylabel('Average Time [s]')\n",
+    "    ax.set_xticks(x)\n",
+    "    ax.grid(True)\n",
+    "    max_data =(x[-1]-72)*72*msg_size\n",
+    "    min_data =(x[0]-72)*72*msg_size\n",
+    "\n",
+    "    textstr = \"\"\n",
+    "    # if(max_data > 1e9):\n",
+    "    #     textstr+=f\"max data = {max_data/1e9:0.2f}GB\\n\" \n",
+    "    # else:\n",
+    "    #     textstr+=f\"max data = {max_data/1e6:0.2f}MB\\n\" \n",
+    "\n",
+    "    # if(min_data > 1e9):\n",
+    "    #     textstr+=f\"min data = {min_data/1e9:0.2f}GB\\n\" \n",
+    "    # else:\n",
+    "    #     textstr+=f\"min data = {min_data/1e6:0.2f}MB\\n\" \n",
+    "    # textstr += r\"$\\alpha$\" +f\"= {alpha:.3e}\\n\"+r\"$b_{eff}=$\"+f\"{12.5/alpha:0.3f}Gbps\\n\"+\\\n",
+    "    #            r\"$\\beta$\"+f\"= {beta:.3e} s\"\n",
+    "    # ax.text(0.95, 0.05, textstr, transform=ax.transAxes,\n",
+    "    #         fontsize=10, verticalalignment='bottom',\n",
+    "    #         horizontalalignment='right',\n",
+    "    #         bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))\n",
+    "\n",
+    "fig.suptitle('Alltoall Time Fit per Message Size\\nDots = Data Points | Dashed Lines = Fits\\n off_mem=-1', fontsize=14)\n",
+    "fig.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
+    "# plt.savefig(\"plots/alltoall_analysis.png\",dpi=300)\n",
+    "plt.show()\n",
+    "\n",
+    "fit_results = pd.DataFrame(results)\n",
+    "fit_results['inv_alpha'] = 1 / fit_results['alpha']\n",
+    "print(fit_results)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "ce632d6f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
+       "columns": [
+        {
+         "name": "index",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "benchmark_type",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "proc_num",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "msg_size_bytes",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "repetitions",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "t_min_usec",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "t_max_usec",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "t_avg_usec",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "mpi_datatype",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "mpi_red_datatype",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "mpi_red_op",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "creation_time",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "n_nodes",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "off_cache_flag",
+         "rawType": "int64",
+         "type": "integer"
+        }
+       ],
+       "ref": "70a77f68-cef6-41c4-85bc-7c49e07a3835",
+       "rows": [
+        [
+         "161",
+         "Scatter",
+         "288",
+         "1048576",
+         "40",
+         "348.13",
+         "18588.13",
+         "13870.72",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "4",
+         "-1"
+        ],
+        [
+         "232",
+         "Scatter",
+         "360",
+         "1048576",
+         "40",
+         "5343.85",
+         "24788.75",
+         "18554.78",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "5",
+         "-1"
+        ],
+        [
+         "516",
+         "Scatter",
+         "504",
+         "1048576",
+         "40",
+         "4431.12",
+         "37015.58",
+         "28247.29",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "7",
+         "-1"
+        ],
+        [
+         "930",
+         "Scatter",
+         "144",
+         "1048576",
+         "40",
+         "330.36",
+         "6271.05",
+         "5786.19",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "2",
+         "-1"
+        ],
+        [
+         "1837",
+         "Scatter",
+         "432",
+         "1048576",
+         "40",
+         "348.51",
+         "30875.3",
+         "23317.92",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "6",
+         "-1"
+        ],
+        [
+         "2368",
+         "Scatter",
+         "216",
+         "1048576",
+         "40",
+         "4521.16",
+         "12403.88",
+         "9908.28",
+         "MPI_BYTE",
+         "MPI_FLOAT",
+         "MPI_SUM",
+         "25_07_26_05-44-37",
+         "3",
+         "-1"
+        ]
+       ],
+       "shape": {
+        "columns": 13,
+        "rows": 6
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>benchmark_type</th>\n",
+       "      <th>proc_num</th>\n",
+       "      <th>msg_size_bytes</th>\n",
+       "      <th>repetitions</th>\n",
+       "      <th>t_min_usec</th>\n",
+       "      <th>t_max_usec</th>\n",
+       "      <th>t_avg_usec</th>\n",
+       "      <th>mpi_datatype</th>\n",
+       "      <th>mpi_red_datatype</th>\n",
+       "      <th>mpi_red_op</th>\n",
+       "      <th>creation_time</th>\n",
+       "      <th>n_nodes</th>\n",
+       "      <th>off_cache_flag</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>161</th>\n",
+       "      <td>Scatter</td>\n",
+       "      <td>288</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>348.13</td>\n",
+       "      <td>18588.13</td>\n",
+       "      <td>13870.72</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>4</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>232</th>\n",
+       "      <td>Scatter</td>\n",
+       "      <td>360</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>5343.85</td>\n",
+       "      <td>24788.75</td>\n",
+       "      <td>18554.78</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>5</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>516</th>\n",
+       "      <td>Scatter</td>\n",
+       "      <td>504</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>4431.12</td>\n",
+       "      <td>37015.58</td>\n",
+       "      <td>28247.29</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>7</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>930</th>\n",
+       "      <td>Scatter</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>330.36</td>\n",
+       "      <td>6271.05</td>\n",
+       "      <td>5786.19</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>2</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1837</th>\n",
+       "      <td>Scatter</td>\n",
+       "      <td>432</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>348.51</td>\n",
+       "      <td>30875.30</td>\n",
+       "      <td>23317.92</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>6</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2368</th>\n",
+       "      <td>Scatter</td>\n",
+       "      <td>216</td>\n",
+       "      <td>1048576</td>\n",
+       "      <td>40</td>\n",
+       "      <td>4521.16</td>\n",
+       "      <td>12403.88</td>\n",
+       "      <td>9908.28</td>\n",
+       "      <td>MPI_BYTE</td>\n",
+       "      <td>MPI_FLOAT</td>\n",
+       "      <td>MPI_SUM</td>\n",
+       "      <td>25_07_26_05-44-37</td>\n",
+       "      <td>3</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     benchmark_type  proc_num  msg_size_bytes  repetitions  t_min_usec  \\\n",
+       "161         Scatter       288         1048576           40      348.13   \n",
+       "232         Scatter       360         1048576           40     5343.85   \n",
+       "516         Scatter       504         1048576           40     4431.12   \n",
+       "930         Scatter       144         1048576           40      330.36   \n",
+       "1837        Scatter       432         1048576           40      348.51   \n",
+       "2368        Scatter       216         1048576           40     4521.16   \n",
+       "\n",
+       "      t_max_usec  t_avg_usec mpi_datatype mpi_red_datatype mpi_red_op  \\\n",
+       "161     18588.13    13870.72     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "232     24788.75    18554.78     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "516     37015.58    28247.29     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "930      6271.05     5786.19     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "1837    30875.30    23317.92     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "2368    12403.88     9908.28     MPI_BYTE        MPI_FLOAT    MPI_SUM   \n",
+       "\n",
+       "          creation_time  n_nodes  off_cache_flag  \n",
+       "161   25_07_26_05-44-37        4              -1  \n",
+       "232   25_07_26_05-44-37        5              -1  \n",
+       "516   25_07_26_05-44-37        7              -1  \n",
+       "930   25_07_26_05-44-37        2              -1  \n",
+       "1837  25_07_26_05-44-37        6              -1  \n",
+       "2368  25_07_26_05-44-37        3              -1  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_gather[df_gather['msg_size_bytes']==1048576]"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "data",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}