67 lines
2.5 KiB
Python
67 lines
2.5 KiB
Python
import pandas as pd
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import matplotlib.pyplot as plt
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import seaborn as sns
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import numpy as np
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from mpl_toolkits.mplot3d import Axes3D
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data_file = "data/data-multi-defand100cflag.csv"
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df_multinode = pd.read_csv(data_file, delimiter=',')
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df_multinode_offdef = df_multinode[df_multinode['off_cache_flag'] == 100]
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df_multinode_offdef = df_multinode_offdef[['benchmark_type','msg_size_bytes','t_avg_usec','proc_num']]
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benchmarks = df_multinode_offdef['benchmark_type'].unique().tolist()
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benchmarks = [x for x in benchmarks if x[-1] != 'v']
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df_multinode_offdef = df_multinode_offdef[df_multinode_offdef['benchmark_type'].isin(
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benchmarks)][df_multinode_offdef['msg_size_bytes'] > 1000]
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# fast_benchmarks = ["Allreduce","Bcast","Reduce","Reduce_scatter"]
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medium_benchmarks = ["Gather","Scatter"]
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df_multinode_offdef = df_multinode_offdef[df_multinode_offdef["benchmark_type"].isin(medium_benchmarks)]
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plt.figure(figsize=(16, 9))
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sns.barplot(
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data=df_multinode_offdef,
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x="benchmark_type",
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y="t_avg_usec",
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dodge=True,
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hue=df_multinode_offdef["msg_size_bytes"].astype(str),
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)
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plt.ylim(0)
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plt.title("Average Time (usec) per Benchmark Type and Message Size")
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plt.ylabel("Average Time (usec)")
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plt.xlabel("Benchmark Type")
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plt.xticks(rotation=45)
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plt.legend(title="Message Size (bytes)")
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plt.tight_layout()
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plt.savefig("./plots/mbenchmarks_avg_time_barplot.png", dpi=300)
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plt.close()
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df_gather = df_multinode_offdef[df_multinode_offdef['benchmark_type']=='Gather']
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df_gather = df_gather[['msg_size_bytes','t_avg_usec','proc_num']]
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df_gather = df_gather[df_gather['msg_size_bytes']>2**17]
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pivot = df_gather.pivot(index="msg_size_bytes", columns="proc_num", values="t_avg_usec")
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X = pivot.columns.values # proc_num
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Y = pivot.index.values # msg_size_bytes
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X, Y = np.meshgrid(X, Y)
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Z = pivot.values
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fig = plt.figure(figsize=(16, 9))
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ax = fig.add_subplot(111, projection='3d')
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surf = ax.plot_surface(X, Y, Z, cmap="viridis", edgecolor='k')
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cbar = fig.colorbar(surf, ax=ax, shrink=0.6, pad=0.01, location='left')
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cbar.set_label("Average Time (μs)")
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ax.set_xlabel("Process Count")
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ax.set_ylabel("Message Size (B)")
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ax.set_zlabel("Average Time (μs)")
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ax.set_title("Gather")
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ax.set_xticks(pivot.columns.values) # use the actual process count values
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ax.set_xticklabels(pivot.columns.values)
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ax.set_yticks(Y[:, 0])
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ymin, ymax = ax.get_ylim()
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ax.set_ylim(ymin*0.8, ymax) # 30% more space at top
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ax.set_yticklabels([f"$2^{{{int(np.log2(v))}}}$" for v in Y[:, 0]])
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plt.tight_layout()
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plt.savefig("./plots/gather_surface.png", dpi=300)
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plt.close()
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