Measure memory transfer of CPU to GPU, add explanation how to distribute calculation among multiple GPUs
This commit is contained in:
		| @@ -144,10 +144,15 @@ double computeForce( | ||||
|     for(int i = 0; i < nDevices; ++i) { | ||||
|         cudaDeviceProp prop; | ||||
|         cudaGetDeviceProperties(&prop, i); | ||||
|         printf("DEVICE NAME: %s\r\n", prop.name); | ||||
|         printf("DEVICE %d/%d NAME: %s\r\n", i + 1, nDevices, prop.name); | ||||
|     } | ||||
|  | ||||
|     // Choose GPU where you want to execute code on | ||||
|     // It is possible to execute the same kernel on multiple GPUs but you have to copy the data multiple times | ||||
|     // Executing `cudaSetDevice(N)` before cudaMalloc / cudaMemcpy / calc_force <<< >>> will set the GPU accordingly | ||||
|     */ | ||||
|  | ||||
|  | ||||
|     // HINT: Run with cuda-memcheck ./MDBench-NVCC in case of error | ||||
|     // HINT: Only works for data layout = AOS!!! | ||||
|  | ||||
|   | ||||
		Reference in New Issue
	
	Block a user