批改娘 10104. Streams and Concurrency (CUDA)

contents

  1. 1. 題目描述
  2. 2. 測試流程
    1. 2.1. profiler script
    2. 2.2. 編譯執行
  3. 3. Solution

題目描述

根據 Nvidia - Streams and Concurrency 讓 Data transfer 和 Kernel execute 時間重疊達到加速。

  • 任何程式都可以
  • 沒有指定輸入、輸出

測試流程

profiler script

下載 nvprof.sh 和 nvvp.log

編譯執行

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$ chmod +x nvprof.sh
$ nvcc -Xcompiler "-O2 -fopenmp" main.cu -o main
$ ./nvprof.sh ./main
$ cat nvvp.log

Accepted 判斷依準:單一 Device 是否在運行過程中發生并行。

Accepted

Wrong Answer

Solution

出這一題是為了測試 software pipeline 的設計,加快批次處理的效能,藉由數個 stream 的使用,讓資料傳輸和計算相互重疊。

這一題讓我設計測試 Judge 相當懊惱,藉由 Nvidia 提供環境變數的 debug 資訊產生的 log 檔就能分析執行區間是否有重疊,這個問題就迎刃而解。當然此題不在課程範圍內,提案給老師說要不要教,預料中地被打槍。

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/* Copyright (c) 1993-2015, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/


#include <stdio.h>

// Convenience function for checking CUDA runtime API results
// can be wrapped around any runtime API call. No-op in release builds.
inline
cudaError_t checkCuda(cudaError_t result)
{

#if defined(DEBUG) || defined(_DEBUG)
if (result != cudaSuccess) {
fprintf(stderr, "CUDA Runtime Error: %s\n", cudaGetErrorString(result));
assert(result == cudaSuccess);
}
#endif
return result;
}

__global__ void kernel(float *a, int offset)
{

int i = offset + threadIdx.x + blockIdx.x*blockDim.x;
float x = (float)i;
float s = sinf(x);
float c = cosf(x);
a[i] = a[i] + sqrtf(s*s+c*c);
}

float maxError(float *a, int n)
{

float maxE = 0;
for (int i = 0; i < n; i++) {
float error = fabs(a[i]-1.0f);
if (error > maxE) maxE = error;
}
return maxE;
}

int main(int argc, char **argv)
{

const int blockSize = 256, nStreams = 4;
const int n = 4 * 1024 * blockSize * nStreams;
const int streamSize = n / nStreams;
const int streamBytes = streamSize * sizeof(float);
const int bytes = n * sizeof(float);

int devId = 0;
if (argc > 1) devId = atoi(argv[1]);

cudaDeviceProp prop;
checkCuda( cudaGetDeviceProperties(&prop, devId));
printf("Device : %s\n", prop.name);
checkCuda( cudaSetDevice(devId) );

// allocate pinned host memory and device memory
float *a, *d_a;
checkCuda( cudaMallocHost((void**)&a, bytes) ); // host pinned
checkCuda( cudaMalloc((void**)&d_a, bytes) ); // device

float ms; // elapsed time in milliseconds

// create events and streams
cudaEvent_t startEvent, stopEvent, dummyEvent;
cudaStream_t stream[nStreams];
checkCuda( cudaEventCreate(&startEvent) );
checkCuda( cudaEventCreate(&stopEvent) );
checkCuda( cudaEventCreate(&dummyEvent) );
for (int i = 0; i < nStreams; ++i)
checkCuda( cudaStreamCreate(&stream[i]) );

// baseline case - sequential transfer and execute
memset(a, 0, bytes);
checkCuda( cudaEventRecord(startEvent,0) );
checkCuda( cudaMemcpy(d_a, a, bytes, cudaMemcpyHostToDevice) );
kernel<<<n/blockSize, blockSize>>>(d_a, 0);
checkCuda( cudaMemcpy(a, d_a, bytes, cudaMemcpyDeviceToHost) );
checkCuda( cudaEventRecord(stopEvent, 0) );
checkCuda( cudaEventSynchronize(stopEvent) );
checkCuda( cudaEventElapsedTime(&ms, startEvent, stopEvent) );
printf("Time for sequential transfer and execute (ms): %f\n", ms);
printf(" max error: %e\n", maxError(a, n));
// asynchronous version 1: loop over {copy, kernel, copy}
memset(a, 0, bytes);
checkCuda( cudaEventRecord(startEvent,0) );
for (int i = 0; i < nStreams; ++i) {
int offset = i * streamSize;
checkCuda( cudaMemcpyAsync(&d_a[offset], &a[offset],
streamBytes, cudaMemcpyHostToDevice,
stream[i]) );
kernel<<<streamSize/blockSize, blockSize, 0, stream[i]>>>(d_a, offset);
checkCuda( cudaMemcpyAsync(&a[offset], &d_a[offset],
streamBytes, cudaMemcpyDeviceToHost,
stream[i]) );
}
checkCuda( cudaEventRecord(stopEvent, 0) );
checkCuda( cudaEventSynchronize(stopEvent) );
checkCuda( cudaEventElapsedTime(&ms, startEvent, stopEvent) );
printf("Time for asynchronous V1 transfer and execute (ms): %f\n", ms);
printf(" max error: %e\n", maxError(a, n));

// asynchronous version 2:
// loop over copy, loop over kernel, loop over copy
memset(a, 0, bytes);
checkCuda( cudaEventRecord(startEvent,0) );
for (int i = 0; i < nStreams; ++i)
{
int offset = i * streamSize;
checkCuda( cudaMemcpyAsync(&d_a[offset], &a[offset],
streamBytes, cudaMemcpyHostToDevice,
stream[i]) );
}
for (int i = 0; i < nStreams; ++i)
{
int offset = i * streamSize;
kernel<<<streamSize/blockSize, blockSize, 0, stream[i]>>>(d_a, offset);
}
for (int i = 0; i < nStreams; ++i)
{
int offset = i * streamSize;
checkCuda( cudaMemcpyAsync(&a[offset], &d_a[offset],
streamBytes, cudaMemcpyDeviceToHost,
stream[i]) );
}
checkCuda( cudaEventRecord(stopEvent, 0) );
checkCuda( cudaEventSynchronize(stopEvent) );
checkCuda( cudaEventElapsedTime(&ms, startEvent, stopEvent) );
printf("Time for asynchronous V2 transfer and execute (ms): %f\n", ms);
printf(" max error: %e\n", maxError(a, n));

// cleanup
checkCuda( cudaEventDestroy(startEvent) );
checkCuda( cudaEventDestroy(stopEvent) );
checkCuda( cudaEventDestroy(dummyEvent) );
for (int i = 0; i < nStreams; ++i)
checkCuda( cudaStreamDestroy(stream[i]) );
cudaFree(d_a);
cudaFreeHost(a);

return 0;
}