我尝试使用OpenMP并行化以下代码。
#pragma omp parallel for collapse(2)
{
for (int mNdx = 0; mNdx < M; ++mNdx)
{
for (int nNdx = mNdx; nNdx < N; ++nNdx)
{
for (int elemNdx = mNdx; elemNdx <= nNdx; ++elemNdx)
{
result[mNdx * N + nNdx] += matrixOne[mNdx * N + elemNdx] * matrixTwo[elemNdx * N + nNdx];
}
}
}
}
但SpeedUp总是大约1.0(+ - 0.05)。我尝试了所有可能的调度(自动,动态,静态和引导),不同的块大小,没有崩溃和崩溃(2)。 运行时根本不会改变......
任何人都能解释我为什么或在哪里犯错?
可能是由于自动化的for循环编译器并行化?
提前感谢任何建议/提示!
更新
根据需要提供可验证的示例。
#include <omp.h>
#include <iostream>
void initMatrix(float* mat, const int M, const int N);
void initResMatrix(float* mat, const int M, const int N);
double matMulUpperTriangular_C(float* matrixOne, float* matrixTwo, float* result, const int M, const int N);
double matMulUpperTriangular_Omp(float* matrixOne, float* matrixTwo, float* result, const int M, const int N);
int main()
{
const int M = 2048, N = 2048;
float* matOne = (float*)malloc(M * N * sizeof(float));
float* matTwo = (float*)malloc(M * N * sizeof(float));
float* res = (float*)malloc(M * N * sizeof(float));
initMatrix(matOne, M, N);
initMatrix(matTwo, M, N);
initResMatrix(res, M, N);
double timeConsumption[2] = { 0.0, 0.0 };
timeConsumption[0] = matMulUpperTriangular_C(matOne, matTwo, res, M, N);
timeConsumption[1] = matMulUpperTriangular_Omp(matOne, matTwo, res, M, N);
std::cout << "Runtime C:\t\t" << timeConsumption[0] << "s" << std::endl;
std::cout << "Runtime Omp:\t\t" << timeConsumption[1] << "s";
std::cout << " | SpeedUp: " << timeConsumption[0] / timeConsumption[1] << std::endl;
system("PAUSE");
return 0;
}
void initMatrix(float* mat, const int M, const int N)
{
for (int mNdx = 0; mNdx < M; ++mNdx)
{
for (int nNdx = 0; nNdx < mNdx; ++nNdx)
{
mat[mNdx * N + nNdx] = 0;
}
for (int nNdx = mNdx; nNdx < N; ++nNdx)
{
mat[mNdx * N + nNdx] = ((mNdx + nNdx) % 5 + 1) * 0.1f;
}
}
}
void initResMatrix(float* mat, const int M, const int N)
{
for (int mNdx = 0; mNdx < M; ++mNdx)
{
for (int nNdx = 0; nNdx < N; ++nNdx)
{
mat[mNdx * N + nNdx] = 0.0f;
}
}
}
double matMulUpperTriangular_C(float* matrixOne, float* matrixTwo, float* result, const int M, const int N)
{
double startTime = omp_get_wtime();
for (int mNdx = 0; mNdx < M; ++mNdx)
{
for (int nNdx = mNdx; nNdx < N; ++nNdx)
{
for (int elemNdx = mNdx; elemNdx <= nNdx; ++elemNdx)
{
result[mNdx * N + nNdx] += matrixOne[mNdx * N + elemNdx] * matrixTwo[elemNdx * N + nNdx];
}
}
}
double endTime = omp_get_wtime();
return endTime - startTime;
}
double matMulUpperTriangular_Omp(float* matrixOne, float* matrixTwo, float* result, const int M, const int N)
{
double startTime = omp_get_wtime();
#pragma omp parallel for collapse(2)
{
for (int mNdx = 0; mNdx < M; ++mNdx)
{
for (int nNdx = mNdx; nNdx < N; ++nNdx)
{
for (int elemNdx = mNdx; elemNdx <= nNdx; ++elemNdx)
{
result[mNdx * N + nNdx] += matrixOne[mNdx * N + elemNdx] * matrixTwo[elemNdx * N + nNdx];
}
}
}
}
double endTime = omp_get_wtime();
return endTime - startTime;
}
解决:
愚蠢的错误...... 已设置/ MP-Flag(使用多个进程构建)而不是/ openmp。 现在SpeedUp大概是2.0:)
很抱歉,谢谢大家的帮助!