openmp代码（并行）与串行代码

时间：2015-09-23 17:27:34

标签： parallel-processing openmp performance-testing

如何比较并行代码（使用OpenMP）与串行代码的性能？我使用以下方法

int arr[1000] = {1, 6, 1, 3, 1, 9, 7, 3, 2, 0, 5, 0, 8, 9, 8, 4, 4, 4, 0, 9, 6, 5, 9, 5, 9, 2, 5, 8, 6, 1, 0, 7, 7, 3, 2, 8, 3, 2, 3, 7, 2, 0, 7, 2, 9, 5, 8, 6, 2, 8, 5, 8, 5, 6, 3, 5, 8, 1, 3, 7, 2, 6, 6, 2, 1, 9, 0, 6, 1, 6, 3, 5, 6, 3, 0, 8, 0, 8, 4, 2, 7, 1, 0, 2, 7, 6, 9, 7, 7, 5, 4, 9, 3, 1, 1, 4, 2, 4, 1, 5, 2, 6, 0, 8, 9, 2, 6, 0, 1, 0, 2, 0, 3, 3, 4, 0, 1, 4, 8, 8, 1, 4, 9, 4, 7, 3, 8, 9, 9, 1, 4, 1, 8, 7, 9, 9, 9, 8, 9, 0, 0, 4, 2, 4, 9, 7, 6, 0, 3, 4, 8, 6, 1, 9, 0, 8, 2, 0, 8, 1, 2, 4, 2, 2, 1, 4, 1, 1, 4, 3, 3, 4, 9, 8, 0, 8, 7, 7, 8, 0, 3, 8, 8, 4, 7, 8, 5, 2, 0, 3, 3, 4, 9, 8, 6, 1, 4, 0, 4, 8, 5, 9, 4, 4, 7, 5, 2, 4, 2, 2, 6, 5, 2, 4, 2, 1, 4, 7, 3, 5, 2, 7, 9, 1, 7, 8, 4, 3, 0, 8, 1, 5, 8, 7, 1, 7, 2, 5, 2, 6, 9, 8, 2, 1, 5, 4, 2, 9, 1, 6, 6, 5, 5, 8, 6, 4, 6, 1, 7, 8, 1, 0, 3, 9, 7, 6, 7, 2, 1, 1, 8, 2, 9, 2, 3, 6, 8, 7, 8, 9, 5, 4, 4, 2, 2, 3, 6, 8, 4, 5, 6, 5, 7, 1, 7, 7, 9, 6, 9, 2, 7, 9, 4, 8, 2, 7, 5, 0, 7, 3, 2, 2, 9, 8, 7, 2, 3, 5, 2, 9, 1, 1, 5, 8, 4, 4, 5, 4, 0, 6, 6, 9, 8, 1, 7, 0, 0, 4, 2, 7, 9, 6, 2, 9, 7, 9, 1, 0, 4, 3, 0, 7, 6, 7, 8, 1, 1, 5, 5, 3, 4, 3, 2, 2, 4, 1, 2, 7, 6, 6, 4, 5, 3, 8, 4, 2, 9, 7, 2, 6, 3, 4, 3, 9, 1, 1, 0, 4, 9, 5, 7, 3, 9, 1, 5, 5, 5, 9, 2, 3, 5, 9, 8, 0, 9, 5, 2, 9, 4, 7, 5, 7, 1, 0, 7, 5, 4, 7, 9, 3, 5, 9, 8, 6, 2, 3, 1, 7, 2, 6, 0, 9, 7, 1, 2, 6, 8, 4, 5, 2, 3, 2, 2, 7, 3, 9, 2, 9, 6, 3, 2, 3, 2, 2, 9, 7, 5, 3, 4, 9, 9, 7, 8, 6, 0, 0, 4, 0, 7, 2, 4, 0, 4, 6, 9, 9, 5, 1, 0, 4, 5, 4, 7, 9, 6, 9, 6, 1, 2, 3, 0, 3, 2, 1, 1, 4, 1, 5, 4, 0, 7, 8, 3, 4, 5, 2, 5, 2, 6, 6, 6, 1, 0, 6, 2, 9, 5, 1, 0, 9, 6, 3, 4, 8, 4, 5, 2, 7, 2, 8, 8, 2, 6, 1, 6, 3, 5, 3, 6, 1, 1, 4, 4, 2, 0, 7, 1, 7, 0, 3, 8, 6, 6, 2, 6, 2, 7, 0, 0, 2, 8, 0, 4, 6, 3, 2, 0, 8, 5, 8, 2, 7, 2, 6, 1, 5, 5, 4, 4, 5, 9, 3, 3, 8, 7, 9, 0, 7, 1, 2, 9, 1, 2, 3, 8, 7, 5, 0, 8, 0, 8, 0, 9, 2, 6, 0, 7, 2, 6, 4, 9, 6, 7, 3, 4, 6, 4, 6, 3, 6, 9, 2, 7, 3, 5, 7, 1, 2, 7, 9, 5, 7, 1, 4, 0, 7, 7, 9, 1, 3, 3, 1, 1, 2, 4, 5, 9, 0, 4, 4, 6, 3, 7, 6, 8, 4, 3, 1, 7, 1, 2, 2, 8, 3, 6, 0, 1, 5, 0, 2, 1, 5, 5, 2, 0, 9, 0, 1, 0, 4, 5, 8, 7, 2, 4, 7, 7, 0, 9, 6, 1, 1, 8, 1, 5, 6, 4, 8, 2, 4, 0, 3, 1, 6, 5, 1, 7, 7, 4, 9, 1, 0, 0, 0, 4, 6, 8, 3, 6, 7, 9, 9, 0, 9, 3, 5, 6, 7, 3, 8, 3, 6, 3, 4, 4, 0, 8, 1, 8, 2, 3, 1, 4, 3, 2, 9, 1, 0, 4, 8, 9, 4, 9, 9, 3, 2, 7, 1, 9, 0, 1, 4, 8, 4, 9, 2, 7, 9, 6, 5, 1, 1, 6, 8, 4, 0, 9, 7, 2, 3, 5, 1, 9, 7, 3, 5, 9, 0, 6, 1, 2, 8, 5, 1, 4, 6, 5, 1, 5, 3, 8, 9, 4, 7, 7, 0, 9, 6, 8, 2, 9, 3, 5, 9, 2, 8, 4, 2, 0, 2, 5, 3, 2, 2, 6, 7, 9, 3, 0, 6, 7, 1, 5, 1, 0, 2, 2, 9, 0, 2, 1, 2, 7, 7, 3, 0, 7, 9, 4, 8, 1, 9, 3, 4, 1, 1, 3, 2, 6, 3, 9, 3, 6, 6, 7, 6, 1, 1, 6, 1, 3, 9, 3, 2, 6, 8, 2, 6, 7, 6, 4, 1, 5, 9, 5, 9, 2, 0, 3, 8, 5, 2, 4, 2, 9, 3, 8, 0, 6, 6, 3, 1, 6, 9, 3, 2, 7, 6, 0, 7, 2, 6, 8, 0, 5, 5, 9, 9, 5, 4, 8, 0, 7, 4, 2, 8, 9, 3, 0, 5, 9, 3, 6, 5, 4, 9, 0, 2, 7, 2, 9, 0, 9, 9, 2, 6, 4, 3, 6, 9, 7, 6, 1, 6, 0, 6, 4, 9, 9, 6, 6, 0, 2, 2, 6, 6, 3, 8, 8, 1, 0, 9, 3, 9, 8, 5, 6, 4, 8, 4, 3, 5, 0, 7, 2, 2, 3, 8, 3, 2, 5, 9, 2, 7, 1, 0, 5, 6, 0, 4};

clock_t begin, end;
double time_spent;

begin = clock();
/* here, do your time-consuming job */

    #pragma omp parallel for private(temp)
    for(j=0;j<1000;j++){
        temp = arr[j];
        for(i=0;i<temp;temp--)
        result[j]=result[j]*temp;
    }   


end = clock();
time_spent = (double)(end - begin) / CLOCKS_PER_SEC;
printf("\n\n%f",time_spent);

但是每次运行代码时我都会得到不同的输出。我想看看openmp和串行代码的代码性能有何不同。我应该采用什么方法来实现同样的目标？

1 个答案:

答案 0 :(得分：0)

由于计算机/服务器的使用，代码运行的时间会稍微改变一下;但是，如果同时运行并行和串行版本，则应该看到两者之间的运行时间差异。此外，并行操作的大小非常小。但你应该看到和改进。 

int arr[1000] = {1, 6, 1, 3, 1, 9, 7, 3, 2, 0, 5, 0, 8, 9, 8, 4, 4, 4, 0, 9, 6, 5, 9, 5, 9, 2, 5, 8, 6, 1, 0, 7, 7, 3, 2, 8, 3, 2, 3, 7, 2, 0, 7, 2, 9, 5, 8, 6, 2, 8, 5, 8, 5, 6, 3, 5, 8, 1, 3, 7, 2, 6, 6, 2, 1, 9, 0, 6, 1, 6, 3, 5, 6, 3, 0, 8, 0, 8, 4, 2, 7, 1, 0, 2, 7, 6, 9, 7, 7, 5, 4, 9, 3, 1, 1, 4, 2, 4, 1, 5, 2, 6, 0, 8, 9, 2, 6, 0, 1, 0, 2, 0, 3, 3, 4, 0, 1, 4, 8, 8, 1, 4, 9, 4, 7, 3, 8, 9, 9, 1, 4, 1, 8, 7, 9, 9, 9, 8, 9, 0, 0, 4, 2, 4, 9, 7, 6, 0, 3, 4, 8, 6, 1, 9, 0, 8, 2, 0, 8, 1, 2, 4, 2, 2, 1, 4, 1, 1, 4, 3, 3, 4, 9, 8, 0, 8, 7, 7, 8, 0, 3, 8, 8, 4, 7, 8, 5, 2, 0, 3, 3, 4, 9, 8, 6, 1, 4, 0, 4, 8, 5, 9, 4, 4, 7, 5, 2, 4, 2, 2, 6, 5, 2, 4, 2, 1, 4, 7, 3, 5, 2, 7, 9, 1, 7, 8, 4, 3, 0, 8, 1, 5, 8, 7, 1, 7, 2, 5, 2, 6, 9, 8, 2, 1, 5, 4, 2, 9, 1, 6, 6, 5, 5, 8, 6, 4, 6, 1, 7, 8, 1, 0, 3, 9, 7, 6, 7, 2, 1, 1, 8, 2, 9, 2, 3, 6, 8, 7, 8, 9, 5, 4, 4, 2, 2, 3, 6, 8, 4, 5, 6, 5, 7, 1, 7, 7, 9, 6, 9, 2, 7, 9, 4, 8, 2, 7, 5, 0, 7, 3, 2, 2, 9, 8, 7, 2, 3, 5, 2, 9, 1, 1, 5, 8, 4, 4, 5, 4, 0, 6, 6, 9, 8, 1, 7, 0, 0, 4, 2, 7, 9, 6, 2, 9, 7, 9, 1, 0, 4, 3, 0, 7, 6, 7, 8, 1, 1, 5, 5, 3, 4, 3, 2, 2, 4, 1, 2, 7, 6, 6, 4, 5, 3, 8, 4, 2, 9, 7, 2, 6, 3, 4, 3, 9, 1, 1, 0, 4, 9, 5, 7, 3, 9, 1, 5, 5, 5, 9, 2, 3, 5, 9, 8, 0, 9, 5, 2, 9, 4, 7, 5, 7, 1, 0, 7, 5, 4, 7, 9, 3, 5, 9, 8, 6, 2, 3, 1, 7, 2, 6, 0, 9, 7, 1, 2, 6, 8, 4, 5, 2, 3, 2, 2, 7, 3, 9, 2, 9, 6, 3, 2, 3, 2, 2, 9, 7, 5, 3, 4, 9, 9, 7, 8, 6, 0, 0, 4, 0, 7, 2, 4, 0, 4, 6, 9, 9, 5, 1, 0, 4, 5, 4, 7, 9, 6, 9, 6, 1, 2, 3, 0, 3, 2, 1, 1, 4, 1, 5, 4, 0, 7, 8, 3, 4, 5, 2, 5, 2, 6, 6, 6, 1, 0, 6, 2, 9, 5, 1, 0, 9, 6, 3, 4, 8, 4, 5, 2, 7, 2, 8, 8, 2, 6, 1, 6, 3, 5, 3, 6, 1, 1, 4, 4, 2, 0, 7, 1, 7, 0, 3, 8, 6, 6, 2, 6, 2, 7, 0, 0, 2, 8, 0, 4, 6, 3, 2, 0, 8, 5, 8, 2, 7, 2, 6, 1, 5, 5, 4, 4, 5, 9, 3, 3, 8, 7, 9, 0, 7, 1, 2, 9, 1, 2, 3, 8, 7, 5, 0, 8, 0, 8, 0, 9, 2, 6, 0, 7, 2, 6, 4, 9, 6, 7, 3, 4, 6, 4, 6, 3, 6, 9, 2, 7, 3, 5, 7, 1, 2, 7, 9, 5, 7, 1, 4, 0, 7, 7, 9, 1, 3, 3, 1, 1, 2, 4, 5, 9, 0, 4, 4, 6, 3, 7, 6, 8, 4, 3, 1, 7, 1, 2, 2, 8, 3, 6, 0, 1, 5, 0, 2, 1, 5, 5, 2, 0, 9, 0, 1, 0, 4, 5, 8, 7, 2, 4, 7, 7, 0, 9, 6, 1, 1, 8, 1, 5, 6, 4, 8, 2, 4, 0, 3, 1, 6, 5, 1, 7, 7, 4, 9, 1, 0, 0, 0, 4, 6, 8, 3, 6, 7, 9, 9, 0, 9, 3, 5, 6, 7, 3, 8, 3, 6, 3, 4, 4, 0, 8, 1, 8, 2, 3, 1, 4, 3, 2, 9, 1, 0, 4, 8, 9, 4, 9, 9, 3, 2, 7, 1, 9, 0, 1, 4, 8, 4, 9, 2, 7, 9, 6, 5, 1, 1, 6, 8, 4, 0, 9, 7, 2, 3, 5, 1, 9, 7, 3, 5, 9, 0, 6, 1, 2, 8, 5, 1, 4, 6, 5, 1, 5, 3, 8, 9, 4, 7, 7, 0, 9, 6, 8, 2, 9, 3, 5, 9, 2, 8, 4, 2, 0, 2, 5, 3, 2, 2, 6, 7, 9, 3, 0, 6, 7, 1, 5, 1, 0, 2, 2, 9, 0, 2, 1, 2, 7, 7, 3, 0, 7, 9, 4, 8, 1, 9, 3, 4, 1, 1, 3, 2, 6, 3, 9, 3, 6, 6, 7, 6, 1, 1, 6, 1, 3, 9, 3, 2, 6, 8, 2, 6, 7, 6, 4, 1, 5, 9, 5, 9, 2, 0, 3, 8, 5, 2, 4, 2, 9, 3, 8, 0, 6, 6, 3, 1, 6, 9, 3, 2, 7, 6, 0, 7, 2, 6, 8, 0, 5, 5, 9, 9, 5, 4, 8, 0, 7, 4, 2, 8, 9, 3, 0, 5, 9, 3, 6, 5, 4, 9, 0, 2, 7, 2, 9, 0, 9, 9, 2, 6, 4, 3, 6, 9, 7, 6, 1, 6, 0, 6, 4, 9, 9, 6, 6, 0, 2, 2, 6, 6, 3, 8, 8, 1, 0, 9, 3, 9, 8, 5, 6, 4, 8, 4, 3, 5, 0, 7, 2, 2, 3, 8, 3, 2, 5, 9, 2, 7, 1, 0, 5, 6, 0, 4};

clock_t begin, end;
double time_spent_omp;
double time_spent;

begin = omp_get_wtime();
/* here, do your time-consuming job */

#pragma omp parallel for private(temp)
for(j=0;j<1000;j++){
    temp = arr[j];
    for(i=0;i<temp;temp--)
    result[j]=result[j]*temp;
}   


end = omp_get_wtime();
time_spent_omp = (double)(end - begin) / CLOCKS_PER_SEC;

begin = omp_get_wtime();
/* here, do your time-consuming job */

for(j=0;j<1000;j++){
    temp = arr[j];
    for(i=0;i<temp;temp--)
    result[j]=result[j]*temp;
}   


end = omp_get_wtime();
time_spent = (double)(end - begin) / CLOCKS_PER_SEC;
printf("\n\n Time to process: %f --- Time to process with OPENMP %f",time_spent, time_spent_omp);

这可以让您更好地了解它是如何工作的。

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