[游戏开发]c++ openMP 循环处理数组 耗时对比

//在图像处理中，计算很耗时，考虑用openMP并行化,

//本文对比不同办法的循环处理数组的耗费时间,在visual studio 2017调试通过。

//实际测试对比，简单循环并行化、分块技术、编译制导的效果都比较显著。

//但是使用分块技术，两重循环对应行数和列数，比较直观，应用价值大。

#include <iostream>
#include <windows.h>
#include <thread>
#include <omp.h>
#include "time.h"
const int ?width = 10000;
const int height = 10000;
long ? array1[width * height];
long ?array2[width * height];
long ?array3[width * height];
int func1(int w, int h)//不使用并行化
{
?? ?clock_t t1 = clock();
?? ?long t = w * h;
?? ?for (long i = 0; i < t; i++)//遍历每个元素
?? ?{
?? ??? ?array1[i] = 0; array2[i] = 0;
?? ??? ?array3[i] = array1[i] + array2[i];
?? ?}
?? ?clock_t t2 = clock();
?? ?std::cout << t2 - t1 << std::endl;
?? ?std::cout << "---" << std::endl;
?? ?return 0;
}

int func2(int w, int h)//简单循环并行化
{
?? ?clock_t t1 = clock();
?? ?long t = w * h;
#pragma omp parallel for
?? ?for (long i = 0; i < t; i++)
?? ?{
?? ??? ?array1[i] = 0; array2[i] = 0;
?? ??? ?array3[i] = array1[i] + array2[i];
?? ?}
?? ?clock_t t2 = clock();
?? ?std::cout << t2 - t1 << std::endl;
?? ?std::cout << "---" << std::endl;
?? ?return 0;
}
int func3(int w, int h)//使用分块技术将循环转换为等效的多线程
{
?? ?clock_t t1 = clock();
?? ?int i; int j; int m; int n;
#pragma omp parallel for private(i,j)
?? ?for (i = 0; i < h; i++)//遍历行
?? ?{
?? ??? ?for (j = i * w; j < i*w + w; j++)//遍历列
?? ??? ?{
?? ??? ??? ?array1[j] = 0; array2[j] = 0;
?? ??? ??? ?array3[j] = array1[j] + array2[j];
?? ??? ?}

?? ?}
?? ?clock_t t2 = clock();
?? ?std::cout << t2 - t1 << std::endl;
?? ?std::cout << "---" << std::endl;
?? ?return 0;
}

int func3p(long srcArry1[], long srcArry2[], int w, int h, long destsrcArry[])

///数组做参数，使用分块技术将循环转换为等效的多线程
{
? ? clock_t t1 = clock();
? ? int i; int j; int m; int n;
#pragma omp parallel for private(i,j)
? ? for (i = 0; i < h; i++)//遍历行
? ? {
? ? ? ? for (j = i * w; j < i * w + w; j++)//遍历列
? ? ? ? {
? ? ? ? ? ? srcArry1[j] = 0; srcArry2[j] = 0;
? ? ? ? ? ? destsrcArry[j] = srcArry1[j] + srcArry1[j];
? ? ? ? }

? ? }
? ? clock_t t2 = clock();
? ? std::cout << t2 - t1 << std::endl;
? ? std::cout << "---" << std::endl;
? ? return 0;
}

int func4(int w, int h)//使用编译制导将循环转换成等效的多线程度
{
?? ?clock_t t1 = clock();
?? ?long t = w * h;
?? ?long i;
#pragma omp parallel sections private (i)
?? ?{
#pragma omp section
?? ??? ?{
?? ??? ??? ?for (i = 0; i < t / 2; i++)
?? ??? ??? ?{
?? ??? ??? ??? ?array1[i] = 0; array2[i] = 0;
?? ??? ??? ??? ?array3[i] = array1[i] + array2[i];
?? ??? ??? ?}
?? ??? ?}
#pragma omp section
?? ??? ?{ ?for (i = t / 2 + 1; i < t; i++)
?? ??? ?{
?? ??? ??? ?array1[i] = 0; array2[i] = 0;
?? ??? ??? ?array3[i] = array1[i] + array2[i];
?? ??? ?}
?? ??? ?}

?? ?}
?? ?clock_t t2 = clock();
?? ?std::cout << t2 - t1 << std::endl;
?? ?std::cout << "---" << std::endl;
?? ?return 0;
}

int main()
{
?? ?func1(width, height);
?? ?func2(width, height);
?? ?func3(width, height);

? ? func3p(array1, array2, width, height, array3);
?? ?func4(width, height);
?? ?
?? ?system("pause");
?? ?return 0;
}