SSE intrinsic函数_优化

原文地址http://blog.csdn.net/guoqiangma/article/details/5455661

    编写一个基于SSE多媒体指令集的快速矩阵加法运算函数，输入参数为两个单精度浮点型数组srcA与srcB，长度为N，输出结果保存在一个单精度浮点型数组dest中，假设srcA、srcB以及dest内存空间的首地址均按照16-byte对齐。请利用多媒体指令集获得最大的程序性能（可以使用Visual Studio中的SSE intrinsic函数）

 

推荐函数定义：void SSE_Add(float* srcA, float* srcB, float* dest, int M) {}

 

编程实现：

// SSE.cpp : 定义控制台应用程序的入口点。//#include "stdafx.h"#include <xmmintrin.h>#include <iomanip>#include <stdlib.h>#include <time.h>#include <windows.h>#include<iostream>using namespace std; void SSE_Add(float* srcA, float* srcB, float* dest, int N){      __m128 a, b, c;     int len = N/4;      for(int i=0;i<4*len;i=i+4)     {         a = _mm_set_ps(srcA[i+3], srcA[i+2], srcA[i+1], srcA[i]);         b = _mm_set_ps(srcB[i+3], srcB[i+2], srcB[i+1], srcB[i]);         c = _mm_set_ps(0, 0, 0, 0);         c = _mm_add_ps(a, b);                 dest[i+3] = c.m128_f32[3];         dest[i+2] = c.m128_f32[2];         dest[i+1] = c.m128_f32[1];         dest[i] = c.m128_f32[0];     }     int last = N-4*len;     //cout <<last<<endl;     if(last == 3)     {         int i = 4*len;         a = _mm_set_ps(0, srcA[i+2], srcA[i+1], srcA[i]);         b = _mm_set_ps(0, srcB[i+2], srcB[i+1], srcB[i]);         c = _mm_set_ps(0, 0, 0, 0);         c = _mm_add_ps(a, b);                 dest[i+2] = c.m128_f32[2];         dest[i+1] = c.m128_f32[1];         dest[i] = c.m128_f32[0];     }      if(last == 2)     {         int i = 4*len;         a = _mm_set_ps(0, 0, srcA[i+1], srcA[i]);         b = _mm_set_ps(0, 0, srcB[i+1], srcB[i]);         c = _mm_set_ps(0, 0, 0, 0);         c = _mm_add_ps(a, b);                 dest[i+1] = c.m128_f32[1];         dest[i] = c.m128_f32[0];     }     if(last == 1)     {         int i = 4*len;         a = _mm_set_ps(0, 0, 0, srcA[i]);         b = _mm_set_ps(0, 0, 0, srcB[i]);         c = _mm_set_ps(0, 0, 0, 0);         c = _mm_add_ps(a, b);                 dest[i] = c.m128_f32[0];     }} void normal_Add(float* srcA, float* srcB, float* dest, int N){     for(int i=0;i<N;i++)         dest[i] = srcA[i] + srcB[i];} int main(){     double len=100009;//len=100010;     double run_time;     double  duration,duration1;      float *srcA = new float[len];     float *srcB = new float[len];     float *dest = new float[len];      int i;     for( i=0;i<len;i++)     {         srcA[i] = (float)i;         srcB[i] = (float)i;     }         SYSTEMTIME sys;     SYSTEMTIME sys_end;     double calcRunTime; /*     SSE_Add(srcA,srcB,dest,len);     for(int i=0;i<len;i++)         cout<<setw(7)<<dest[i]<<endl;*/         for(int m =0 ;m<3;m++)     {         cout<<"第"<<m<<"次测试："<<endl;         run_time = 10;         for(;run_time <1000000;run_time = run_time*10)         {              calcRunTime = len * run_time;              cout<<"运行"<<calcRunTime<<"次加法：";              //优化前              GetLocalTime( &sys );              for(i=0;i<run_time;i++)                   normal_Add(srcA,srcB,dest,len);              GetLocalTime( &sys_end );              duration = sys_end.wHour*3600000+sys_end.wMinute*60000 + sys_end.wSecond*1000+sys_end.wMilliseconds                   -(sys.wHour*3600000+sys.wMinute*60000 + sys.wSecond*1000+sys.wMilliseconds);                           cout<<"优化前"<<"用时"<<duration<<"ms    ";                //优化后              GetLocalTime( &sys );              for(i=0;i<run_time;i++)                   SSE_Add(srcA,srcB,dest,10000);               GetLocalTime( &sys_end );              duration1 = sys_end.wHour*3600000+sys_end.wMinute*60000 + sys_end.wSecond*1000+sys_end.wMilliseconds                   -(sys.wHour*3600000+sys.wMinute*60000 + sys.wSecond*1000+sys.wMilliseconds);               float speedup;              if(duration1 == 0)                   speedup = 0;              else                   speedup = duration/duration1;               cout<<"优化后"<<"用时"<<duration1<<"ms"<<"速度提高"<<speedup<<"倍"<<endl;         }     }     return 0;}

 

 

运行环境：

Cpu T7250 ，内存：1G，XP系统

 

优化结果截图