通过 openmp 在 C++ 中并行化 three_for_loop

Question

我有密码。这里，A、B、C、A1、B1、C1 是 3 维向量。 A、B、C相互独立，A1、B1、C1也相互独立。我想使用 openmp 并行计算它。但是，我运行它用openmp，我得到"Segmentation fault"error.Could你能帮我解决这个问题吗？先感谢您。

#include <omp.h>
#include<math.h> 
#include<cmath> 
#include<vector>    
#include<iostream>

using namespace std;
int main ()
{

int NX=801;              // NUmber of grid in X direction
int NY=501;              
int NZ=401;   
float PI=3.14159265358979323846;
unsigned int i,j,k;
vector<vector<vector<float> > > A (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
vector<vector<vector<float> > > B (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
vector<vector<vector<float> > > C (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
vector<vector<vector<float> > > A1 (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
vector<vector<vector<float> > > B1 (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
vector<vector<vector<float> > > C1 (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));

cout<<"start"<<endl;
#pragma omp parallel for private (j) shared(A,B,C,i,k,NX,NY,NZ) 
for (i=0;i<NX;i++)
    for (j=0;j<NY;j++)
        for (k=0;k<NZ;k++)
        {
            A[i][j][k]=sin(2.0*PI/float(NX*NY*NZ)*float(i*j*k));
            B[i][j][k]=cos(5.0*PI/float(NX*NY*NZ)*float(i*j*k));
            C[i][j][k]=sin(2.0*PI/float(NX*NY*NZ))*cos(5.0*PI/float(NX*NY*NZ)*float(i*j*k));
        }

#pragma omp parallel for private (j) shared(A1,B1,C1,A,B,C,i,k,NX,NY,NZ) 
for (i=1;i<NX-1;i++)
    for (j=1;j<NY-1;j++)
        for (k=1;k<NZ-1;k++)
        {
            A1[i][j][k]=C[i+1][j][k]*cos(5.0*PI/float(NX*NY*NZ)*float(i*j*k));
            B1[i][j][k]=A[i][j][k]+B[i][j][k]+C[i][j][k]*cos(5.0*PI/float(NX*NY*NZ)*float(i*j*k));
            C1[i][j][k]=16.0*A[i][j][k]*cos(5.0*PI/float(NX*NY*NZ)*float(i*j*k));
        }
cout<<"finish"<<endl;


return 0;
}

Answer 1

此代码很容易与 OpenMP 并行化。但是，您在自己的尝试中犯了一些错误，特别是试图声明 i 和 k shared 而实际上它们应该是 private。更好的是，不要提前声明变量，只需在 for 循环内声明它们。这样，它们将自动具有正确的范围，防止您混淆它。

这是它给出的结果：

#include <omp.h>
#include<math.h> 
#include<cmath> 
#include<vector>    
#include<iostream>

using namespace std;
int main ()
{

    int NX=801;              // NUmber of grid in X direction
    int NY=501;              
    int NZ=401;   
    float PI=3.14159265358979323846;
    vector<vector<vector<float> > > A (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
    vector<vector<vector<float> > > B (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
    vector<vector<vector<float> > > C (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
    vector<vector<vector<float> > > A1 (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
    vector<vector<vector<float> > > B1 (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
    vector<vector<vector<float> > > C1 (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));

    cout<<"start"<<endl;
    #pragma omp parallel for
    for (int i=0;i<NX;i++)
        for (int j=0;j<NY;j++)
            for (int k=0;k<NZ;k++)
            {
                A[i][j][k]=sin(2.0*PI/float(NX*NY*NZ)*float(i*j*k));
                B[i][j][k]=cos(5.0*PI/float(NX*NY*NZ)*float(i*j*k));
                C[i][j][k]=sin(2.0*PI/float(NX*NY*NZ))*cos(5.0*PI/float(NX*NY*NZ)*float(i*j*k));
            }

    #pragma omp parallel for 
    for (int i=1;i<NX-1;i++)
        for (int j=1;j<NY-1;j++)
            for (int k=1;k<NZ-1;k++)
            {
                A1[i][j][k]=C[i+1][j][k]*cos(5.0*PI/float(NX*NY*NZ)*float(i*j*k));
                B1[i][j][k]=A[i][j][k]+B[i][j][k]+C[i][j][k]*cos(5.0*PI/float(NX*NY*NZ)*float(i*j*k));
                C1[i][j][k]=16.0*A[i][j][k]*cos(5.0*PI/float(NX*NY*NZ)*float(i*j*k));
            }
    cout<<"finish"<<endl;

    return 0;
}

现在，由于您要求并行化此代码，我猜您对性能感兴趣。因此，没有什么能阻止您像这样实施一两个非常基本的性能优化：

#include <omp.h>
#include<math.h> 
#include<cmath> 
#include<vector>    
#include<iostream>

using namespace std;
int main ()
{

    int NX=801;              // NUmber of grid in X direction
    int NY=501;              
    int NZ=401;   
    float PI=3.14159265358979323846;
    vector<vector<vector<float> > > A (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
    vector<vector<vector<float> > > B (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
    vector<vector<vector<float> > > C (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
    vector<vector<vector<float> > > A1 (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
    vector<vector<vector<float> > > B1 (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));
    vector<vector<vector<float> > > C1 (NX,vector<vector<float> >(NY,vector <float>(NZ,0.0)));

    const float PIOverSize = PI/(NX*NY*NZ);
    const float sin2PIOverSize = sin(2.0f*PIOverSize);
    cout<<"start"<<endl;
    double tbeg = omp_get_wtime();
    #pragma omp parallel
    {
    #pragma omp for
    for (int i=0;i<NX;i++)
        for (int j=0;j<NY;j++)
        {
            float IJPIOverSize=i*j*PIOverSize;
            for (int k=0;k<NZ;k++)
            {
                A[i][j][k]=sin(2.0f*IJPIOverSize*k);
                B[i][j][k]=cos(5.0f*IJPIOverSize*k);
                C[i][j][k]=sin2PIOverSize*cos(5.0f*IJPIOverSize*k);
            }
         }
    #pragma omp for 
    for (int i=1;i<NX-1;i++)
        for (int j=1;j<NY-1;j++)
        {
            float IJPIOverSize=i*j*PIOverSize;
            for (int k=1;k<NZ-1;k++)
            {
                A1[i][j][k]=C[i+1][j][k]*cos(5.0f*IJPIOverSize*k);
                B1[i][j][k]=A[i][j][k]+B[i][j][k]+C[i][j][k]*cos(5.0f*IJPIOverSize*k);
                C1[i][j][k]=16.0f*A[i][j][k]*cos(5.0f*IJPIOverSize*k);
            }
        }
    }
    double time = omp_get_wtime() - tbeg;
    cout<<"finish in "<<time<<" seconds"<<endl;

    return 0;
}

有了这个，您的代码应该已经快得多了。

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