用户定义减少在不同大小的矢量上 [英] User Defined Reduction on vector of varying size

问题描述

我想为问题此答案之后，为复杂< float>的向量定义自己的缩减在OpenMP中减少阵列。

I'm trying to define my own reduction for vectors of complex<float>, following this answer to the question Reducing on array in OpenMP.

但是我的向量的大小在编译时并不固定，所以我不知道如何在 declare reduction pragma中为向量定义初始化器。也就是说，我不能只有

But the size of my vectors aren't fixed at compile time, so I'm not sure how to define the initializer for the vector in the declare reduction pragma. That is, I can't just have

initializer( omp_priv=TComplexVector(10,0) )

但是向量需要初始化器。

But the initializer is needed for vectors.

如何在运行时我需要的向量传递初始化子句的大小？我到目前为止的是：

How can I pass the initializer clause the size of the vector I need at run time? What I have so far is below:

typedef std::vector<complex<float>> TCmplxVec;

void ComplexAdd(TCmplxVec & x,TCmplxVec & y){
  for (int i=0;i<x.size();i++) 
  {
      x.real()+= y.real();
      //... same for imaginary part and other operations
  }

}

#pragma omp declare reduction(AddCmplx: TCmplxVec: \
ComplexAdd(&omp_out, &omp_in)) initializer( \
omp_priv={TCmplxVec(**here I want a variable length**,0} )

void DoSomeOperation ()
{
    //TCmplxVec vec is empty and anotherVec not

    //so each thread runs the inner loop serially
  #pragma omp parallel for reduction(AddCmplx: vec) 
  for ( n=0 ; n<10 ; ++n )
    {
      for (m=0; m<=someLength; ++m){
        vec[m] += anotherVec[m+someOffset dependend on n and else];
      }
    }
}

推荐答案

现在，你必须挖一点才能找到它，但在 OpenMP Standard ，其中讨论了用户声明的缩减，您会发现特殊标识omp_orig也可以出现在initializer子句中，它将引用要减少的原始变量的存储。

You have to dig a little bit to find it online right now, but in section 2.15 of the OpenMP Standard, where user-declared reductions are discussed, you'll find that "The special identifier omp_orig can also appear in the initializer-clause and it will refer to the storage of the original variable to be reduced."

因此，您可以使用 initializer （omp_priv = TCmplxVec（omp_orig.size（），0））或只是 initalizer（omp_priv（omp_orig））减少。

So you could use initializer (omp_priv=TCmplxVec(omp_orig.size(),0)), or just initalizer ( omp_priv(omp_orig) ) to initialize the vector in the reduction.

所以下面的工作（注意，你不需要编写自己的例程;你可以使用std :: transform和std :: plus来添加你的向量;你也可以使用std :: valarray而不是向量，这取决于你如何使用它们，它有operator +已经定义）：

So the following works (note that you don't need to write your own routine; you can use std::transform and std::plus to add your vectors; you could also use std::valarray rather than vectors, depending on how you use them, which has operator+ already defined):

#include <complex>
#include <vector>
#include <algorithm>
#include <functional>
#include <iostream>
#include <omp.h>

typedef std::vector< std::complex<float> > TCmplxVec;

#pragma omp declare reduction( + : TCmplxVec : \
        std::transform(omp_in.begin( ),  omp_in.end( ), \
                       omp_out.begin( ), omp_out.begin( ), \
                       std::plus< std::complex<float> >( )) ) \
                       initializer (omp_priv(omp_orig))

int main(int argc, char *argv[]) {

    int size;

    if (argc < 2)
        size = 10;
    else
        size = atoi(argv[1]);

    TCmplxVec result(size,0);

    #pragma omp parallel reduction( + : result )
    {
        int tid=omp_get_thread_num();

        for (int i=0; i<std::min(tid+1,size); i++) 
            result[i] += tid;
    }

    for (int i=0; i<size; i++) 
        std::cout << i << "\t" << result[i] << std::endl;

    return 0;
}

运行

$ OMP_NUM_THREADS=1 ./reduction 8
0   (0,0)
1   (0,0)
2   (0,0)
3   (0,0)
4   (0,0)
5   (0,0)
6   (0,0)
7   (0,0)

$ OMP_NUM_THREADS=4 ./reduction 8
0   (6,0)
1   (6,0)
2   (5,0)
3   (3,0)
4   (0,0)
5   (0,0)
6   (0,0)
7   (0,0)

$ OMP_NUM_THREADS=8 ./reduction 8
0   (28,0)
1   (28,0)
2   (27,0)
3   (25,0)
4   (22,0)
5   (18,0)
6   (13,0)
7   (7,0)

这篇关于用户定义减少在不同大小的矢量上的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！