OpenMP：在每个线程中有一个完整的“for”循环 [英] OpenMP: having a complete 'for' loop into each thread

问题描述

我有这个代码：

  #pragma omp parallel 
 {
 #pragma omp single 
 {
 for（int i = 0; i } 
 
 #pragma omp single 
 {
 for（int i = 0; i } 
} 
 
 //等等...最多5或6个myObject_x 
 
 //然后我总结缓冲区和做一些与他们
 float result; 
 for（int i = 0; i  result = myBuffer_1 [i] + myBuffer_2 [i]; 
 
 //与结果做某事
  

如果我运行此代码，得到我所期望的但CPU使用率看起来相当高。相反，如果我正常运行没有OpenMP我得到相同的结果，但CPU使用率是低得多，尽管在单个线程中运行。

我不想指定一个线程数，我希望程序根据CPU能力选择最大线程数，但我想让每个 for 循环运行完全在自己的线程。我该怎么办？

此外，我的期望是，对于myBuffer_1，为循环运行一个线程，另一个 for 循环运行另一个线程，其余的运行在'master'线程中。这是正确的吗？

解决方案

1. #pragma omp single 在结束时有一个隐式屏障，你需要使用 #pragma omp single nowait 如果你想要两个 single

一个更好的主意

  #pragma omp parallel 
 {
 #pragma omp sections 
 {
 #pragma omp section 
 {
 for（int i = 0; i } 
 #pragma omp section 
 {
 for（int i = 0; i } 
} 
 
} 
  




I have this code:

#pragma omp parallel
{
  #pragma omp single
  {
    for (int i=0; i<given_number; ++i) myBuffer_1[i] = myObject_1->myFunction();
  }

  #pragma omp single
  {
    for (int i=0; i<given_number; ++i) myBuffer_2[i] = myObject_2->myFunction();
  }
}

// and so on... up to 5 or 6 of myObject_x

// Then I sum up the buffers and do something with them
float result;
for (int i=0; i<given_number; ++i)
  result = myBuffer_1[i] + myBuffer_2[i];

// do something with result

If I run this code, I get what I expect but the CPU usage looks quite high. Instead, if I run it normally without OpenMP I get the same results but the CPU usage is much lower, despite running in a single thread.

I don't want to specify a number of threads, I wish the program pick the max number of threads according to the CPU capabilities, but I want that each for loop runs entirely in its own thread. How can I do that?

Also, my expectation is that the for loop for myBuffer_1 runs a thread, the other for loop runs another thread, and the rest runs in the 'master' thread. Is this correct?

解决方案

1. #pragma omp single has an implicit barrier at the end, you need to use #pragma omp single nowait if you want the two single block run concurrently.

2. However, for your requirement, using section might be a better idea

   #pragma omp parallel
   {
       #pragma omp sections 
       {
           #pragma omp section 
           {
               for (int i=0; i<given_number; ++i) myBuffer_1[i] = myObject_1->myFunction();  
           }
           #pragma omp section
           {
               for (int i=0; i<given_number; ++i) myBuffer_2[i] = myObject_2->myFunction();  
           }
       }
   
   }
   

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