OpenMP的和C并行for循环：为什么使用OpenMP时，我的code放缓？ [英] OpenMP and C parallel for loop: why does my code slow down when using OpenMP?

问题描述

我是新来的，在C.初学者水平的程序员我在与使用OpenMP用来加快for循环的一些问题。下面是简单的例子：

I'm new here and a beginner level programmer in C. I'm having some problem with using openmp to speedup the for-loop. Below is simple example:

#include <stdlib.h>
#include <stdio.h>
#include <gsl/gsl_rng.h>
#include <omp.h>

gsl_rng *rng;

main()
{
int i, M=100000000;
double tmp;

/* initialize RNG */
gsl_rng_env_setup();
rng = gsl_rng_alloc (gsl_rng_taus);
gsl_rng_set (rng,(unsigned long int)791526599);

// option 1: parallel        
  #pragma omp parallel for default(shared) private( i, tmp ) schedule(dynamic)
  for(i=0;i<=M-1;i++){
     tmp=gsl_ran_gamma_mt(rng, 4, 1./3 );
  }


// option 2: sequential       
  for(i=0;i<=M-1;i++){
     tmp=gsl_ran_gamma_mt(rng, 4, 1./3 );
  }
}

在code从并购迭代的伽玛随机分布绘制。原来使用OpenMP（选项1）并行的方式约需要1分钟，而顺序方法（选项2）只需要20秒。虽然使用OpenMP运行时，我可以看到CPU使用率是800％（我使用的服务器有8个CPU）。而且系统是Linux使用GCC 4.1.3。我使用的编译命令是gcc -fopenmp -lgsl -lgslcblas -lm（我使用GSL）

The code draws from a gamma random distribution for M iterations. It turns out the parallel approach with openmp (option 1) takes about 1 minute while the sequential approach (option 2) takes only 20 seconds. While running with openmp, I can see the cpu usage is 800% ( the server I'm using has 8 CPUs ). And the system is linux with GCC 4.1.3. The compile command I'm using is gcc -fopenmp -lgsl -lgslcblas -lm (I'm using GSL )

我是不是做错了什么？请帮帮我！谢谢！

Am I doing something wrong? Please help me! Thanks!

P.S。如由某些用户所指出的，它可能是由R​​NG引起。但是即使我代替

P.S. As pointed out by some users, it might be caused by rng. But even if I replace

tmp=gsl_ran_gamma_mt(rng, 4, 1./3 );

这是说

tmp=1000*10000;

问题仍然存在...

the problem still there...

推荐答案

gsl_ran_gamma_mt 可能锁住 RNG 至prevent并发问题（如果没有，您的并行code可能包含一个竞争条件，从而产生错误的结果）。那么解决办法是有一个单独的 RNG 实例为每个线程，从而避免锁定。

gsl_ran_gamma_mt probably locks on rng to prevent concurrency issues (if it didn’t, your parallel code probably contains a race condition and thus yields wrong results). The solution then would be to have a separate rng instance for each thread, thus avoiding locking.

这篇关于OpenMP的和C并行for循环：为什么使用OpenMP时，我的code放缓？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！