openmp | 易学教程

Is there a simple `parallel for` in golang like OpenMP?

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问题 I'm trying to optimise a puzzle with parallel processing, for better performance. Ideally, in C99 w/ OpenMP, I should be able to do that with the help of a #pragma omp parallel for prior to a for loop in question, and then it should be up to the system to distribute the load between the CPUs. The official documentation for Go at https://golang.org/doc/effective_go.html#parallel, however, seems to suggest that for parallel processing I must, (0), manually get the number of cores from the

OpenMp doesn't utilize all CPUs(dual socket, windows and Microsoft visual studio)

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问题 I have a dual socket system with 22 real cores per CPU or 44 hyperthreads per CPU. I can get openMP to completely utilize the first CPU(22 cores/44 hyper) but I cannot get it to utilize the second CPU. I am using CPUID HWMonitor to check my core usage. The second CPU is always at or near 0 % on all cores. Using: int nProcessors = omp_get_max_threads(); gets me nProcessors = 44, but I think it's just using the 44 hyperthreads of 1 CPU instead of 44 real cores(should be 88 hyperthreads) After

OpenMp doesn't utilize all CPUs(dual socket, windows and Microsoft visual studio)

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Use OpenMP with Windows SDK

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问题 I am aware that VC2010 Express Edition does not include OpenMP support and therefore would report omp.h file missing. Therefore, I have installed Windows SDK v7.1 64-bit version in Windows. However, even I ran: set DISTUTIL_USE_SDK=1 setenv /x64 /release And then try to compile the code, it would still report cannot find omp.h. Could anyone give me a hint on how to solve this? 回答1: Did some checking, and it appears that OpenMP is not part of the Windows SDK, and is only shipped with Visual C+

Timing a Fortran multithreaded program

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问题 I have a Fortran 90 program calling a multi threaded routine. I would like to time this program from the calling routine. If I use cpu_time() , I end up getting the cpu_time for all the threads (8 in my case) added together and not the actual time it takes for the program to run. The etime() routine seems to do the same. Any idea on how I can time this program (without using a stopwatch)? 回答1: Try omp_get_wtime() ; see http://gcc.gnu.org/onlinedocs/libgomp/omp_005fget_005fwtime.html for the

openMP的一点使用经验

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最近在看多核编程。简单来说，由于现在电脑CPU一般都有两个核，4核与8核的CPU也逐渐走入了寻常百姓家，传统的单线程编程方式难以发挥多核CPU的强大功能，于是多核编程应运而生。按照我的理解，多核编程可以认为是对多线程编程做了一定程度的抽象，提供一些简单的API，使得用户不必花费太多精力来了解多线程的底层知识，从而提高编程效率。这两天关注的多核编程的工具包括openMP和TBB。按照目前网上的讨论，TBB风头要盖过openMP，比如openCV过去是使用openMP的，但从2.3版本开始抛弃openMP，转向TBB。但我试下来，TBB还是比较复杂的，相比之下，openMP则非常容易上手。因为精力和时间有限，没办法花费太多时间去学习TBB，就在这里分享下这两天学到的openMP的一点知识，和大家共同讨论。 openMP支持的编程语言包括C语言、C++和Fortran，支持OpenMP的编译器包括Sun Studio，Intel Compiler，Microsoft Visual Studio，GCC。我使用的是Microsoft Visual Studio 2008，CPU为Intel i5 四核，首先讲一下在Microsoft Visual Studio 2008上openMP的配置。非常简单，总共分2步： (1) 新建一个工程。这个不再多讲。 (2) 建立工程后，点击菜单栏-

Intel compiler (C++) issue with OpenMP reduction on std::vector

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问题 Since OpenMP 4.0, user-defined reduction is supported. So I defined the reduction on std::vector in C++ exactly from here. It works fine with GNU/5.4.0 and GNU/6.4.0, but it returns random values for the reduction with intel/2018.1.163. This is the example: #include <iostream> #include <vector> #include <algorithm> #include "omp.h" #pragma omp declare reduction(vec_double_plus : std::vector<double> : \ std::transform(omp_out.begin(), omp_out.end(), omp_in.begin(), omp_out.begin(), std::plus

Is there any difference between variables in a private clause and variables defined within a parallel region in OpenMP?

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问题 I was wondering if there is any reason for preferring the private(var) clause in OpenMP over the local definition of (private) variables, i.e. int var; #pragma omp parallel private(var) { ... } vs. #pragma omp parallel { int var; ... } Also, I'm wondering what's the point of private clauses then. This question was partially explained in OpenMP: are local variables automatically private?, but I don't like the answer since even C89 doesn't bar you from defining variables in the middle of

OpenMP recursive tasks

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问题 Consider following Program calculating Fibonacci Numbers. It uses OpenMP Tasks for parallelisation. #include <iostream> #include <omp.h> using namespace std; int fib(int n) { if(n == 0 || n == 1) return n; int res, a, b; #pragma omp parallel { #pragma omp single { #pragma omp task shared(a) a = fib(n-1); #pragma omp task shared(b) b = fib(n-2); #pragma omp taskwait res = a+b; } } return res; } int main() { cout << fib(40); } I use gcc version 4.8.2 and Fedora 20. When compiling the above

Issue with common block in OpenMP parallel programming

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问题 I have a few questions about using common blocks in parallel programming in Fortran. My subroutines have common blocks. Do I have to declare all the common blocks and threadprivate in the parallel do region? How do they pass information? I want seperate common clock for each thread and want them to pass information through the end of parallel region. Does it happen here? My Ford subroutine changes some variables in common blocks and Condact subroutine overwrites over them again but the