我曾经遇到过一个问题，我拥有的线程越多，task指令似乎会降低代码的执行时间。现在我已经从代码中删除了所有与问题无关的不必要的东西，因为即使这段精简的代码实际上什么也不做，问题仍然会发生。但我对这段代码的总体想法是，让主线程生成任务，以便所有其他工作线程执行。

#ifndef _REENTRANT 
#define _REENTRANT 
#endif 

#include <vector>
#include <iostream>
#include <random>
#include <sched.h>
#include <semaphore.h>
#include <time.h>
#include <bits/stdc++.h>
#include <sys/times.h>
#include <stdio.h>
#include <stdbool.h>
#include <omp.h>
#include <chrono>

#define MAXWORKERS 16

using namespace std;

int nbrThreads = MAXWORKERS;    //Number of threads

void busyWait() {
    for (int i=0; i < 999; i++){}
}

void generatePlacements() {
#pragma omp parallel
{
    #pragma omp master
    {
    int j = 0;
        while (j < 8*7*6*5*4*3*2) {
            #pragma omp task
            {
              busyWait();
            }
            j++;
        }
    }
}
}

int main(int argc, char const *argv[])
{
    for (int i = 1; i <= MAXWORKERS; i++) {
        int nbrThreads = i;
        omp_set_num_threads(nbrThreads);
        auto begin = omp_get_wtime();
        generatePlacements();
        double elapsed;
        auto end = omp_get_wtime();
        auto diff = end - begin;
        cout << "Time taken for " << nbrThreads << " threads to execute was " << diff << endl;
    }
    return 0;
}

我从运行程序中得到了以下输出：

Time taken for 1 threads to execute was 0.0707005
Time taken for 2 threads to execute was 0.0375168
Time taken for 3 threads to execute was 0.0257982
Time taken for 4 threads to execute was 0.0234329
Time taken for 5 threads to execute was 0.0208451
Time taken for 6 threads to execute was 0.0288127
Time taken for 7 threads to execute was 0.0380352
Time taken for 8 threads to execute was 0.0403016
Time taken for 9 threads to execute was 0.0470985
Time taken for 10 threads to execute was 0.0539719
Time taken for 11 threads to execute was 0.0582986
Time taken for 12 threads to execute was 0.051923
Time taken for 13 threads to execute was 0.571846
Time taken for 14 threads to execute was 0.569011
Time taken for 15 threads to execute was 0.562491
Time taken for 16 threads to execute was 0.562118

最值得注意的是，从6个线程的时间似乎变慢了，从12个线程到13个线程似乎有最大的性能打击，变得whooping慢了10倍。现在我知道这个问题围绕着OpenMP任务指令，因为如果我删除busyWait（）函数的性能保持与上面看到的相同，但是如果我同时删除#pragma omp任务头沿着busyWait（）调用我没有得到任何减速，所以减速不依赖于线程创建。我不知道这里的问题是什么。