我可以计算多线程数的平均值吗?

Can i calculate the average of multi-thread numbers?

本文关键字：平均值 计算 多线程 我可以      更新时间：2023-10-16

我在C++中使用多线程函数。使用n多线程，我有n随机输出。我需要计算代码中多线程输出的平均值。假设对于n=4线程，代码是

#include <omp.h>
#include <unistd.h>
#include <stdio.h>
#include <random>
#include <iostream>
#include <cmath>
#include <iomanip>
#include <array>
#include <eigen3/Eigen/Dense>
#define         W               1.0
#define         avg_disorder    10
#define         numThd          4
int main()
{
#pragma omp parallel num_threads(numThd)
{
// define random numbers
std::mt19937 rng;                  
std::uniform_real_distribution <> dist;
std::random_device r;
std::array<int,624> seed_data;
std::generate(seed_data.begin(), seed_data.end(), std::ref(r));
std::seed_seq seq(std::begin(seed_data), std::end(seed_data));
rng.seed(seq);
Eigen::Array<double, -1, 1> rp; // rp= random potential
rp  = Eigen::Array<double, -1, 1>::Zero(avg_disorder, 1);
//List of 10 random numbers
for(int avr = 0; avr < avg_disorder; avr++ )
{
rp(avr,0) = 0.5* W* (-1 + 2* dist(rng) );
}
// output: the mean of the rp
#pragma omp critical
{ 
FILE *output;
char name[50];
sprintf(name, "avgW%06.2f.dat", W);    
output = fopen(name, "a");
fprintf(output, "%e n", rp.mean() );
fclose(output);     
}
}
return 1;
}
// run the file avgThreads
//g++ -std=c++0x -fopenmp -o avgThreads avgThreads.cpp
输出：4 个

线程：4 个结果(rp 的 4 个不同平均值(。

1.015983e-01
4.097469e-02
-1.275186e-01
-1.243190e-01

我的问题是：

我可以计算代码中多线程输出的平均值吗？

你可以试试这样的东西

#include <omp.h>
#include <stdio.h>
#include <random>
#include <iostream>
#include <cmath>
#include <iomanip>
#include <array>
#include <Eigen/Dense>
#define         W          1.0
#define    avg_disorder    10
#define     numThd          4
int main()
{
double average = 0.0;
#pragma omp parallel num_threads(numThd) reduction(+ : average)  
{
// define random numbers
std::mt19937 rng;
std::uniform_real_distribution <> dist;
std::random_device r;
std::array<int, 624> seed_data;
std::generate(seed_data.begin(), seed_data.end(), std::ref(r));
std::seed_seq seq(std::begin(seed_data), std::end(seed_data));
rng.seed(seq);
Eigen::Array<double, -1, 1> rp; // rp= random potential
rp = Eigen::Array<double, -1, 1>::Zero(avg_disorder, 1);
//List of 10 random numbers
for (int avr = 0; avr < avg_disorder; avr++)
{
rp(avr, 0) = 0.5* W* (-1 + 2 * dist(rng));
}
average += rp.mean();
// output: the mean of the rp
#pragma omp critical
{
cout << rp.mean() << endl;
//FILE *output;
//char name[50];
//sprintf(name, "avgW%06.2f.dat", W);
//output = fopen(name, "a");
//fprintf(output, "%e n", rp.mean());
//fclose(output);
}
}
cout << average / (double) numThd << endl;
return 1;
}

它使用 omp 缩减。

对于通用用途(假设您不知道使用的线程数(，您可以执行

double operation();
double averaged_operation()
{
double average = 0.0, count_threads=0.0;
#pragma omp parallel reduction(+ : average, count_threads)  
{
average += operation();
count_threads += 1.0;
}
return  average / count_threads;
}
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