【发布时间】:2019-01-18 11:45:37
【问题描述】:
我是 C++ 多线程编程领域的新手,我尝试使用多线程并行计算数据的均值和标准差,以减少时间成本。我计算平均值和标准差的函数如下。
void cal_mean_std(float* data, float* mean, float* sd, int N, int start_index, int span_cols)
{
int value;
for(int j = start_index; j < start_index + span_cols; j++){
mean[j] = 0;
sd[j] = 0;
for (int i = 0; i < N; i++) {
value = data[j * N + i];
mean[j] += value;
sd[j] += value * value;
}
mean[j] = mean[j] / N;
sd[j] = sqrt(sd[j] / N - mean[j] * mean[j]);
}
}
我指定每个线程的起始索引和计算范围,并按以下方式激活我的线程池。
x.mean = new float[x.M];
x.sd = new float[x.M];
std::vector<std::thread> thread_pool;
int h = 4;
thread_pool.reserve(h);
int SNIPs = static_cast<int>(x.M / h + 1);
int SNIPs_final = x.M - (h - 1) * SNIPs;
for (int i = 0; i < h - 1; i++)
{
thread_pool.push_back(std::thread(std::bind(cal_mean_std, x.data, x.mean, x.sd,
x.N, i*SNIPs, SNIPs)));
}
thread_pool.push_back(std::thread(std::bind(cal_mean_std, x.data, x.mean, x.sd,
x.N, (h-1)*SNIPs, SNIPs_final)));
for (int i = 0; i < h; i++)
thread_pool.at(i).join();
x.M 是我的数据的总列数。但是,我发现以这种方式实现并没有提高程序效率。我不确定问题是什么。
实际上,我们可以模拟数据来进行计算。我的数据大小是 5k x 300k。一个线程对所有数据使用for循环的顺序计算需要15秒。我的多线程版本有时需要 16 秒。
仿真代码如下,我发现当我使用h = 1时,程序需要6s才能完成。但是,当我使用 h = 4 时,程序需要 14 秒才能完成。
#include <thread>
#include <vector>
#include <stdlib.h>
#include <vector>
#include <stdio.h>
#include <iostream>
#include <math.h>
void gen_matrix(int N, int P, float* data){
for (int i = 0; i < N * P; i++)
{
data[i] = rand() % 10;
}
}
void cal_mean_std(float* data, float* mean, float* sd, int N, int start_index, int span_cols)
{
int value;
for(int j = start_index; j < start_index + span_cols; j++){
mean[j] = 0;
sd[j] = 0;
for (int i = 0; i < N; i++) {
value = data[j * N + i];
mean[j] += value;
sd[j] += value * value;
}
mean[j] = mean[j] / N;
sd[j] = sqrt(sd[j] / N - mean[j] * mean[j]);
}
}
int main()
{
int N = 5000;
int P = 300000;
float* data = new float[N*P];
gen_matrix(N, P, data);
float* mean = new float[P];
float* std = new float[P];
std::vector<std::thread> thread_pool;
clock_t t1;
t1 = clock();
int h = 1;
thread_pool.reserve(h);
int SNIPs = static_cast<int>(P / h + 1);
int SNIPs_final = P - (h - 1) * SNIPs;
for (int i = 0; i < h - 1; i++)
{
thread_pool.push_back(std::thread(std::bind(cal_mean_std, data, mean, std,
N, i*SNIPs, SNIPs)));
}
thread_pool.push_back(std::thread(std::bind(cal_mean_std, data, mean, std,
N, (h-1)*SNIPs, SNIPs_final)));
for (int i = 0; i < h; i++)
thread_pool.at(i).join();
std::cout <<"Time for the cal mean and std is " << (clock() - t1) * 1.0/CLOCKS_PER_SEC << std::endl;
return 0;
}
【问题讨论】:
-
评论不用于扩展讨论;这个对话是moved to chat。
标签: c++ multithreading c++11 parallel-processing