Lin*_*Lin 9 c++ multithreading asynchronous c++11
#include <future>
#include <iostream>
#include <vector>
#include <cstdint>
#include <algorithm>
#include <random>
#include <chrono>
#include <utility>
#include <type_traits>
template <class Clock = std::chrono::high_resolution_clock, class Task>
double timing(Task&& t, typename std::result_of<Task()>::type* r = nullptr)
{
using namespace std::chrono;
auto begin = Clock::now();
if (r != nullptr) *r = std::forward<Task>(t)();
auto end = Clock::now();
return duration_cast<duration<double>>(end - begin).count();
}
template <typename Num>
double sum(const std::vector<Num>& v, const std::size_t l, const std::size_t h)
{
double s;
for (auto i = l; i <= h; i++) s += v[i];
return s;
}
template <typename Num>
double asum(const std::vector<Num>& v, const std::size_t l, const std::size_t h)
{
auto m = (l + h) / 2;
auto s1 = std::async(std::launch::async, sum<Num>, v, l, m);
auto s2 = std::async(std::launch::async, sum<Num>, v, m+1, h);
return s1.get() + s2.get();
}
int main()
{
std::vector<uint> v(1000);
auto s = std::chrono::system_clock::now().time_since_epoch().count();
std::generate(v.begin(), v.end(), std::minstd_rand0(s));
double r;
std::cout << 1000 * timing([&]() -> double { return asum(v, 0, v.size() - 1); }, &r) << " msec | rst " << r << std::endl;
std::cout << 1000 * timing([&]() -> double { return sum(v, 0, v.size() - 1); }, &r) << " msec | rst " << r << std::endl;
}
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嗨,
所以上面是用于求和随机数矢量的两个函数.
我做了好几次,但似乎我没有受益std::async.以下是我得到的一些结果.
0.130582 msec | rst 1.09015e+12
0.001402 msec | rst 1.09015e+12
0.23185 msec | rst 1.07046e+12
0.002308 msec | rst 1.07046e+12
0.18052 msec | rst 1.07449e+12
0.00244 msec | rst 1.07449e+12
0.190455 msec | rst 1.08319e+12
0.002315 msec | rst 1.08319e+12
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异步版本的所有四种情况都花费了更多时间.但理想情况下我应该快两倍吧?
我在代码中遗漏了什么吗?
顺便说一句,我在OS X 10.10.4Macbook Air上运行1.4 GHz Intel Core i5.
谢谢,
编辑:
g++ -o asum asum.cpp -std=c++11-O3和矢量大小10000000,但结果仍然是必需的.72.1743 msec | rst 1.07349e+16
14.3739 msec | rst 1.07349e+16
58.3542 msec | rst 1.07372e+16
12.1143 msec | rst 1.07372e+16
57.1576 msec | rst 1.07371e+16
11.9332 msec | rst 1.07371e+16
59.9104 msec | rst 1.07395e+16
11.9923 msec | rst 1.07395e+16
64.032 msec | rst 1.07371e+16
12.0929 msec | rst 1.07371e+16
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这里
auto s1 = std::async(std::launch::async, sum<Num>, v, l, m);
auto s2 = std::async(std::launch::async, sum<Num>, v, m+1, h);
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async将存储自己的矢量副本两次.您应该使用std::cref并确保在向量消失之前检索期货(就像在当前代码中一样)并且访问得到正确同步(就像在当前代码中一样).
正如评论中所提到的,线程创建开销可能会进一步降低代码速度.