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我有一个函数，它需要一个整数，然后运行一段时间（5-500 秒，具体取决于函数输入）。

void foo(int parameter) { /*do some staff*/ }

此计算的结果存储在此函数创建的文本文件中。

resultsFor{参数}.txt

然后我有一个 for 循环，它为给定的整数集评估这个函数。

for (int i = 0; i < 100; i++)
   foo(i);

现在我想用线程优化这个循环的计算时间。最好使用标准库。

#include <thread>

起初我想创建一定数量的线程，这将等于当前机器的核心数。

numberOfThreads = std::thread::hardware_concurrency();

然后我想分配这些线程来计算numberOfThreads循环的第一个整数的函数，如果一个线程完成了它的工作，那么循环的下一步被分配给它。我该如何做到这一点？

问题是无法通过将 for 循环分成numberOfThreads几部分来重新分配工作，因为无法确定给定整数的计算需要多长时间。甚至通过循环的一部分重新分配到线程可能会导致一个线程完成，而另一个线程甚至不会完成其工作的十分之一。

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1 回答 1

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以下是如何使用原子执行此操作的一个示例，如果您有一组需要处理的静态数据，这种可供性很好。对于这个示例，我构建了 100 个向量，每个向量包含 100,000 个元素，所有这些向量都随机打乱，并将它们发送到线程进行排序。

注意：我确实必须在其中引入一个互斥锁以使输出到标准输出正确地不交错。实际上，如果您不进行这样的交互式输出，则不需要它。特别注意输出线程 ID，您会看到每个线程都有多个工作项，所有工作都相当平衡（因为工作负载是）。

我希望它可以帮助你。

#include <iostream>
#include <algorithm>
#include <iterator>
#include <vector>
#include <thread>
#include <atomic>
#include <random>
#include <mutex>

// our work item
typedef std::vector<std::vector<int>> WorkQueue;

// holds the atomic counter for our vector
std::atomic<std::size_t> cnt = ATOMIC_VAR_INIT(0);
std::mutex mtx;

void thread_proc(WorkQueue& wq)
{
    int count = 0;
    std::size_t n = std::atomic_fetch_add(&cnt, std::size_t(1));
    while (n < wq.size())
    {
        //
        // TODO: do something with the n-th item in the vector
        //
        std::unique_lock<std::mutex> lck(mtx);
        std::cout << "Thread " << std::this_thread::get_id() << ": item " << n << std::endl;
        lck.unlock();

        std::sort(wq[n].begin(), wq[n].end());
        ++count;

        // increment by one and move to next item
        n = std::atomic_fetch_add(&cnt, std::size_t(1));
    }

    std::unique_lock<std::mutex> lck(mtx);
    std::cout << "Thread " << std::this_thread::get_id() << " processed " << count << " items." << std::endl;
    lck.unlock();
}

int main(int argc, char *argv[])
{
    std::random_device rd;
    std::default_random_engine rng(rd());

    // build a sizable work queue.
    WorkQueue wq;

    // make a 100000 element sequence of incrementing numbers
    std::vector<int> item;
    item.reserve(100000);
    std::generate_n(std::back_inserter(item), 100000,
                    [](){ static int i=0; return ++i;});

    // add 100 vectors of 1000000 elements each
    wq.reserve(100);
    for (unsigned i=0; i<100; ++i)
    {
        // make a unique shuffle for this insertion
        std::shuffle(item.begin(), item.end(), rng);

        // append a random length of values (1000..size);
        long len = 1000 + (rng() % (item.size() - 1000));
        std::cout << "Appending vector of " << len << " items. " << std::endl;
        wq.emplace_back(item.begin(), std::next(item.begin(), len));
    }

    // ok. get the number of threads we're going to be using.
    unsigned n_threads = std::thread::hardware_concurrency();
    std::vector<std::thread> threads;
    for (unsigned i=0; i<n_threads;++i)
        threads.push_back(std::thread(thread_proc, std::ref(wq)));

    // now join the threads
    for (auto& thrd : threads)
        thrd.join();

    return EXIT_SUCCESS;
}

输出（显然取决于系统）

Appending vector of 67742 items. 
Appending vector of 87839 items. 
Appending vector of 13960 items. 
Appending vector of 64161 items. 
Appending vector of 56993 items. 
Appending vector of 30626 items. 
Appending vector of 24970 items. 
Appending vector of 96336 items. 
Appending vector of 2697 items. 
Appending vector of 70087 items. 
Appending vector of 35234 items. 
Appending vector of 82828 items. 
Appending vector of 15808 items. 
Appending vector of 38646 items. 
Appending vector of 55819 items. 
Appending vector of 99380 items. 
Appending vector of 33486 items. 
Appending vector of 9742 items. 
Appending vector of 50267 items. 
Appending vector of 4421 items. 
Appending vector of 33577 items. 
Appending vector of 55888 items. 
Appending vector of 61601 items. 
Appending vector of 19894 items. 
Appending vector of 90217 items. 
Appending vector of 80498 items. 
Appending vector of 40101 items. 
Appending vector of 50601 items. 
Appending vector of 71679 items. 
Appending vector of 65707 items. 
Appending vector of 8671 items. 
Appending vector of 67409 items. 
Appending vector of 47066 items. 
Appending vector of 53989 items. 
Appending vector of 88724 items. 
Appending vector of 82923 items. 
Appending vector of 38571 items. 
Appending vector of 58705 items. 
Appending vector of 13149 items. 
Appending vector of 97816 items. 
Appending vector of 59586 items. 
Appending vector of 20798 items. 
Appending vector of 45906 items. 
Appending vector of 96078 items. 
Appending vector of 24951 items. 
Appending vector of 19954 items. 
Appending vector of 52154 items. 
Appending vector of 49653 items. 
Appending vector of 14830 items. 
Appending vector of 45169 items. 
Appending vector of 96009 items. 
Appending vector of 15941 items. 
Appending vector of 37832 items. 
Appending vector of 55441 items. 
Appending vector of 65057 items. 
Appending vector of 69484 items. 
Appending vector of 27425 items. 
Appending vector of 11579 items. 
Appending vector of 43795 items. 
Appending vector of 71688 items. 
Appending vector of 17214 items. 
Appending vector of 69687 items. 
Appending vector of 18897 items. 
Appending vector of 96105 items. 
Appending vector of 62040 items. 
Appending vector of 26292 items. 
Appending vector of 34464 items. 
Appending vector of 49473 items. 
Appending vector of 83357 items. 
Appending vector of 50406 items. 
Appending vector of 48313 items. 
Appending vector of 22030 items. 
Appending vector of 2352 items. 
Appending vector of 82989 items. 
Appending vector of 42358 items. 
Appending vector of 59134 items. 
Appending vector of 46823 items. 
Appending vector of 36615 items. 
Appending vector of 40752 items. 
Appending vector of 49963 items. 
Appending vector of 73666 items. 
Appending vector of 29816 items. 
Appending vector of 4112 items. 
Appending vector of 31045 items. 
Appending vector of 8810 items. 
Appending vector of 43021 items. 
Appending vector of 83699 items. 
Appending vector of 5551 items. 
Appending vector of 85914 items. 
Appending vector of 11835 items. 
Appending vector of 82329 items. 
Appending vector of 13567 items. 
Appending vector of 74271 items. 
Appending vector of 49083 items. 
Appending vector of 42803 items. 
Appending vector of 92871 items. 
Appending vector of 17562 items. 
Appending vector of 28686 items. 
Appending vector of 61544 items. 
Appending vector of 13375 items. 
Thread 0x101bc3000: item 0
Thread 0x101c46000: item 1
Thread 0x101cc9000: item 2
Thread 0x101e81000: item 3
Thread 0x101cc9000: item 4
Thread 0x101bc3000: item 5
Thread 0x101e81000: item 6
Thread 0x101e81000: item 7
Thread 0x101bc3000: item 8
Thread 0x101c46000: item 9
Thread 0x101bc3000: item 10
Thread 0x101bc3000: item 11
Thread 0x101e81000: item 12
Thread 0x101e81000: item 13
Thread 0x101bc3000: item 14
Thread 0x101cc9000: item 15
Thread 0x101c46000: item 16
Thread 0x101bc3000: item 17
Thread 0x101bc3000: item 18
Thread 0x101c46000: item 19
Thread 0x101c46000: item 20
Thread 0x101bc3000: item 21
Thread 0x101cc9000: item 22
Thread 0x101bc3000: item 23
Thread 0x101bc3000: item 24
Thread 0x101c46000: item 25
Thread 0x101e81000: item 26
Thread 0x101e81000: item 27
Thread 0x101bc3000: item 28
Thread 0x101c46000: item 29
Thread 0x101e81000: item 30
Thread 0x101e81000: item 31
Thread 0x101cc9000: item 32
Thread 0x101bc3000: item 33
Thread 0x101cc9000: item 34
Thread 0x101e81000: item 35
Thread 0x101c46000: item 36
Thread 0x101bc3000: item 37
Thread 0x101cc9000: item 38
Thread 0x101cc9000: item 39
Thread 0x101c46000: item 40
Thread 0x101bc3000: item 41
Thread 0x101bc3000: item 42
Thread 0x101e81000: item 43
Thread 0x101cc9000: item 44
Thread 0x101bc3000: item 45
Thread 0x101bc3000: item 46
Thread 0x101cc9000: item 47
Thread 0x101e81000: item 48
Thread 0x101c46000: item 49
Thread 0x101e81000: item 50
Thread 0x101cc9000: item 51
Thread 0x101bc3000: item 52
Thread 0x101c46000: item 53
Thread 0x101cc9000: item 54
Thread 0x101bc3000: item 55
Thread 0x101c46000: item 56
Thread 0x101e81000: item 57
Thread 0x101c46000: item 58
Thread 0x101cc9000: item 59
Thread 0x101e81000: item 60
Thread 0x101bc3000: item 61
Thread 0x101c46000: item 62
Thread 0x101e81000: item 63
Thread 0x101c46000: item 64
Thread 0x101cc9000: item 65
Thread 0x101cc9000: item 66
Thread 0x101bc3000: item 67
Thread 0x101c46000: item 68
Thread 0x101cc9000: item 69
Thread 0x101e81000: item 70
Thread 0x101bc3000: item 71
Thread 0x101cc9000: item 72
Thread 0x101cc9000: item 73
Thread 0x101bc3000: item 74
Thread 0x101e81000: item 75
Thread 0x101c46000: item 76
Thread 0x101bc3000: item 77
Thread 0x101cc9000: item 78
Thread 0x101e81000: item 79
Thread 0x101c46000: item 80
Thread 0x101bc3000: item 81
Thread 0x101cc9000: item 82
Thread 0x101cc9000: item 83
Thread 0x101e81000: item 84
Thread 0x101e81000: item 85
Thread 0x101cc9000: item 86
Thread 0x101bc3000: item 87
Thread 0x101bc3000: item 88
Thread 0x101e81000: item 89
Thread 0x101e81000: item 90
Thread 0x101c46000: item 91
Thread 0x101c46000: item 92
Thread 0x101cc9000: item 93
Thread 0x101bc3000: item 94
Thread 0x101e81000: item 95
Thread 0x101c46000: item 96
Thread 0x101cc9000: item 97
Thread 0x101bc3000: item 98
Thread 0x101c46000: item 99
Thread 0x101cc9000 processed 24 items.
Thread 0x101c46000 processed 22 items.
Thread 0x101bc3000 processed 30 items.
Thread 0x101e81000 processed 24 items.
于 2013-10-06T10:37:27.197 回答