parallel_for_each, C++ (gcc)

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#include <algorithm>
#include <iostream>
#include <vector>
#include <thread>
#include <mutex>

template <typename InputIter, typename UnaryFunction>
void parallel_for_each(InputIter first, InputIter last, UnaryFunction f)
{
    auto range = std::distance(first, last);
    size_t approxNumThreads = std::thread::hardware_concurrency();

// number of elements for one thread
    size_t jobsForThread = range / approxNumThreads;
    // number of elements for one thread + remainder
    size_t jobsForMainThread = range % approxNumThreads + jobsForThread;

// minus main thread
    std::vector<std::thread> threads(approxNumThreads - 1);

InputIter block_start = first;
    InputIter block_end = first + jobsForThread;

for(size_t i = 0; i < approxNumThreads - 1; ++i)
    {
        threads[i] = std::thread(std::for_each<InputIter, UnaryFunction>,
                                 block_start, block_end, f);

block_start = block_end;
        block_end += jobsForThread;
    }

std::for_each(block_start, block_start + jobsForMainThread, f);

for(auto& t : threads)
    {
        if(t.joinable())
        {
            t.join();
        }
    }
}

int main(int argc, char* argv[])
{
    std::vector<size_t> vec;

for(size_t i = 0; i < 100; ++i)
    {
        vec.push_back(i);
    }

parallel_for_each(std::begin(vec), std::end(vec), [&vec](size_t& n) { ++n; });
    for(auto e : vec)
    {
        std::cout << e << std::endl;
    }

return 0;
}

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Compilation time: 1.12 sec, absolute running time: 0.14 sec, cpu time: 0 sec, memory peak: 3 Mb, absolute service time: 1,26 sec