将向量元素和分配给另一个元素的并行算法 [英] Parallel algorithm to sum-assign the elements of a vector to the elements of another one

问题描述

考虑：

std::vector<double> u, v;

#pragma omp parallel for
for (std::size_t i = 0u; i < u.size(); ++i)
  u[i] += v[i];

要使用C ++ 17并行算法表达类似的代码，到目前为止，我发现的解决方案是使用 std :: transform ：

To express similar code with the C++17 parallel algorithms, the solution I found so far is to use the two input ranges version of std::transform:

std::transform(std::execution::par_unseq,
               std::begin(u), std::end(u), std::begin(v), std::begin(u),
               std::plus())

我一点都不喜欢，因为它绕过了我类型的 + = 运算符，在我的实际用例中，导致的代码比原始OpenMP代码冗长得多（长4倍）（我不能只使用 std :: plus ，因为我必须首先对RHS范围元素进行操作）。

which I don't like at all because it bypasses the += operator of my types and in my real use case leads to much more verbose (4 times longer) code than the original OpenMP code (I cannot just use std::plus because I have to first make an operation on the RHS range elements).

还有另一个我监督的算法吗？ ？

Is there another algorithm that I oversight?

还要注意，如果我使用 ranges :: zip ，则代码不会在GCC 9中并行运行因为如果 iterator_category 至少不小于 forward_iterator ，则PSTL后端会回落到t顺序算法： https://godbolt.org/z/XGtPwc 。

Note also that if I use ranges::zip the code won't run in parallel in GCC 9 because if iterator_category is not at least forward_iterator the PSTL back-end falls back to the sequential algorithm: https://godbolt.org/z/XGtPwc.

推荐答案

您是否尝试过tbb :: zip_iterator（ https://www.threadingbuildingblocks.org/docs/help/reference/iterators/zip_iterator.html ）？
其 iterator_category 是 random_access_iterator 。

Have you tried tbb::zip_iterator (https://www.threadingbuildingblocks.org/docs/help/reference/iterators/zip_iterator.html)? Its iterator_category is random_access_iterator.

所以代码看起来像

auto zip_begin = tbb::make_zip_iterator(std::begin(u), std::begin(v));
std::for_each(par_unseq, zip_begin, zip_begin + u.size(),
                  [](auto &&x) { std::get<0u>(x) += std::get<1u>(x); });

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