8个打包的32位浮点数的水平和 [英] horizontal sum of 8 packed 32bit floats

问题描述

如果我有8个压缩的32位浮点数(__m256)，提取所有8个元素的水平和的最快方法是什么?同样，如何获取水平的最大值和最小值?换句话说，以下C ++函数的最佳实现是什么?

If I have 8 packed 32-bit floating point numbers (__m256), what's the fastest way to extract the horizontal sum of all 8 elements? Similarly, how to obtain the horizontal maximum and minimum? In other words, what's the best implementation for the following C++ functions?

float sum(__m256 x);  ///< returns sum of all 8 elements
float max(__m256 x);  ///< returns the maximum of all 8 elements
float min(__m256 x);  ///< returns the minimum of all 8 elements

推荐答案

在此处快速记入(因此未经测试):

Quickly jotted down here (and hence untested):

float sum(__m256 x) {
    __m128 hi = _mm256_extractf128_ps(x, 1);
    __m128 lo = _mm256_extractf128_ps(x, 0);
    lo = _mm_add_ps(hi, lo);
    hi = _mm_movehl_ps(hi, lo);
    lo = _mm_add_ps(hi, lo);
    hi = _mm_shuffle_ps(lo, lo, 1);
    lo = _mm_add_ss(hi, lo);
    return _mm_cvtss_f32(lo);
}

对于最小/最大，将_mm_add_ps和_mm_add_ss替换为_mm_max_*或_mm_min_*.

For min/max, replace _mm_add_ps and _mm_add_ss with _mm_max_* or _mm_min_*.

请注意，这需要执行一些操作，因此需要进行大量工作； AVX并非真正旨在有效地进行水平操作.如果您可以将这项工作分批处理成多个向量，那么可能会有更有效的解决方案.

Note that this is a lot of work for a few operations; AVX isn't really intended to do horizontal operations efficiently. If you can batch up this work for multiple vectors, then more efficient solutions are possible.

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