Code-used-on-Daniel-Lemire-s-blog | This is a repository for the code posted on my blog

I will preface this by saying that I am a complete beginner at SIMD intrinsics.

Essentially, I have a CPU which supports the AVX2 instrinsic (Intel(R) Core(TM) i5-7500T CPU @ 2.70GHz). I would like to know the fastest way to compute the dot product of two std::vector of size 512.

I have done some digging online and found this and this, and this stack overflow question suggests using the following function __m256 _mm256_dp_ps(__m256 m1, __m256 m2, const int mask);, However, these all suggest different ways of performing the dot product I am not sure what is the correct (and fastest) way to do it.

In particular, I am looking for the fastest way to perform dot product for a vector of size 512 (because I know the vector size effects the implementation).

Thank you for your help

Edit 1: I am also a little confused about the -mavx2 gcc flag. If I use these AVX2 functions, do I need to add the flag when I compile? Also, is gcc able to do these optimizations for me (say if I use the -OFast gcc flag) if I write a naive dot product implementation?

Edit 2 If anyone has the time and energy, I would very much appreciate if you could write a full implementation. I am sure other beginners would also value this information.