[Beowulf] Here we go again

[Brian Dobbins]

Hi Doug,

  I've seen pretty decent performance on the AMD processors, and was even
told by AMD people to use the Intel compiler -- but when doing that, we
specify the processor type (eg, AVX capabilities), and it works pretty
well.  However, I don't have any experience using the MKL on them.

  That said, looking at the numbers, it's pretty interesting that there's
roughly a factor of 2 from the AVX2 (OpenBLAS) -> AVX512 (MKL) results on
Intel, and with the two systems being relatively comparable with OpenBLAS
(AVX2).  Then it's *roughly* a factor of 8 going from the MKL on Intel to
the MKL on AMD, and since AVX512 is 8 x 64 floats, it seems it could just
be it's not using any vectorization whatsoever on AMD... presumably because
Intel claims they can't recognize the chip?  That said, I'd love to see the
author try after setting:

MKL_ENABLE_INSTRUCTIONS=AVX2

  That might be an easy fix, if it works[1].

  Anyone got a Zen2 system with NumPy & the MKL to try it with?

  - Brian

[1]
https://software.intel.com/en-us/mkl-linux-developer-guide-instruction-set-specific-dispatching-on-intel-architectures


On Thu, Dec 12, 2019 at 7:35 AM Douglas Eadline <deadline at eadline.org>
wrote:

>
> Anyone see anything like this with Epyc, i.e. poor AMD performance
> when using Intel compilers or MKL?
>
>
> https://www.pugetsystems.com/labs/hpc/AMD-Ryzen-3900X-vs-Intel-Xeon-2175W-Python-numpy---MKL-vs-OpenBLAS-1560/
>
>
>
> --
> Doug
>
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