[Numpy-discussion] ENH: Proposal to add KML_BLAS support

[Matthew Brett]

Hi,

The only pages I could find on KML_BLAS were in Chinese.  Like Matti,
I'd be interested to know about the license for this library.  Which
particular ARM chips will it run on?

Cheers,

Matthew

On Mon, Feb 22, 2021 at 12:15 PM ChunLin Fang <qiyu8f at gmail.com> wrote:
>
>   Hi all,
>     Whether you're running apps on your phone or the world's fastest supercomputer, you're most likely running ARM. Many major events have occurred related to ARM archtecture:
>
> Apple may have done the most to make ARM relatively relevant in popular culture with its new ARM-based M1 processor.
> Amazon Web Services launched its Graviton2 processors based on the Arm architecture , which promise up to 40% better performance from comparable x86-based instances for 20% less.
> Microsoft currently uses Arm-based chips from Qualcomm in some of its Surface PCs.
> Huawei unveiled a new chipset called the Kunpeng based on ARM, designed to go into its new TaiShan servers, in a bid to boost its nascent cloud business.
>
>      So It's obvious that ARM will become more and more popular in the future, Since Intel MKL has provide good accelerate support for X86-based chips, Huawei also published KML_BLAS(kunpeng math library blas) that can make full advantage of ARM-based chips,  KML_BLAS is a mathematical library for basic linear algebra operations. it provides three levels of high-performance vector operations: vector-vector operations, vector-matrix operations, and matrix-matrix operations. The performance advantage is shown in the attachment compared with OpenBlas. Can we add KML_BLAS support to numpy?
>
> Cheers,
> Chunlin Fang(github ID:Qiyu8)
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