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On 2/22/21 2:13 PM, ChunLin Fang 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)
Thanks, I hadn't heard of this library before. I am a bit
confused as to the link: did you mean this?
https://www.huaweicloud.com/kunpeng/software/KML_BLAS.html
Is there something beyond choosing KML_BLAS in the site.cfg file
that needs to be done to support it? What is the
license/redistribution policy?
Matti
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