Mangala V f6046784ce Re-Designed SGEMM SUP kernel to use mask load/store instruction
Added all fringe kernels with mask load store support
Fringe kernels cover m direction from 5 to 1 and
n direction from 15 to 1 for row storage format

- New edge kernels that uses masked load-store
  instructions for handling corner cases.

- Mask load-store instruction macros are added.
  vmaskmovps, VMASKMOVPS for masked load-store.

- It improves performance by reducing branching overhead
  and by being more cache friendly.

- Mask load-store is added only for row storage format

AMD-Internal: [CPUPL-4041]

Change-Id: I563c036c79bf8e476a8ebde37f8f6db751fb3456
2023-11-10 01:23:48 -05:00
2019-05-23 12:51:17 -05:00
2023-11-09 00:16:30 -05:00
2021-07-02 01:20:01 -04:00
2019-10-02 10:16:22 +01:00
2021-07-06 19:35:55 -05:00
2021-03-22 17:42:33 -05:00
2023-10-18 09:09:54 -04:00
2018-08-07 14:21:07 -05:00
2022-05-17 18:10:39 +05:30
2023-05-25 14:46:33 +00:00
2023-08-08 07:27:41 -04:00
2023-08-08 07:27:41 -04:00

AOCL-BLAS library

AOCL-BLAS is AMD's optimized version of BLAS targeted for AMD EPYC and Ryzen CPUs. It is developed as a forked version of BLIS (https://github.com/flame/blis), which is developed by members of the Science of High-Performance Computing (SHPC) group in the Institute for Computational Engineering and Sciences at The University of Texas at Austin and other collaborators (including AMD). All known features and functionalities of BLIS are retained and supported in AOCL-BLAS library. AOCL-BLAS is regularly updated with the improvements from the upstream repository.

AOCL BLAS is optimized with SSE2, AVX2, AVX512 instruction sets which would be enabled based on the target Zen architecture using the dynamic dispatch feature. All prominent Level 3, Level 2 and Level 1 APIs are designed and optimized for specific paths targeting different size spectrums e.g., Small, Medium and Large sizes. These algorithms are designed and customized to exploit the architectural improvements of the target platform.

For detailed instructions on how to configure, build, install, and link against AOCL-BLAS on AMD CPUs, please refer to the AOCL User Guide located on AMD developer portal.

The upstream repository (https://github.com/flame/blis) contains further information on BLIS, including background information on BLIS design, usage examples, and a complete BLIS API reference.

AOCL-BLAS is developed and maintained by AMD. You can contact us on the email-id toolchainsupport@amd.com. You can also raise any issue/suggestion on the git-hub repository at https://github.com/amd/blis/issues.

Description
BLAS-like Library Instantiation Software Framework
Readme BSD-3-Clause 72 MiB
Languages
C 86.3%
C++ 9.5%
Fortran 1.9%
Makefile 0.8%
MATLAB 0.5%
Other 0.9%