4eabb5cd2e
SCALV is used directly by BLAS, CBLAS and BLIS scal{v} APIs but
also within many other APIs to handle special cases. In general
it is preferred to use SETV when alpha=0, but BLAS and CBLAS
continue to multiple all vector element by alpha. This has
different behaviour for propagating NaNs or Infs.
Changes in this commit:
- Standardize early returns from SCALV reference and optimized
kernels.
- User supplied N<0 is handled at the top level API layer. Use
negative values of N in kernel calls to signify that SETV
should _not_ be used when alpha=0. This should only be
required in SCALV.
- Include serial threshold in zdscal (as in dscal) to reduce
overhead for small problem sizes.
- Code tidying to make different variants more consistent.
- More standardization of tests in SCALV gtestsuite programs.
- Remove scalv_extreme_cases.cpp as it is now redundant.
AMD-Internal: [CPUPL-4415]
Change-Id: I42e98875ceaea224cc98d0cdfe0133c9abc3edae
(cherry picked from commit a07e041b1f)
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.