7a4f84fbac
- This commit focused on enhancing the performance of dgemm for matrices for very small dimenstions. - blis_dgemm_tiny function re-uses dgemm sup kernels, bypassing the conventional SUP framework code path. As SUP framework code path requires the creation and initilization of blis objects, accessing all the needed meta-information from objects, querying contexts which adds performance penaulty while computing for matrices with very small dimensions. - To avoid such performance penaulty blis_dgemm_tiny function implements a lightweight support code so that it can re-use dgemm SUP kernels such a way that it directly operates on input buffers. It avoids framework overhead of creating and intializing blis objects, context intialization, accessing other large framework data structures. - blis_dgemm_tiny function checks for threshold condition to match before picking the kernel. For zen, zen2, zen3 architecture tiny kernel is invoked for any shape as long as m < 8 and k <= 1500 or m < 1000 and n <= 24 and k <=1500. While for zen4 as long as dimensions are less than 1500 for m,n,k tiny kernel is invoked. -blis_dgemm_tiny function supports single threaded computation as of now. AMD-Internal: [CPUPL-3574] Change-Id: Ife66d35b51add4fccbeebd29911e0c957e59a05f
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.