fbb72d047f
Description: 1. Added group quantization and zero-point (zp) in aocl_gemm_bf16s4f32o<bf16|f32> API. 2. Group quantization is technique to improve accuracy where scale factors to dequantize weights varies at group level instead of per channel and per tensor level. 3. Added zp and scaling in woq packb kernels so that for large M values zp and scaling are performed at pack-b stage and bf16 kernels are called 4. Adding zp support and scaling to default path in WoQ kernels created some performance overhead when M value is very small. 5. Added string group_size to lpgemm bench to read group size from bench_input.txt and tested for various combinations of matrix dimensions. 6. The scalefactors could be of type float or bf16 and the zeropoint values are expected to be in int8 format. AMD-Internal: [SWLCSG-3168, SWLCSG-3172] Change-Id: Iff07b54d76edc7408eb2ea0b29ce8b4a04a38f57
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.