Computer Science > Computation and Language
arXiv:2310.20347 (cs)
[Submitted on 31 Oct 2023]
Title:Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM
Authors:Guillermo Alaejos,Adrián Castelló,Pedro Alonso-Jordá,Francisco D. Igual,Héctor Martínez,Enrique S. Quintana-Ortí
View a PDF of the paper titled Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM, by Guillermo Alaejos and 5 other authors
View PDFAbstract:We explore the utilization of the Apache TVM open source framework to automatically generate a family of algorithms that follow the approach taken by popular linear algebra libraries, such as GotoBLAS2, BLIS and OpenBLAS, in order to obtain high-performance blocked formulations of the general matrix multiplication (GEMM). %In addition, we fully automatize the generation process, by also leveraging the Apache TVM framework to derive a complete variety of the processor-specific micro-kernels for GEMM. This is in contrast with the convention in high performance libraries, which hand-encode a single micro-kernel per architecture using Assembly code. %In global, the combination of our TVM-generated blocked algorithms and micro-kernels for GEMM 1)~improves portability, maintainability and, globally, streamlines the software life cycle; 2)~provides high flexibility to easily tailor and optimize the solution to different data types, processor architectures, and matrix operand shapes, yielding performance on a par (or even superior for specific matrix shapes) with that of hand-tuned libraries; and 3)~features a small memory footprint.
Comments: | 35 pages, 22 figures. Submitted to ACM TOMS |
Subjects: | Computation and Language (cs.CL) |
Cite as: | arXiv:2310.20347 [cs.CL] |
(orarXiv:2310.20347v1 [cs.CL] for this version) | |
https://doi.org/10.48550/arXiv.2310.20347 arXiv-issued DOI via DataCite |
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View a PDF of the paper titled Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM, by Guillermo Alaejos and 5 other authors
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