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arxiv logo>cs> arXiv:2310.20347
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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

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Abstract: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

Submission history

From: Adrián Castelló [view email]
[v1] Tue, 31 Oct 2023 10:36:26 UTC (2,346 KB)
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