Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM
2023
Online
report
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.
Comment: 35 pages, 22 figures. Submitted to ACM TOMS
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Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM
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Autor/in / Beteiligte Person: | Alaejos, Guillermo ; Castelló, Adrián ; Alonso-Jordá, Pedro ; Igual, Francisco D. ; Martínez, Héctor ; Quintana-Ortí, Enrique S. |
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Veröffentlichung: | 2023 |
Medientyp: | report |
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