Algorithm 1039: Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM
In: ACM Transactions on Mathematical Software, Jg. 50 (2024), Heft 1, S. 1-34
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Zugriff:
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, 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.
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Algorithm 1039: 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. ; European High-Performance Computing Joint Undertaking ; European Union’s Horizon 2020 research and innovation programme, and Spain, Germany, France, Italy, Poland, Switzerland, and Norway |
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Zeitschrift: | ACM Transactions on Mathematical Software, Jg. 50 (2024), Heft 1, S. 1-34 |
Veröffentlichung: | Association for Computing Machinery (ACM), 2024 |
Medientyp: | academicJournal |
ISSN: | 0098-3500 |
DOI: | 10.1145/3638532 |
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