RT Journal Article
T1 Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM
A1 Alaejos, Guillermo
A1 Castelló, Adrián
A1 Alonso-Jordá, Pedro
A1 Martínez, Héctor
A1 Quintana-Ortí, Enrique S.
A1 Igual Peña, Francisco Daniel
AB 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.
PB Association for Computing Machinery
YR 2024
FD 2024-03-16
LK https://hdl.handle.net/20.500.14352/115351
UL https://hdl.handle.net/20.500.14352/115351
LA eng
NO Guillermo Alaejos, Adrián Castelló, Pedro Alonso-Jordá, Francisco D. Igual, Héctor Martínez, and Enrique S. Quintana-Ortí. 2024. Algorithm 1039: Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM. ACM Trans. Math. Softw. 50, 1, Article 6 (March 2024), 34 pages. https://doi.org/10.1145/3638532
DS Docta Complutense
RD 5 abr 2025