%0 Journal Article
%A Alaejos, Guillermo
%A Castelló, Adrián
%A Alonso-Jordá, Pedro
%A Martínez, Héctor
%A Quintana-Ortí, Enrique S.
%A Igual Peña, Francisco Daniel
%T Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM
%D 2024
%U https://hdl.handle.net/20.500.14352/115351
%X 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.
%~