MAGMA: Enabling exascale performance with accelerated BLAS and LAPACK for diverse GPU architectures

TitleMAGMA: Enabling exascale performance with accelerated BLAS and LAPACK for diverse GPU architectures
Publication TypeJournal Article
Year of Publication2024
AuthorsAbdelfattah, A., N. Beams, R. Carson, P. Ghysels, T. Kolev, T. Stitt, A. Vargas, S. Tomov, and J. Dongarra
JournalThe International Journal of High Performance Computing Applications
Date Published2024-06
Abstract

MAGMA (Matrix Algebra for GPU and Multicore Architectures) is a pivotal open-source library in the landscape of GPU-enabled dense and sparse linear algebra computations. With a repertoire of approximately 750 numerical routines across four precisions, MAGMA is deeply ingrained in the DOE software stack, playing a crucial role in high-performance computing. Notable projects such as ExaConstit, HiOP, MARBL, and STRUMPACK, among others, directly harness the capabilities of MAGMA. In addition, the MAGMA development team has been acknowledged multiple times for contributing to the vendors’ numerical software stacks. Looking back over the time of the Exascale Computing Project (ECP), we highlight how MAGMA has adapted to recent changes in modern HPC systems, especially the growing gap between CPU and GPU compute capabilities, as well as the introduction of low precision arithmetic in modern GPUs. We also describe MAGMA’s direct impact on several ECP projects. Maintaining portable performance across NVIDIA and AMD GPUs, and with current efforts toward supporting Intel GPUs, MAGMA ensures its adaptability and relevance in the ever-evolving landscape of GPU architectures.

URLhttps://journals.sagepub.com/doi/10.1177/10943420241261960
DOI10.1177/10943420241261960
Short TitleThe International Journal of High Performance Computing Applications
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