Video Highlight: SLATE Project Aims to Provide Basic Dense Matrix Operations for Exascale

In this video, Jakub Kurzak, a research assistant professor at the University of Tennessee’s Innovative Computing Laboratory, discusses the Software for Linear Algebra Targeting Exascale (SLATE) project.

The objective of SLATE is to provide basic dense matrix operations such as matrix multiplication, rank-k update, and triangular solve, as well as linear systems solvers, least square solvers, and singular value and eigenvalue solvers, in support of the ECP efforts to build a capable exascale computing ecosystem.

Ultimately, SLATE hopes to replace the venerable Scalable Linear Algebra PACKage (ScaLAPACK) library, which has become the industry standard for dense linear algebra operations in distributed memory environments, but unfortunately is a library at the end of its lifecycle due to the growing need to support hardware accelerators, which are an integral part of today’s high-performance computing hardware infrastructure.

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