Linear Systems Solvers for Distributed-Memory Machines with GPU Accelerators

Jakub Kurzak, Mark Gates, Ali Charara, Asim YarKhan, Ichitaro Yamazaki, Jack Dongarra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

This work presents two implementations of linear solvers for distributed-memory machines with GPU accelerators—one based on the Cholesky factorization and one based on the LU factorization with partial pivoting. The routines are developed as part of the Software for Linear Algebra Targeting Exascale (SLATE) package, which represents a sharp departure from the traditional conventions established by legacy packages, such as LAPACK and ScaLAPACK. The article lays out the principles of the new approach, discusses the implementation details, and presents the performance results.

Original languageEnglish
Title of host publicationEuro-Par 2019
Subtitle of host publicationParallel Processing - 25th International Conference on Parallel and Distributed Computing, Proceedings
EditorsRamin Yahyapour
PublisherSpringer
Pages495-506
Number of pages12
ISBN (Print)9783030293994
DOIs
StatePublished - 2019
Event25th International European Conference on Parallel and Distributed Computing, Euro-Par 2019 - Göttingen, Germany
Duration: Aug 26 2019Aug 30 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11725 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th International European Conference on Parallel and Distributed Computing, Euro-Par 2019
Country/TerritoryGermany
CityGöttingen
Period08/26/1908/30/19

Funding

This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration). Acknowledgments. This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration) responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering and early testbed platforms, in support of the nation’s exascale computing imperative.

FundersFunder number
U.S. Department of Energy organizations
National Nuclear Security Administration
U.S. Department of Energy organizations
National Nuclear Security Administration

    Keywords

    • Cholesky factorization
    • Distributed memory
    • GPU acceleration
    • LU factorization
    • Linear algebra
    • Linear systems of equations

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