A Portable and Heterogeneous LU Factorization on IRIS

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

1 Scopus citations

Abstract

Here, the IRIS programming model is evaluated as a method to improve performance portability for heterogeneous systems that use LU matrix factorization. LU (lower-upper) factorization is considered one of the most important numerical linear algebra operations used in multiple high-performance computing and scientific applications. IRIS enables the separation of the algorithm’s definition from the tuning by using tasks + dependencies. This considerably reduces the effort required to achieve performance portability on heterogeneous systems. One IRIS code can use different settings depending on the underlying hardware features. Different configurations are evaluated on two different heterogeneous systems to achieve important speedups for the reference code with minimal changes to the source code.

Original languageEnglish
Title of host publicationEuro-Par 2022
Subtitle of host publicationParallel Processing Workshops - Euro-Par 2022 International Workshops, Revised Selected Papers
EditorsJeremy Singer, Yehia Elkhatib, Dora Blanco Heras, Patrick Diehl, Nick Brown, Aleksandar Ilic
PublisherSpringer Science and Business Media Deutschland GmbH
Pages17-31
Number of pages15
ISBN (Print)9783031312083
DOIs
StatePublished - 2023
Event28th International European Conference on Parallel and Distributed Computing , Euro-Par 2022 - Glasgow, United Kingdom
Duration: Aug 22 2022Aug 26 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13835 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference28th International European Conference on Parallel and Distributed Computing , Euro-Par 2022
Country/TerritoryUnited Kingdom
CityGlasgow
Period08/22/2208/26/22

Funding

J. Kim—Now at NVIDIA. Notice: This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid up, irrevocable, world-wide license to publish or reproduce the published form of the manuscript, or allow others to do so, for U.S. Government purposes. The DOE will provide public access to these results in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

FundersFunder number
U.S. Department of Energy

    Keywords

    • CPU
    • GPU
    • Heterogeneity
    • IRIS
    • LU factorization
    • Performance portability
    • Tasking

    Fingerprint

    Dive into the research topics of 'A Portable and Heterogeneous LU Factorization on IRIS'. Together they form a unique fingerprint.

    Cite this