An efficient multi-algorithms sparse linear solver for GPUs
Identifieur interne : 002A78 ( Hal/Checkpoint ); précédent : 002A77; suivant : 002A79An efficient multi-algorithms sparse linear solver for GPUs
Auteurs : Thomas Jost [France] ; Sylvain Contassot-Vivier [France] ; Stéphane Vialle [France]Source :
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Abstract
We present a new sparse linear solver for GPUs. It is designed to work with structured sparse matrices where all the non-zeros are on a few diagonals. Several iterative algorithms are implemented, both on CPU and GPU. The GPU code is designed to be fast yet simple to read and understand. It aims to be as accurate as possible, even on chips that do not support double-precision floating-point arithmetic. Several benchmarks show that GPU algorithms are much faster than their CPU counterpart while their accuracy is satisfying.
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It is designed to work with structured sparse matrices where all the non-zeros are on a few diagonals. Several iterative algorithms are implemented, both on CPU and GPU. The GPU code is designed to be fast yet simple to read and understand. It aims to be as accurate as possible, even on chips that do not support double-precision floating-point arithmetic. Several benchmarks show that GPU algorithms are much faster than their CPU counterpart while their accuracy is satisfying.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">An efficient multi-algorithms sparse linear solver for GPUs</title><author role="aut"><persName><forename type="first">Thomas</forename><surname>Jost</surname></persName><email></email><idno type="halauthor">445781</idno><orgName ref="#struct-300009"></orgName><affiliation ref="#struct-2346"></affiliation></author><author role="aut"><persName><forename type="first">Sylvain</forename><surname>Contassot-Vivier</surname></persName><email>sylvain.contassotvivier@loria.fr</email><idno type="halauthor">445518</idno><affiliation ref="#struct-2346"></affiliation></author><author role="aut"><persName><forename type="first">Stéphane</forename><surname>Vialle</surname></persName><email>vialle@metz.supelec.fr</email><idno type="idhal">stephane-vialle</idno><idno type="halauthor">135091</idno><affiliation ref="#struct-26305"></affiliation></author><editor role="depositor"><persName><forename>Sylvain</forename><surname>Contassot-Vivier</surname></persName><email>sylvain.contassotvivier@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2009-11-08 16:01:37</date><date type="whenModified">2016-05-18 08:57:56</date><date type="whenReleased">2009-11-08 16:01:37</date><date type="whenProduced">2009-09-01</date></edition><respStmt><resp>contributor</resp><name key="122046"><persName><forename>Sylvain</forename><surname>Contassot-Vivier</surname></persName><email>sylvain.contassotvivier@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">inria-00430520</idno><idno type="halUri">https://hal.inria.fr/inria-00430520</idno><idno type="halBibtex">jost:inria-00430520</idno><idno type="halRefHtml">ParCo2009, Sep 2009, Lyon, France. 2009</idno><idno type="halRef">ParCo2009, Sep 2009, Lyon, France. 2009</idno></publicationStmt><seriesStmt><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno><idno type="stamp" n="SUP_IMS" p="SUPELEC">IMS - Equipe Information, Multimodalité et Signal</idno><idno type="stamp" n="SUPELEC">SUPELEC</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA-NSS" p="LORIA">Réseaux, systèmes et services</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="INRIA2">INRIA 2</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="audience" n="2">International</note><note type="invited" n="0">No</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note><note type="proceedings" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">An efficient multi-algorithms sparse linear solver for GPUs</title><author role="aut"><persName><forename type="first">Thomas</forename><surname>Jost</surname></persName><idno type="halAuthorId">445781</idno><orgName ref="#struct-300009"></orgName><affiliation ref="#struct-2346"></affiliation></author><author role="aut"><persName><forename type="first">Sylvain</forename><surname>Contassot-Vivier</surname></persName><email>sylvain.contassotvivier@loria.fr</email><idno type="halAuthorId">445518</idno><affiliation ref="#struct-2346"></affiliation></author><author role="aut"><persName><forename type="first">Stéphane</forename><surname>Vialle</surname></persName><email>vialle@metz.supelec.fr</email><idno type="idHal">stephane-vialle</idno><idno type="halAuthorId">135091</idno><affiliation ref="#struct-26305"></affiliation></author></analytic><monogr><meeting><title>ParCo2009</title><date type="start">2009-09-01</date><date type="end">2009-09-04</date><settlement>Lyon</settlement><country key="FR">France</country></meeting><respStmt><resp>conferenceOrganizer</resp><name>Frédéric Desprez</name></respStmt><imprint><date type="datePub">2009-09</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">Parallelism</term><term xml:lang="en">GPU Computing</term><term xml:lang="en">Sparse Linear Solver</term></keywords><classCode scheme="acm" n="G.4.4"></classCode><classCode scheme="acm" n="G.4.0"></classCode><classCode scheme="halDomain" n="info.info-dc">Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">We present a new sparse linear solver for GPUs. It is designed to work with structured sparse matrices where all the non-zeros are on a few diagonals. Several iterative algorithms are implemented, both on CPU and GPU. The GPU code is designed to be fast yet simple to read and understand. It aims to be as accurate as possible, even on chips that do not support double-precision floating-point arithmetic. Several benchmarks show that GPU algorithms are much faster than their CPU counterpart while their accuracy is satisfying.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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