An efficient multi-algorithms sparse linear solver for GPUs
Identifieur interne : 003507 ( Main/Merge ); précédent : 003506; suivant : 003508An efficient multi-algorithms sparse linear solver for GPUs
Auteurs : Thomas Jost [France] ; Sylvain Contassot-Vivier [France] ; Stéphane Vialle [France]Source :
English descriptors
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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<affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-26305" status="VALID"><orgName>SUPELEC-Campus Metz</orgName>
<desc><address><addrLine>2 rue Edouard Belin 57070 Metz</addrLine>
<country key="FR"></country>
</address>
<ref type="url">http://www.metz.supelec.fr/metz/</ref>
</desc>
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<desc><address><country key="FR"></country>
</address>
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<country>France</country>
</affiliation>
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<profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>GPU Computing</term>
<term>Parallelism</term>
<term>Sparse Linear Solver</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="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.</div>
</front>
</TEI>
</record>
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