A Parallel Algebraic Multigrid Solver on Graphics Processing Units

Handle URI:
http://hdl.handle.net/10754/597368
Title:
A Parallel Algebraic Multigrid Solver on Graphics Processing Units
Authors:
Haase, Gundolf; Liebmann, Manfred; Douglas, Craig C.; Plank, Gernot
Abstract:
The paper presents a multi-GPU implementation of the preconditioned conjugate gradient algorithm with an algebraic multigrid preconditioner (PCG-AMG) for an elliptic model problem on a 3D unstructured grid. An efficient parallel sparse matrix-vector multiplication scheme underlying the PCG-AMG algorithm is presented for the many-core GPU architecture. A performance comparison of the parallel solver shows that a singe Nvidia Tesla C1060 GPU board delivers the performance of a sixteen node Infiniband cluster and a multi-GPU configuration with eight GPUs is about 100 times faster than a typical server CPU core. © 2010 Springer-Verlag.
Citation:
Haase G, Liebmann M, Douglas CC, Plank G (2010) A Parallel Algebraic Multigrid Solver on Graphics Processing Units. High Performance Computing and Applications: 38–47. Available: http://dx.doi.org/10.1007/978-3-642-11842-5_5.
Publisher:
Springer Science + Business Media
Journal:
High Performance Computing and Applications
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
2010
DOI:
10.1007/978-3-642-11842-5_5
Type:
Book Chapter
ISSN:
0302-9743; 1611-3349
Sponsors:
This publication is based on work supported in part by NSF grants OISE-0405349, ACI-0305466, CNS-0719626, and ACI-0324876, by DOE project DE-FC26-08NT4, by FWF project SFB032, by BMWF project AustrianGrid 2, and Award No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST).
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorHaase, Gundolfen
dc.contributor.authorLiebmann, Manfreden
dc.contributor.authorDouglas, Craig C.en
dc.contributor.authorPlank, Gernoten
dc.date.accessioned2016-02-25T12:31:45Zen
dc.date.available2016-02-25T12:31:45Zen
dc.date.issued2010en
dc.identifier.citationHaase G, Liebmann M, Douglas CC, Plank G (2010) A Parallel Algebraic Multigrid Solver on Graphics Processing Units. High Performance Computing and Applications: 38–47. Available: http://dx.doi.org/10.1007/978-3-642-11842-5_5.en
dc.identifier.issn0302-9743en
dc.identifier.issn1611-3349en
dc.identifier.doi10.1007/978-3-642-11842-5_5en
dc.identifier.urihttp://hdl.handle.net/10754/597368en
dc.description.abstractThe paper presents a multi-GPU implementation of the preconditioned conjugate gradient algorithm with an algebraic multigrid preconditioner (PCG-AMG) for an elliptic model problem on a 3D unstructured grid. An efficient parallel sparse matrix-vector multiplication scheme underlying the PCG-AMG algorithm is presented for the many-core GPU architecture. A performance comparison of the parallel solver shows that a singe Nvidia Tesla C1060 GPU board delivers the performance of a sixteen node Infiniband cluster and a multi-GPU configuration with eight GPUs is about 100 times faster than a typical server CPU core. © 2010 Springer-Verlag.en
dc.description.sponsorshipThis publication is based on work supported in part by NSF grants OISE-0405349, ACI-0305466, CNS-0719626, and ACI-0324876, by DOE project DE-FC26-08NT4, by FWF project SFB032, by BMWF project AustrianGrid 2, and Award No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST).en
dc.publisherSpringer Science + Business Mediaen
dc.titleA Parallel Algebraic Multigrid Solver on Graphics Processing Unitsen
dc.typeBook Chapteren
dc.identifier.journalHigh Performance Computing and Applicationsen
dc.contributor.institutionKarl-Franzens-Universitat Graz, Graz, Austriaen
dc.contributor.institutionUniversity of Wyoming, Laramie, United Statesen
dc.contributor.institutionUniversity of Oxford, Oxford, United Kingdomen
kaust.grant.numberKUS-C1-016-04en
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