Partitioning sparse matrices for parallel preconditioned iterative methods

buir.contributor.authorAykanat, Cevdet
dc.citation.epage1709en_US
dc.citation.issueNumber4en_US
dc.citation.spage1683en_US
dc.citation.volumeNumber29en_US
dc.contributor.authorUçar, B.en_US
dc.contributor.authorAykanat, Cevdeten_US
dc.date.accessioned2016-02-08T10:11:06Z
dc.date.available2016-02-08T10:11:06Z
dc.date.issued2007en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractThis paper addresses the parallelization of the preconditioned iterative methods that use explicit preconditioners such as approximate inverses. Parallelizing a full step of these methods requires the coefficient and preconditioner matrices to be well partitioned. We first show that different methods impose different partitioning requirements for the matrices. Then we develop hypergraph models to meet those requirements. In particular, we develop models that enable us to obtain partitionings on the coefficient and preconditioner matrices simultaneously. Experiments on a set of unsymmetric sparse matrices show that the proposed models yield effective partitioning results. A parallel implementation of the right preconditioned BiCGStab method on a PC cluster verifies that the theoretical gains obtained by the models hold in practice. © 2007 Society for Industrial and Applied Mathematics.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:11:06Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2007en
dc.identifier.doi10.1137/040617431en_US
dc.identifier.issn1064-8275en_US
dc.identifier.urihttp://hdl.handle.net/11693/23266en_US
dc.language.isoEnglishen_US
dc.publisherSociety for Industrial and Applied Mathematicsen_US
dc.relation.isversionofhttp://dx.doi.org/10.1137/040617431en_US
dc.source.titleSIAM Journal on Scientific Computingen_US
dc.subjectIterative methoden_US
dc.subjectMatrix partitioningen_US
dc.subjectParallel computingen_US
dc.subjectPreconditioningen_US
dc.subjectApplied mathematicsen_US
dc.subjectApproximate inversesen_US
dc.titlePartitioning sparse matrices for parallel preconditioned iterative methodsen_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Partitioning sparse matrices for parallel preconditioned iterative methods.pdf
Size:
270.98 KB
Format:
Adobe Portable Document Format
Description:
Full printable version