ON two-dimensional sparse matrix partitioning: models, methods, and a recipe

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buir.contributor.authorAykanat, Cevdet
dc.citation.epage683en_US
dc.citation.issueNumber2en_US
dc.citation.spage656en_US
dc.citation.volumeNumber32en_US
dc.contributor.authorÇatalyürek, U. V.en_US
dc.contributor.authorAykanat, Cevdeten_US
dc.contributor.authorUçar, A.en_US
dc.date.accessioned2016-02-08T09:58:59Z
dc.date.available2016-02-08T09:58:59Z
dc.date.issued2010en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractWe consider two-dimensional partitioning of general sparse matrices for parallel sparse matrix-vector multiply operation. We present three hypergraph-partitioning-based methods, each having unique advantages. The first one treats the nonzeros of the matrix individually and hence produces fine-grain partitions. The other two produce coarser partitions, where one of them imposes a limit on the number of messages sent and received by a single processor, and the other trades that limit for a lower communication volume. We also present a thorough experimental evaluation of the proposed two-dimensional partitioning methods together with the hypergraph-based one-dimensional partitioning methods, using an extensive set of public domain matrices. Furthermore, for the users of these partitioning methods, we present a partitioning recipe that chooses one of the partitioning methods according to some matrix characteristics. © 2010 Society for Industrial and Applied Mathematics.en_US
dc.identifier.doi10.1137/080737770en_US
dc.identifier.issn1064-8275
dc.identifier.urihttp://hdl.handle.net/11693/22351
dc.language.isoEnglishen_US
dc.publisherSociety for Industrial and Applied Mathematicsen_US
dc.relation.isversionofhttp://dx.doi.org/10.1137/080737770en_US
dc.source.titleSIAM Journal on Scientific Computingen_US
dc.subjectCombinatorial scientific computingen_US
dc.subjectHypergraph partitioningen_US
dc.subjectParallel matrix-vector multiplicationen_US
dc.subjectSparse matrix partitioningen_US
dc.subjectTwo-dimensional partitioningen_US
dc.subjectExperimental evaluationen_US
dc.subjectHypergraphen_US
dc.subjectMatrix vector multiplicationen_US
dc.subjectOne-dimensional partitioningen_US
dc.subjectPartitioning methodsen_US
dc.subjectPublic domainsen_US
dc.subjectScientific computingen_US
dc.subjectSingle processorsen_US
dc.subjectSparse matricesen_US
dc.subjectMatrix algebraen_US
dc.titleON two-dimensional sparse matrix partitioning: models, methods, and a recipeen_US
dc.typeArticleen_US
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