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dc.contributor.authorAktemur, Tankut Barış
dc.date.accessioned2019-02-11T08:19:36Z
dc.date.available2019-02-11T08:19:36Z
dc.date.issued2018-11-10
dc.identifier.issn1532-0626en_US
dc.identifier.urihttp://hdl.handle.net/10679/6162
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/full/10.1002/cpe.4701
dc.description.abstractSparse matrix-vector multiplication (SpMV) is a crucial operation used for solving many engineering and scientific problems. In general, there is no single SpMV method that gives high performance for all sparse matrices. Even though there exist sparse matrix storage formats and SpMV implementations that yield high efficiency for certain matrix structures, using these methods may entail high preprocessing or format conversion costs. In this work, we present a new SpMV implementation, named CSRLenGoto, that can be utilized by preprocessing the Compressed Sparse Row (CSR) format of a matrix. This preprocessing phase is inexpensive enough for the associated cost to be compensated in just a few repetitions of the SpMV operation. CSRLenGoto is based on complete loop unrolling and gives performance improvements in particular for matrices whose mean row length is low. We parallelized our method by integrating it into a state-of-the-art matrix partitioning approach as the kernel operation. We observed up to 2.46× and on the average 1.29× speedup with respect to Intel MKL's SpMV function for matrices with short- or medium-length rows.en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.relation.ispartofConcurrency Computation
dc.rightsrestrictedAccess
dc.titleA sparse matrix‐vector multiplication method with low preprocessing costen_US
dc.typeConference paperen_US
dc.publicationstatusPublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID(ORCID 0000-0002-1414-9338 & YÖK ID 124803) Aktemur, Barış
dc.contributor.ozuauthorAktemur, Tankut Barış
dc.identifier.volume30en_US
dc.identifier.issue21en_US
dc.identifier.startpage1en_US
dc.identifier.endpage12en_US
dc.identifier.wosWOS:000447267900007
dc.identifier.doi10.1002/cpe.4701en_US
dc.subject.keywordsCompressed sparse rowen_US
dc.subject.keywordsSparse matrix-vector multiplicationen_US
dc.subject.keywordsSpMVen_US
dc.identifier.scopusSCOPUS:2-s2.0-85052438571
dc.contributor.authorMale1
dc.relation.publicationcategoryConference Paper - International - Institutional Academic Staff


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