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dc.contributor.authorYılmaz, Buse
dc.date.accessioned2023-10-18T12:06:14Z
dc.date.available2023-10-18T12:06:14Z
dc.date.issued2023en_US
dc.identifier.citationYılmaz, B. A novel graph transformation strategy for optimizing SpTRSV on CPUs. Concurrency and Computation: Practice and Experience, e7761.en_US
dc.identifier.issn1532-0626en_US
dc.identifier.issn1532-0634en_US
dc.identifier.urihttps://doi.org/10.1002/cpe.7761
dc.identifier.urihttps://hdl.handle.net/20.500.11779/1987
dc.description.abstractSparse triangular solve (SpTRSV) is an extensively studied computational kernel. An important obstacle in parallel SpTRSV implementations is that in some parts of a sparse matrix the computation is serial. By transforming the dependency graph, it is possible to increase the parallelism of the parts that lack it. In this work, we present a novel graph transformation strategy to increase the parallelism degree of a sparse matrix and compare it to our previous strategy. It is seen that our transformation strategy can provide a speedup as high as 1.42x$$ 1.42x $$.en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectgraph transformationen_US
dc.subjectparallel computingen_US
dc.subjectsparse matrixen_US
dc.subjectsparse triangle solveen_US
dc.subjectspTRSVen_US
dc.subjectICCGen_US
dc.titleA novel graph transformation strategy for optimizing SpTRSV on CPUsen_US
dc.typearticleen_US
dc.relation.journalConcurrency and Computation-Practice & Experienceen_US
dc.departmentMühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.description.wosidWOS:000982366300001en_US
dc.description.scopusid2-s2.0-85158086996en_US
dc.contributor.institutionauthorYılmaz, Buse
dc.description.woscitationindexScience Citation Index Expandeden_US
dc.identifier.wosqualityQ2-Q3en_US
dc.description.WoSDocumentTypearticleen_US
dc.description.WoSInternationalCollaborationUluslararası işbirliği ile yapılmayan - HAYIRen_US
dc.description.WoSPublishedMonthMayısen_US
dc.description.WoSIndexDate2023en_US
dc.description.WoSYOKperiodYÖK - 2022-23en_US
dc.identifier.doi10.1002/cpe.7761en_US
dc.identifier.scopusqualityQ1 - Q2en_US


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