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A comparison of parallel preconditioners for the sparse generalized eigenvalue problems by Rayleigh-quotient minimization

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dc.contributor.authorMa, Sangback-
dc.contributor.authorJang, Ho-Jong-
dc.date.accessioned2021-06-23T22:39:19Z-
dc.date.available2021-06-23T22:39:19Z-
dc.date.issued2006-06-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/45373-
dc.description.abstractIn this paper we address Ourselves to the problem of finding efficient parallel preconditioner for the interior generalized eigenvalue problem Ax = lambda Bx, where A and B are large sparse symmetric positive definite matrices. We consider incomplete LU(ILU)(0) in two variants, Multi-Color block successive over-relaxation(SOR), and Point-symmetric SOR(SSOR). Our results show that for small number of processors the Multi-Color ILU(0) gives the best performance, while for large number of processors the Multi-Color Block SOR does.-
dc.format.extent9-
dc.language영어-
dc.language.isoENG-
dc.publisherSpringer Verlag-
dc.titleA comparison of parallel preconditioners for the sparse generalized eigenvalue problems by Rayleigh-quotient minimization-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1007/11558958_39-
dc.identifier.scopusid2-s2.0-33745309885-
dc.identifier.wosid000237003200039-
dc.identifier.bibliographicCitationApplied Parallel Computing State of the Art in Scientific Computing, v.3732, pp 333 - 341-
dc.citation.titleApplied Parallel Computing State of the Art in Scientific Computing-
dc.citation.volume3732-
dc.citation.startPage333-
dc.citation.endPage341-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.subject.keywordPlusSYMMETRICAL EIGENPROBLEMS-
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/11558958_39-
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