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Improvement of the Efficiency of Genetic Algorithms for Scalable Parallel Graph Partitioning in a Multi-Level Framework

hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierAlgorithms and high performance computing for grand challenge applications [SCALAPPLIX]
dc.contributor.authorCHEVALIER, Cédric
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierAlgorithms and high performance computing for grand challenge applications [SCALAPPLIX]
dc.contributor.authorPELLEGRINI, François
dc.date.accessioned2024-04-15T09:51:21Z
dc.date.available2024-04-15T09:51:21Z
dc.date.created2006-08
dc.date.issued2006-11-01
dc.date.conference2006-08-30
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/198424
dc.description.abstractEnParallel graph partitioning is a difficult issue, because the best sequential graph partitioning methods known to date are based on iterative local optimization algorithms that do not parallelize nor scale well. On the other hand, evolutionary algorithms are highly parallel and scalable, but converge very slowly as problem size increases. This paper presents methods that can be used to reduce problem space in a dramatic way when using graph partitioning techniques in a multi-level framework, thus enabling the use of evolutionary algorithms as possible candidates, among others, for the realization of efficient scalable parallel graph partitioning tools. Results obtained on the recursive bipartitioning problem with a multi-threaded genetic algorithm are presented, which show that this approach outperforms existing state-of-the-art parallel partitioners.
dc.description.sponsorshipSOLveurs et SimulaTIons en Calculs Extrême - ANR-06-CIS6-0010
dc.language.isoen
dc.publisherSpringer
dc.source.titleEuro-Par 2006 Parallel Processing
dc.title.enImprovement of the Efficiency of Genetic Algorithms for Scalable Parallel Graph Partitioning in a Multi-Level Framework
dc.typeCommunication dans un congrès
dc.identifier.doi10.1007/11823285
dc.subject.halInformatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
bordeaux.page243-252
bordeaux.volume4128
bordeaux.hal.laboratoriesLaboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleEuro-Par
bordeaux.countryDE
bordeaux.title.proceedingEuro-Par 2006 Parallel Processing
bordeaux.conference.cityDresden
bordeaux.peerReviewedoui
hal.identifierhal-00402946
hal.version1
hal.invitednon
hal.proceedingsoui
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00402946v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=Euro-Par%202006%20Parallel%20Processing&rft.date=2006-11-01&rft.volume=4128&rft.spage=243-252&rft.epage=243-252&rft.au=CHEVALIER,%20C%C3%A9dric&PELLEGRINI,%20Fran%C3%A7ois&rft.genre=unknown


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