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Dynamic Task and Data Placement over NUMA Architectures: an OpenMP Runtime Perspective

hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
dc.contributor.authorBROQUEDIS, François
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
dc.contributor.authorFURMENTO, Nathalie
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
dc.contributor.authorGOGLIN, Brice
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
dc.contributor.authorNAMYST, Raymond
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
dc.contributor.authorWACRENIER, Pierre-André
dc.date.accessioned2024-04-15T09:52:01Z
dc.date.available2024-04-15T09:52:01Z
dc.date.issued2009
dc.date.conference2009-06-03
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/198485
dc.description.abstractEnExploiting the full computational power of current hierarchical multiprocessor machines requires a very careful distribution of threads and data among the underlying non-uniform architecture so as to avoid memory access penalties. Directive-based programming languages such as OpenMP provide programmers with an easy way to structure the parallelism of their application and to transmit this information to the runtime system. Our runtime, which is based on a multi-level thread scheduler combined with a NUMA-aware memory manager, converts this information into ``scheduling hints'' to solve thread/memory affinity issues. It enables dynamic load distribution guided by application structure and hardware topology, thus helping to achieve performance portability. First experiments show that mixed solutions (migrating threads and data) outperform Next-touch-based data distribution policies and open possibilities for new optimizations.
dc.language.isoen
dc.title.enDynamic Task and Data Placement over NUMA Architectures: an OpenMP Runtime Perspective
dc.typeCommunication dans un congrès
dc.identifier.doi10.1007/978-3-642-02303-3_7
dc.subject.halInformatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
bordeaux.hal.laboratoriesLaboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleInternational Workshop on OpenMP (IWOMP)
bordeaux.countryDE
bordeaux.conference.cityDresden
bordeaux.peerReviewedoui
hal.identifierinria-00367570
hal.version1
hal.invitednon
hal.proceedingsoui
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//inria-00367570v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2009&rft.au=BROQUEDIS,%20Fran%C3%A7ois&FURMENTO,%20Nathalie&GOGLIN,%20Brice&NAMYST,%20Raymond&WACRENIER,%20Pierre-Andr%C3%A9&rft.genre=unknown


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