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Kernel Assisted Collective Intra-node MPI Communication Among Multi-core and Many-core CPUs

hal.structure.identifierInnovative Computing Laboratory [Knoxville] [ICL]
dc.contributor.authorMA, Teng
hal.structure.identifierInnovative Computing Laboratory [Knoxville] [ICL]
dc.contributor.authorBOSILCA, George
hal.structure.identifierInnovative Computing Laboratory [Knoxville] [ICL]
dc.contributor.authorBOUTEILLER, Aurélien
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
dc.contributor.authorGOGLIN, Brice
hal.structure.identifierCisco Systems
dc.contributor.authorSQUYRES, Jeffrey
hal.structure.identifierInnovative Computing Laboratory [Knoxville] [ICL]
dc.contributor.authorDONGARRA, Jack
dc.contributor.editorIEEE
dc.date.accessioned2024-04-15T09:47:18Z
dc.date.available2024-04-15T09:47:18Z
dc.date.issued2011-09
dc.date.conference2011-09-13
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/198087
dc.description.abstractEnShared memory is among the most common approaches to implementing message passing within multi-core nodes. However, current shared memory techniques do not scale with increasing numbers of cores and expanding memory hierarchies -- most notably when handling large data transfers and collective communication. Neglecting the underlying hardware topology, using copy-in/copy-out memory transfer operations, and overloading the memory subsystem using one-to-many types of operations are some of the most common mistakes in today's shared memory implementations. Unfortunately, they all negatively impact the performance and scalability of MPI libraries -- and therefore applications. In this paper, we present several kernel-assisted intra-node collective communication techniques that address these three issues on many-core systems. We also present a new Open MPI collective communication component that uses the KNEM Linux module for direct inter-process memory copying. Our Open MPI component implements several novel strategies to decrease the number of intermediate memory copies and improve data locality in order to diminish both cache pollution and memory pressure. Experimental results show that our KNEM-enabled Open\,MPI collective component can outperform state-of-art MPI libraries (Open\,MPI and MPICH2) on synthetic benchmarks, resulting in a significant improvement for a typical graph application.
dc.language.isoen
dc.title.enKernel Assisted Collective Intra-node MPI Communication Among Multi-core and Many-core CPUs
dc.typeCommunication dans un congrès
dc.identifier.doi10.1109/ICPP.2011.29
dc.subject.halInformatique [cs]/Système d'exploitation [cs.OS]
bordeaux.hal.laboratoriesLaboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.title40th International Conference on Parallel Processing (ICPP-2011)
bordeaux.countryTW
bordeaux.conference.cityTaipei
bordeaux.peerReviewedoui
hal.identifierinria-00602877
hal.version1
hal.invitednon
hal.proceedingsoui
hal.conference.end2011-09-16
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//inria-00602877v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2011-09&rft.au=MA,%20Teng&BOSILCA,%20George&BOUTEILLER,%20Aur%C3%A9lien&GOGLIN,%20Brice&SQUYRES,%20Jeffrey&rft.genre=unknown


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