Kernel Assisted Collective Intra-node Communication Among Multicore and Manycore CPUs
hal.structure.identifier | Innovative Computing Laboratory [Knoxville] [ICL] | |
dc.contributor.author | MA, Teng | |
hal.structure.identifier | Innovative Computing Laboratory [Knoxville] [ICL] | |
dc.contributor.author | BOSILCA, George | |
hal.structure.identifier | Innovative Computing Laboratory [Knoxville] [ICL] | |
dc.contributor.author | BOUTEILLER, Aurélien | |
hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
hal.structure.identifier | Efficient runtime systems for parallel architectures [RUNTIME] | |
dc.contributor.author | GOGLIN, Brice | |
hal.structure.identifier | Cisco Systems | |
dc.contributor.author | SQUYRES, Jeffrey | |
hal.structure.identifier | Innovative Computing Laboratory [Knoxville] [ICL] | |
dc.contributor.author | DONGARRA, Jack | |
dc.date.accessioned | 2024-04-15T09:48:20Z | |
dc.date.available | 2024-04-15T09:48:20Z | |
dc.date.issued | 2010-12 | |
dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/198171 | |
dc.description.abstractEn | More memory hierarchies, NUMA architectures and network-style interconnection are widely used in modern many-core CPU design to achieve performance scalability. As a leading intra-node programming model, Message Passing Interface (MPI) implementations must exploit these architectures to provide reliable performance portability. These new architectures not only require specialized MPI point-to-point messaging protocols, they also require carefully designed and tuned algorithms for MPI collective operations. Multiple issues must be taken into account: 1) minimizing the number of copies required, 2) minimizing traffic to ''remote'' NUMA memory, and 3) carefully avoiding memory bottlenecks for ''rooted'' collective operations. In this paper, we present a kernel assisted intra-node collective module addressing those three issues on many-core systems. A kernel level inter-process memory copy module, called KNEM, is used by a novel Open MPI collective module to implement several improved strategies based on decreasing the number of intermediate memory copies and improving locality to reduce both the pressure on the memory banks and the cache pollution. The collective topology is mapped onto the NUMA topology to minimize cross traffic on inter-socket links. Experiments illustrate that the KNEM enabled Open MPI collective module can achieve up to a threefold speedup on synthetic benchmarks, resulting in a 12% improvement for a parallel graph shortest path discovery application. | |
dc.language.iso | en | |
dc.subject.en | MPI | |
dc.subject.en | Multicore | |
dc.subject.en | Shared memory | |
dc.subject.en | NUMA | |
dc.subject.en | Kernel | |
dc.subject.en | Collective communication | |
dc.title.en | Kernel Assisted Collective Intra-node Communication Among Multicore and Manycore CPUs | |
dc.type | Rapport | |
dc.subject.hal | Informatique [cs]/Système d'exploitation [cs.OS] | |
bordeaux.page | 11 | |
bordeaux.hal.laboratories | Laboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800 | * |
bordeaux.institution | Université de Bordeaux | |
bordeaux.institution | Bordeaux INP | |
bordeaux.institution | CNRS | |
bordeaux.type.report | rr | |
hal.identifier | inria-00544872 | |
hal.version | 1 | |
hal.audience | Non spécifiée | |
hal.origin.link | https://hal.archives-ouvertes.fr//inria-00544872v1 | |
bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2010-12&rft.spage=11&rft.epage=11&rft.au=MA,%20Teng&BOSILCA,%20George&BOUTEILLER,%20Aur%C3%A9lien&GOGLIN,%20Brice&SQUYRES,%20Jeffrey&rft.genre=unknown |
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