Kernel Assisted Collective Intra-node Communication Among Multicore and Manycore CPUs
GOGLIN, Brice
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
< Réduire
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
Langue
en
Rapport
Ce document a été publié dans
2010-12p. 11
Résumé en anglais
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 ...Lire la suite >
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.< Réduire
Mots clés en anglais
MPI
Multicore
Shared memory
NUMA
Kernel
Collective communication
Origine
Importé de halUnités de recherche