A framework for adaptive collective communications for heterogeneous hierarchical computing systems

Collective communication operations are widely used in MPI applications and play an important role in their performance. However, the network heterogeneity inherent to grid environments represent a great challenge to develop efficient high performance computing applications. In this work we propose...

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Bibliographic Details
Published in:Journal of computer and system sciences Vol. 74; no. 6; pp. 1082 - 1093
Main Authors: Steffenel, Luiz Angelo, Mounié, Grégory
Format: Journal Article
Language:English
Published: Elsevier Inc 2008
Elsevier
Subjects:
Adaptive techniques
Collective communication
Computer Science
Distributed, Parallel, and Cluster Computing
Grid computing
MPI
Performance modeling
Polyalgorithms
Performance modeling
Grid computing
Adaptive techniques
Collective communication
Polyalgorithms
MPI
ISSN:0022-0000, 1090-2724
Online Access:Get full text
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Summary:Collective communication operations are widely used in MPI applications and play an important role in their performance. However, the network heterogeneity inherent to grid environments represent a great challenge to develop efficient high performance computing applications. In this work we propose a generic framework based on communication models and adaptive techniques for dealing with collective communication patterns on grid platforms. Toward this goal, we address the hierarchical organization of the grid, selecting the most efficient communication algorithms at each network level. Our framework is also adaptive to grid load dynamics since it considers transient network characteristics for dividing the nodes into clusters. Our experiments with the broadcast operation on a real-grid setup indicate that an adaptive framework allows significant performance improvements on MPI collective communications.
ISSN:0022-0000
1090-2724
DOI:10.1016/j.jcss.2007.07.010