This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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354
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Type:
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Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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Abstract - #307373 |
Title:
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Advanced MPI Support of Distributed Execution of R Programs
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Author(s):
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Chen Ding*+ and Bin Bao and Xiaoming Gu
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Companies:
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University of Rochester and University of Rochester and University of Rochester
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Address:
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P.O.Box 270226, Rochester, NY, 14627, United States
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Keywords:
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distributed computing ;
R ;
MPI
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Abstract:
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A modern computer cluster is capable of performance tens or hundreds of times higher than that of a personal computer. To use a cluster, a program must explicitly communicate share data between machines. MPI is widely used in scientific computing, with portable and optimized support for communication over commodity networks. An R package, Rmpi, has recently been developed as a wrapper to MPI. In this paper, we present several improvements to MPI in support of statistical computing in R. For example, it permits an application to compute on a large vector and communicate it at the same time, forming a pipeline. Such pipelines may be dynamically chained at run time, and a program can gain performance more than what is possible with basic computation-communication overlapping. Our results show that this can improve the parallel performance on 30 cluster nodes by integer factors.
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