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Authors: Markus Schmidberger, Martin Morgan, Dirk Eddelbuettel, Hao Yu, Luke Tierney, Ulrich Mansmann
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State of the Art in Parallel Computing with R
Reference: Vol. 31, Issue 1, Aug 2009
Submitted 2008-12-29, Accepted 2009-06-02
Type: Article
Abstract:

R is a mature open-source programming language for statistical computing and graphics. Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel computing.

This paper presents an overview of techniques for parallel computing with R on computer clusters, on multi-core systems, and in grid computing. It reviews sixteen different packages, comparing them on their state of development, the parallel technology used, as well as on usability, acceptance, and performance.

Two packages (snow, Rmpi) stand out as particularly suited to general use on computer clusters. Packages for grid computing are still in development, with only one package currently available to the end user. For multi-core systems five different packages exist, but a number of issues pose challenges to early adopters. The paper concludes with ideas for further developments in high performance computing with R. Example code is available in the appendix.

Paper: [download]
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State of the Art in Parallel Computing with R
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Supplements: [download]
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v31i01-appendix.pdf: Appendix with code examples
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v31i01-appendixA.R: R code from Appendix A
(application/zip, 2.5 KB)
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v31i01-appendixB1.R: R code from Appendix B.1
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v31i01-appendixB2.R: R code from Appendix B.2
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v31i01-appendixB3.R: R code from Appendix B.3
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Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.
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