State of the Art in Parallel Computing with R
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 pres...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Foundation for Open Access Statistics
2009-06-01
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| Series: | Journal of Statistical Software |
| Subjects: | |
| Online Access: | http://www.jstatsoft.org/v31/i01/paper |
| _version_ | 1811282967130013696 |
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| author | Markus Schmidberger Luke Tierney Dirk Eddelbuettel Hao Yu Ulrich Mansmann Martin Morgan |
| author_facet | Markus Schmidberger Luke Tierney Dirk Eddelbuettel Hao Yu Ulrich Mansmann Martin Morgan |
| author_sort | Markus Schmidberger |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T02:03:08Z |
| format | Article |
| id | doaj.art-beb05f9c04264466a9df48d2c9e50ac3 |
| institution | Directory Open Access Journal |
| issn | 1548-7660 |
| language | English |
| last_indexed | 2024-04-13T02:03:08Z |
| publishDate | 2009-06-01 |
| publisher | Foundation for Open Access Statistics |
| record_format | Article |
| series | Journal of Statistical Software |
| spelling | doaj.art-beb05f9c04264466a9df48d2c9e50ac32022-12-22T03:07:34ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602009-06-013101State of the Art in Parallel Computing with RMarkus SchmidbergerLuke TierneyDirk EddelbuettelHao YuUlrich MansmannMartin MorganR 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.http://www.jstatsoft.org/v31/i01/paperRhigh performance computingparallel computingcomputer clustermulti-core systemsgrid computingbenchmark |
| spellingShingle | Markus Schmidberger Luke Tierney Dirk Eddelbuettel Hao Yu Ulrich Mansmann Martin Morgan State of the Art in Parallel Computing with R Journal of Statistical Software R high performance computing parallel computing computer cluster multi-core systems grid computing benchmark |
| title | State of the Art in Parallel Computing with R |
| title_full | State of the Art in Parallel Computing with R |
| title_fullStr | State of the Art in Parallel Computing with R |
| title_full_unstemmed | State of the Art in Parallel Computing with R |
| title_short | State of the Art in Parallel Computing with R |
| title_sort | state of the art in parallel computing with r |
| topic | R high performance computing parallel computing computer cluster multi-core systems grid computing benchmark |
| url | http://www.jstatsoft.org/v31/i01/paper |
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