Journal Article

The gputools package enables GPU computing in R

Joshua Buckner, Justin Wilson, Mark Seligman, Brian Athey, Stanley Watson and Fan Meng

in Bioinformatics

Volume 26, issue 1, pages 134-135
Published in print January 2010 | ISSN: 1367-4803
Published online October 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp608
The gputools package enables GPU computing in R

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Motivation: By default, the R statistical environment does not make use of parallelism. Researchers may resort to expensive solutions such as cluster hardware for large analysis tasks. Graphics processing units (GPUs) provide an inexpensive and computationally powerful alternative. Using R and the CUDA toolkit from Nvidia, we have implemented several functions commonly used in microarray gene expression analysis for GPU-equipped computers.

Results: R users can take advantage of the better performance provided by an Nvidia GPU.

Availability: The package is available from CRAN, the R project's repository of packages, at http://cran.r-project.org/web/packages/gputools More information about our gputools R package is available at http://brainarray.mbni.med.umich.edu/brainarray/Rgpgpu

Contact: bucknerj@umich.edu

Journal Article.  1071 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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