The gputools package enables GPU computing in R.

TitleThe gputools package enables GPU computing in R.
Publication TypeJournal Article
Year of Publication2010
AuthorsBuckner, Joshua, Wilson Justin, Seligman Mark, Athey Brian, Watson Stanley, and Meng Fan
JournalBioinformatics
Volume26
Issue1
Pagination134-5
Date Published2010 Jan 1
ISSN1367-4811
KeywordsAlgorithms, Gene Expression Profiling, Oligonucleotide Array Sequence Analysis, Programming Languages, Software
Abstract

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

DOI10.1093/bioinformatics/btp608
Alternate JournalBioinformatics
PubMed ID19850754
PubMed Central IDPMC2796814
Grant List1U54DA021519-01A1 / DA / NIDA NIH HHS / United States