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BMCBI
2008

SPRINT: A new parallel framework for R

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SPRINT: A new parallel framework for R
Background: Microarray analysis allows the simultaneous measurement of thousands to millions of genes or sequences across tens to thousands of different samples. The analysis of the resulting data tests the limits of existing bioinformatics computing infrastructure. A solution to this issue is to use High Performance Computing (HPC) systems, which contain many processors and more memory than desktop computer systems. Many biostatisticians use R to process the data gleaned from microarray analysis and there is even a dedicated group of packages, Bioconductor, for this purpose. However, to exploit HPC systems, R must be able to utilise the multiple processors available on these systems. There are existing modules that enable R to use multiple processors, but these are either difficult to use for the HPC novice or cannot be used to solve certain classes of problems. A method of exploiting HPC systems, using R, but without recourse to mastering parallel programming paradigms is therefore ...
Jon Hill, Matthew Hambley, Thorsten Forster, Murie
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where BMCBI
Authors Jon Hill, Matthew Hambley, Thorsten Forster, Muriel Mewissen, Terence M. Sloan, Florian Scharinger, Arthur S. Trew, Peter Ghazal
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