Optimization of a parallel permutation testing function for the SPRINT R package

Savvas Petrou, Terence Sloan, Muriel Mewissen, Thorsten Forster, Michal Piotrowski, Bartosz Dobrzelecki, Peter Ghazal, Arthur Trew, Jon Hill

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

The statistical language R and its Bioconductor package are favoured by many biostatisticians for processing microarray data. The amount of data produced by some analyses has reached the limits of many common bioinformatics computing infrastructures. High Performance Computing systems offer a solution to this issue. The Simple Parallel R Interface (SPRINT) is a package that provides biostatisticians with easy access to High Performance Computing systems and allows the addition of parallelized functions to R. Previous work has established that the SPRINT implementation of an R permutation testing function has close to optimal scaling on up to 512 processors on a supercomputer. Access to supercomputers, however, is not always possible, and so the work presented here compares the performance of the SPRINT implementation on a supercomputer with benchmarks on a range of platforms including cloud resources and a common desktop machine with multiprocessing capabilities. Copyright (C) 2011 John Wiley & Sons, Ltd.

Original languageEnglish
Pages (from-to)2258-2268
Number of pages11
JournalConcurrency and Computation: Practice and Experience
Issue number17
Publication statusPublished - 10 Dec 2011

Keywords / Materials (for Non-textual outputs)

  • HPC
  • MPI
  • Permutation
  • Microarray
  • R


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