Parallel Computing with R for Life Sciences

May 18, 2010
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(This article was first published on Revolutions, and kindly contributed to R-bloggers)

I hadn’t heard of the CloudAsia 2010 conference before, but from the programme the workshop Master Class on HPC Application For Life Sciences looked like it was interesting. One workshop session in particular caught my eye: Practical Parallel Computing in R by Xie Chao and Tan Tin Wee (from the National University of Singapore). The workshop notes (PDF) provide a practical and concise overview of the parallel programming options in R, including several examples using our own foreach package under the heading "One Ring to Rule Them All":

The foreach and iterators packages created by REvolution Computing [now Revolution Analytics — ed.] provide us a convenient framework for parallel computing in R. With these two packages, you only need to write one version of your code for all parallel backends.

The document gives examples of using several parallel backends with foreach, including doMC, doSNOW and doMPI

By the way, If you’re planning to try out foreach yourself, don’t forget that a new parallel backend for Windows is now available: doSMP, included with all editions of Revolution R. doSMP is an open-source R package, we’re haven’t yet submitted it to CRAN. But if you want to get in early and try it with R 2.11, Tal Galili has compiled it and made a Windows binary compatible with R 2.11 at his R Statistics blog (thanks, Tal!).

CloudAsia 2010: Master Class on HPC Applications For Life Sciences

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