High-performance computing in R at useR! 2008

August 12, 2008

(This article was first published on Mario's Entangled Bank » R, and kindly contributed to R-bloggers)

The useR! 2008 meeting is about to commence. Although I am not able to go this year I will be keeping a close eye on the talks and slides that (I assume) will be posted.  Last years useR! meeting (which I attended) was a great experience and considering the list of participants for this years meeting, it is bound to be a very interesting meeting. Dirk Eddelbuettel has already posted the slides to his talk entitled “Introduction to High-Performance R” on his web site. Clearly, anyone using R on, say, computer clusters would find this highly relevant.

On a side note, it would be interesting to have some idea of how commonly R is used on computer clusters. I have been using R on our in-house cluster for a few years now, and although it may sound a bit counterintuitive to run a high-level interpreted language such as R in a high-performance computing environment such as a cluster (most people would use a low-level compiled language like C for example), using R has the big advantage of allowing very fast prototyping. In other words, although the R code runs slower on the cluster than native C code would do it takes much less time to code it. Of course, for certain classes of models there is no other option that using C (or a similar low-level language), but if you can get away with R, a cluster allows you to run your serial code (or parallelized R code) in parallel with potentially huge time savings.

This is from the “Mario’s Entangled Bank” blog ( http://pineda-krch.com ) of Mario Pineda-Krch, a theoretical biologist at the University of California, Davis.

To leave a comment for the author, please follow the link and comment on their blog: Mario's Entangled Bank » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: , , , ,

Comments are closed.

Search R-bloggers


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)