Work published last week in BMC Bioinformatics unveiled a way to parallelize R statistical analysis by using an add-on package, called R/parallel. The package "extends R by adding user-friendly parallel computing capabilities" and "processing time can be approximately reduced N-fold, N being the number of available processor cores," researchers write in the abstract. Thomas Mailund discusses the difficulties of developing concurrent programs and the fact that the new software leaves it up to the user to determine which loops to speed up. "Knowing what to run in parallel and what not to is a hard problem. It will often depend on the data as well, if nothing else the data size," he says at Mailund on the Internet.
New and Improved R
Oct 01, 2008