A simple example of parallel computing on a Windows (and also Mac) machine

May 8, 2012

(This article was first published on RDataMining, and kindly contributed to R-bloggers)

by Yanchang Zhao, RDataMining.com

With a Mac, parallel computing can be achieved with package multicore. Unfortunately, it does not work under Windows.

A simple way for parallel computing under Windows (and also Mac) is using package snowfall, which can work with multi-CPU or multi-core on a single machine, as well as a cluster of multiple machines. For parallel computing on a single machine, it is simple and easy as below.

> library (snowfall)
# initialize cluster
> sfInit (parallel=TRUE , cpus=4)
# parallel computing
> result <- sfLapply(1:10, log)
# stop cluster
> sfStop ()

Simply replace “1:10″ and “log” with your parameter and function to make you own parallel computing. Function sfLapply() is a parallelized version of lapply(). Some other fuctions are sfSapply, sfApply, sfRapply and sfCapply.

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