In this section we see an examples of parallelization from within the R computing platform (statistical computing similar to Matlab) using the snow package, which can distribute jobs using either MPI or PVM. In this subsection we will only see usage of R+PVM.
Note, that for installation of packages within R the development packages of R are needed. Anyways, I just installed all R packages that were available in the R repository (something like this: http://cran.es.r-project.org/bin/linux/redhat/fedora9/x86_64, needless to say this may differ for your distribution, machine architecture, and country code).
You need to install R libraries snow and rpvm on master and slave(s). If you don't, R lets you create the PVM cluster object but then freezes when you try to execute a job.
> library('snow') > library('rpvm') > cl<-makePVMcluster(count=2,names=c('node0','node1')) > clusterCall(cl, function() Sys.info()[c("nodename","machine")]) [] nodename machine "node1" "x86_64" [] nodename machine "node0" "x86_64"