How to make R use all processors?

Question

I have a quad-core laptop running Windows XP, but looking at Task Manager R only ever seems to use one processor at a time. How can I make R use all four processors and spee

Answer 1

If you do a lot of matrix operations and you are using Windows you can install revolutionanalytics.com/revolution-r-open for free, and this one comes with the intel MKL libraries which allow you to do multithreaded matrix operations. On Windows if you take the libiomp5md.dll, Rblas.dll and Rlapack.dll files from that install and overwrite the ones in whatever R version you like to use you'll have multithreaded matrix operations (typically you get a 10-20 x speedup for matrix operations). Or you can use the Atlas Rblas.dll from prs.ism.ac.jp/~nakama/SurviveGotoBLAS2/binary/windows/x64 which also work on 64 bit R and are almost as fast as the MKL ones. I found this the single easiest thing to do to drastically increase R's performance on Windows systems. Not sure why they don't come as standard in fact on R Windows installs.

On Windows, multithreading unfortunately is not well supported in R (unless you use OpenMP via Rcpp) and the available SOCKET-based parallelization on Windows systems, e.g. via package parallel, is very inefficient. On POSIX systems things are better as you can use forking there. (package multicore there is I believe the most efficient one). You could also try to use package Rdsm for multithreading within a shared memory model - I've got a version on my github that has unflagged -unix only flag and should work also on Windows (earlier Windows wasn't supported as dependency bigmemory supposedly didn't work on Windows, but now it seems it does) :

library(devtools)
devtools::install_github('tomwenseleers/Rdsm')
library(Rdsm)