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. More examples on data mining with R can be found in my book "R and Data Mining: Examples and Case Studies", which is downloadable as a .PDF file at the link. |
Examples >