Benchmark parallel R backends

Parallel R.r

# Quick and dirty comparison of parallelism in R

#import packages
library(doMC)
library(doMPI)
library(foreach)
library(doParallel)

#number of iterations and procs
iters<-1e4
procs <- 2

###################################################
# Run with stock doParallel
cl<-makeCluster(procs)
registerDoParallel(cl)

strt<-Sys.time()
ls<-foreach(icount(iters)) %dopar% {
  to.ls<-rnorm(1e6)
  to.ls<-summary(to.ls)
  to.ls
}
print("Parallel Procs")
print(Sys.time()-strt)
stopCluster(cl)


###################################################
# Run with doMC (supposingly subsumed into stock R)
registerDoMC(procs)
strt<-Sys.time()
ls<-foreach(icount(iters)) %dopar% {
  to.ls<-rnorm(1e6)
  to.ls<-summary(to.ls)
  to.ls
}
print("Parallel Core")
print(Sys.time()-strt)

###################################################
# Run with doMPI 
cl <- startMPIcluster(procs)
registerDoMPI(cl)
strt<-Sys.time()
ls<-foreach(icount(iters)) %dopar% {
  to.ls<-rnorm(1e6)
  to.ls<-summary(to.ls)
  to.ls
}
print("Parallel MPI")
print(Sys.time()-strt)
closeCluster(cl)