Parallelized optimization in R

Question

I\'m running R on linux box that has 8 multicore processors, and have an optimization problem I\'d like to speed up by parallelizing the optimization routine itself. Importantly

Answer 1

I used the package doSNOW to run a code on 8 cores. I can just copy&paste the part of the code that refers to this package. Hope it helps!

    # use multicore libraries
      # specify number of cores to use
    cores<- 8
      cluster <- makeCluster(cores, type="SOCK")
      registerDoSNOW(cluster)

      # check how many cores will be used
      ncores <- getDoParWorkers()
    print(paste("Computing algorithm for ", cores, " cores", sep=""))
      fph <- rep(-100,12)

      # start multicore cicle on 12  subsets
      fph <- foreach(i=1:12, .combine='c') %dopar% {
        PhenoRiceRun(sub=i, mpath=MODIS_LOCAL_DIR, masklocaldir=MASK_LOCAL_DIR, startYear=startYear, tile=tile, evismoothopt=FALSE)
      }


  stopCluster(cluster) # check if gives error
  gc(verbose=FALSE)