I was able to reproduce your problem on my Linux machine using only the "parallel" package in R 3.2.3:
library(parallel)
cl <- makeCluster(2)
clusterEvalQ(cl, library(parallel))
fun <- function(i) {
mclapply(1:10, function(x) rnorm(1e5), mc.cores=2)
0
}
clusterApplyLB(cl, 1:5, fun)
, , , , , "" .
, , "multicore" "parallel". multicore 0.1-8 RForge.net, :
> install.packages('multicore',,'http://www.rforge.net/')
"multicore" "parallel" :
clusterEvalQ(cl, library(multicore))
. foreach, .packages='multicore'.
. , , "mclapply" "parallel", - , , , , .
, :
- "mclapply" foreach "doParallel"
- "mclapply" "multicore 0.1-8" "parallel"
- R-Core
, R-Core, , , .