mclapply not using multiple cores

I'm trying to process a bunch of csv files and return data frames in R, in parallel using `mclapply()`. I have a 64 core machine, and I can't seem to get anymore that 1 core utilized at the moment using `mclapply()`. In fact, it is a bit quicker to run `lapply()` rather than `mclapply()` at the moment. Here is an example that shows that mclapply() is not utilizing more the cores available: ``` library(parallel) test <- lapply(1:100,function(x) rnorm(10000)) system.time(x <- lapply(test,function(x) loess.smooth(x,x))) system.time(x <- mclapply(test,function(x) loess.smooth(x,x), mc.cores=32)) user system elapsed 0.000 0.000 7.234 user system elapsed 0.000 0.000 8.612 ``` Is there some trick to getting this working? I had to compile R from source on this machine (v3.0.1), are there some compile flags that I missed to allow forking? `detectCores()` tells me that I indeed do have 64 cores to play with... Any tips appreciated!