What is the easiest way to parallelize a vectorized function in R?

Question

I have a very large list X and a vectorized function f. I want to calculate f(X), but this will take a long time if I do it with a single core. I have (access to) a 48-core server. What is the easiest way to parallelize the calculation of f(X)? The following is not the right answer:

library(foreach)
library(doMC)
registerDoMC()

foreach(x=X, .combine=c) %dopar% f(x)

The above code will indeed parallelize the calculation of f(X), but it will do so by applying f separately to every element of X. This ignores the vectorized nature of f and will probably make things slower as a result, not faster. Rather than applying f elementwise to X, I want to split X into reasonably-sized chunks and apply f to those.

So, should I just manually split X into 48 equal-sized sublists and then apply f to each in parallel, then manually put together the result? Or is there a package designed for this?

In case anyone is wondering, my specific use case is here.

Answer 1

Although this is an older question this might be interesting for everyone who stumbled upon this via google (like me): Have a look at the pvec function in the multicore package. I think it does exactly what you want.