[R] Use of nnet() with package SNOW ?

[Ron Piccinini]

Hello R masteRs,

I am trying to train a neural network whose training
set is about 910,000 rows by 5 columns. I am running R
on a small cluster of 8 machines (7 slaves) using the
SNOW package. Is there a smart way to use all 8
processors to train the neural net? or am I just
better off putting all the RAM possible on one machine
and run nnet on one processor? I thought about storing
each column of the training set on a seperate node and
have the master node execute something of the sort:
nnet((cbind(clustr[[1]],clustr[[2]],...,clustr[[5]])),targetvector,,5)

(where clstr is the name of the contents of the 
cluster (is diferent from "cl")
However I think that when I do that R loads the
cbind-ed matrix in the master's node environment and
therefore no parallel processing gains are realized.
Thanks in advance for your comments and suggestions,

Ron.