[R] R Job taking longer in Linux than in Windows

[Patrick Connolly]

On Fri, 02-Aug-2013 at 01:14PM -0700, alina andrei wrote:

|> Hello,
|> ?

|> I am running an R job on a Windows 7 machine, having 4 cores and
|> 16GB RAM?, R 3.0.1,?and it takes 1.5 hours to complete.  I am
|> running the same job in R on a Linux enviroment (Platform:
|> x86_64-redhat-linux-gnu (64-bit)) with huge amounts of memory: 40
|> cores and .5 TB RAM., and the?job takes 3h and 15min to complete
|> (no other concurrent jobs).? The job uses the glmnet package?to
|> perform?model selection on a simulated data set having 1 million
|> records and 150 variables.

|> My questions are:
|> 1. Why R doesn't take advantage of the avaialble RAM?

|> 2. Are there any changes that we can apply to the R configuration
|> file in order to see?superior performance? My expectations are that

I'm guessing you're using mc.lapply from the parallel package, but I
don't have any idea how you're calling it.  That's where I'd be
looking.  40 cores is rather larger than anything I've used.  Even
gkrellm would have a hard time displaying what's going on in that many
'CPU's but I'd suspect you're using only 1 of them.  I've used
mc.lapply with the brt package and occasionally would need to restart
R to make it use all the cores.  Maybe it's something like that, but
it's more likely because of how you call it.


HTH


|> the Linux enviroment would performe a lot better when compared to
|> the Windows enviroment.  ?

|> Any help in sorting out these issues is much appreciated.
|> ?
|> Thank you in advance!
|> Alina?
|> 	[[alternative HTML version deleted]]
|> 

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-- 
~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.   
   ___    Patrick Connolly   
 {~._.~}                   Great minds discuss ideas    
 _( Y )_  	         Average minds discuss events 
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