Looks like this requires use of foreach and lots of extra coding.  
R/parallel only requires that the loop be bracketed with the code 
to start the parallel processing-about 4-5 lines.  Seems a lot 
easier to me.  If I were to go to the trouble of writing a lot of 
new code, it seems that recompiling with BLAS and pnmath would be 
a better option.
 
My main question is how to handle the random number generation
when the child processes are spawned.  That's a problem no matter
what method I choose to create the threads.
 
From: Tal Galili <tal.galili@gmail.com>
To: Scott Raynaud <scott.raynaud@yahoo.com> 
Cc: "r-help@r-project.org" <r-help@r-project.org> 
Sent: Thursday, December 8, 2011 12:38 PM
Subject: Re: [R] R/parallel


Hi Scott, 
Why not use the doSMP package from REvolution?
http://www.r-statistics.com/2010/04/parallel-multicore-processing-with-r-on-windows/


Tal


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te:

I want to take advantage  of my multicore CPU to speed up a loop in a simulation program.  I didn’t write the code,
>but the iterations appear independent to me, at least in the sense that the results of one loop do not depend on
>previous ones.  Right now I’m relegated to a Windows box that runs Windows 7.  These appear to be the options:
> 
>Pnmath-appears to parallelize non-BLAS routine but requires a special build
>Fork-UNIX only
>Romp-looks like this hasn’t advanced past the developmental stage
>Multicore-use on Windows at your own risk
>R/parallel-seems like the best option if I don’t want to recompile.
> 
>Has anyone ever used R/parallel?  What kind of results did you have?  One difficulty with my simulation is that the 
>loop includes code to generate random numbers.  If this loop is split into different threads, then I suspect the 
>randomness of the numbers is not assured.  What can I do about that?
> 
>I can provide the loop code, but it’s fairly long, say 75-100 lines.
> 
>If R/parallel is not feasible then a recompile with BLAS and pnmath appears to be the next best option.
>
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