Message-ID: <CALh21i+XrJUR7O6zo_MLFf1GjhZqynBFeBcn57tQwtodk8k1OA@mail.gmail.com>
Date: 2012-08-22T15:53:19Z
From: Stephen Weston
Subject: Parallel Linear Model
In-Reply-To: <CAEr64e_0J8ocsX-ZD7vqjRVwVEQ+8E6Joziu4P4jcqJ7JWXVSw@mail.gmail.com>
> On Wed, Aug 22, 2012 at 10:47 AM, Patrik Waldmann <
> patrik.waldmann at boku.ac.at> wrote:
>
>> I did not manage to implement this example in foreach, could anyone point
>> me to a similar example?
>>
Here's a version that also uses the parallel package, but supports
multiple nodes:
library(parallel)
cl <- makePSOCKcluster(4)
pval <- parCapply(cl, x, function(xc, y) summary(lm(y ~
xc))$coefficients[2,4], y)
- Steve
>> Patrik
>>
>> >>> Jay Emerson <jayemerson at gmail.com> 22/08/2012 14:05 >>>
>>
>> Patrik,
>>
>> Your question (at least from you example) is really about general parallel
>> computing. Nothing you want to do with your linear model from your short
>> example requires some special type of parallelism. I recommend package
>> 'foreach' with the parallel backends, or else the package 'parallel' that
>> comes with the newer versions of R. You could also have a look at Dirk's
>> HPC page:
>>
>> http://cran.r-project.org/web/views/HighPerformanceComputing.html
>>
>> Jay
>>
>> --
>> John W. Emerson (Jay)
>> Associate Professor of Statistics, Adjunct, and Acting Director of
>> Graduate Studies
>> Department of Statistics
>> Yale University
>> http://www.stat.yale.edu/~jay ( http://www.stat.yale.edu/%7Ejay )
>>
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>>
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