[R] torque/psb & snow library

[jgarcia at ija.csic.es]

Thanks you! I'll look at this new list!
Well, I'm not the system administrator, and my installation of Rmpi and/or
pvm libraries for R crashes. As this is the first time I parallelize some
jobs, snow appealed as a first approach because 1) it compiled correctly
and 2) the use of the library is very easy.

As you tell me MPI is faster, I'll retry Rmpi installation.
B. Regards,
Javier
......

> Hi Javier,
>
> there is a new mailing list for R and HPC: r-sig-hpc at r-project.org
> This is probably a better list for your question.
>
> I never tried torque with socket. We use torque and mpi or pvm (and R)
> and it is working very well.
> Why do you use socket as communication layer?
> MPI was especially developed for communication between nodes in a
> computer cluster. And there you can specify which nodes and the number
> of processors per node you want use. Therfore I would strongly recommend
> to use MPI. This will be faster in every condition!
>
> Best
> Markus
>
>
> jgarcia at ija.csic.es wrote:
>> Hello all;
>> I'm trying to execute parallel jobs trough library snow on a cluster
>> built
>> through torque/PSB. I'm succesfully obtaining the cluster with:
>>
>>
>>> system("cat $PBS_NODEFILE > cluster.txt")
>>> mycluster <- scan(file="cluster.txt",what="character")
>>> cl <- makeSOCKcluster(mycluster)
>>
>> The only problem, at the moment, is that if I use processors in nodes
>> other that the one in which I'm running R, the communication is
>> extremely
>> slow. If all processor are in the "master" computer there not seems ti
>> be
>> any problem.
>>
>> Has anyone got any experience with this and any advice? Perhaps snow() s
>> not adequate for this kind of clusters?
>>
>> Thanks and best regards,
>> Javier
>>
>> ______________________________________________
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>> PLEASE do read the posting guide
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>
>
> --
> Dipl.-Tech. Math. Markus Schmidberger
>
> Ludwig-Maximilians-Universität München
> IBE - Institut für medizinische Informationsverarbeitung,
> Biometrie und Epidemiologie
> Marchioninistr. 15, D-81377 Muenchen
> URL: http://www.ibe.med.uni-muenchen.de
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>