[R] random number generator in batch jobs
Prof Brian Ripley
ripley at stats.ox.ac.uk
Mon Jul 30 12:27:31 CEST 2007
Have you read the help page?
Initially, there is no seed; a new one is created from the
current time when one is required. Hence, different sessions will
give different simulation results, by default.
Thus if you choose to launch processes on different machines at the
same time you will get the same random number stream.
Running random number streams for parallel computation is a (very)
specialized topic and you need to be aware of the literature. I will
point out packages rsprng and accuracy (function runifS).
On Mon, 30 Jul 2007, Jiqiu Cheng wrote:
> Dear sir,
> I want to submit R batch jobs (e.g. 5) under the linux cluster by
> the script file "do_mul".
> The script file "do_mul"
> export var
> for var in $(seq 1 5)
> qsub -v var do_test
> exit 0
> Through "do_mul", 5 "do_test" script files are submitted to the cluster.
> The script file "do_test":
> #!/bin/bash -l
> #PBS -l ncpus=1
> #PBS -l walltime=0:05:00
> cd $PBS_O_WORKDIR
> mkdir test$var
> cd test$var
> module load R/2.5.0
> R --vanilla< test
> exit 0
> The content in R file "test" is :
> I expect to have different samples each time. However, for these 5
> replications, the first 3 jobs giving me the same samples and the last
> 2 are the same. I'm confused because I already used "R --vanilla" to
> avoid loading same workspace each time and "rm(list=ls(all=TRUE))" to
> remove the same random seed each time. Why do same samples still
> happen among 5 replications? Does anybody have some ideas to solve
> this problem? Looking forward to your reply, thanks.
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Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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