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Here's an example R file that generates a large array, fills it with some random numbers, then sleeps for 5mins. This happens to use up almost exactly 8GB of RAM.

[chekh@corn-image-new.stanford.edu] /mnt/glusterfs/chekh/R_test [0] 
$ cat 8GB.R 
x <- array(1:1073741824, dim=c(1024,1024,1024)) 
x <- gaussian()

Here's an example SGE submit script that runs that R file.

$ cat r_test.script

# use the current directory
#$ -cwd
# mail this address
#$ -M chekh@stanford.edu
# send mail on begin, end, suspend
#$ -m bes
# get rid of spurious messages about tty/terminal types
#$ -S /bin/sh

R --vanilla --no-save < 8GB.R 

You can submit it with just

 qsub r_test.script

Here are the output files that I get, one from stderr, one from stdout

$ cat r_test.script.e497 
tset: standard error: Function not implemented

Undefined tty
stdin: is not a tty

$ cat r_test.script.o497 
Warning: no access to tty (Bad file descriptor).
Thus no job control in this shell.

R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- array(1:1073741824, dim=c(1024,1024,1024)) 
> x <- gaussian()
> Sys.sleep(300)

Those errors about tty and job control have something to do with shell startup and terminal settings, and are normal. Or specify the 'sh' shell in your job script

 #get rid of spurious messages about tty/terminal types
 #$ -S /bin/sh

In the mail that you get about the ending of the job, the maxvmem number is actually incorrect, it is a known bug in this version of SGE. The R script on this page actually uses 8GB of vmem.


Some other departments have some other more detailed examples:

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