'R on Shark'
R can be run on all compute nodes, please do not run R on the head node, this will be automatically detected and an alert will be sent to the system maintainer and the job can and will be killed.
R is not a parallel program, it is single threaded which means that it only uses one processor, please keep in mind that R loads everything into memory and therefore you must keep an eye on the memory consumption on the node where R is running on,
you will not be the only one running on Shark. R can use multiple processors, there are multicore packages for R please read http://cran.r-project.org/web/views/HighPerformanceComputing.html
Please use R on Shark together with qsub, this is easily done with the folowing example:
The command to use in a shell script is : R CMD BATCH <script-naam.R>
Your R-script file with the name test.R looks like this:
The output of R can be found in the filename .Rout and the test.R example .Rout file looks like this:
#!/bin/bashR version 2.13.0 (2011-04-13)Copyright (C) 2011 The R Foundation for Statistical ComputingISBN 3-900051-07-0Platform: x86_64-unknown-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. Natural language support but running in an English localeR 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.[saved workspace restored](Previously)> M <- replicate(2, runif(10e5, 0, 1))> d <- data.frame(M)> colnames(d) <- c("y1", "y2")> attach(d)> > reg <- glm(cbind(y2) ~ y1, family = binomial)Warning message:In eval(expr, envir, enclos) : non-integer #successes in a binomial glm!> save(reg, file = "reg.Rdata")> > proc.time() user system elapsed 32.430 1.240 49.674