Minnesota Supercomputing Institute
With regards to the safety measures put in place by the university to mitigate the risks of the COVID-19 virus, at this time all MSI systems will remain operational and can be accessed remotely as usual. The only planned outages concern our in-person Helpdesk and tutorials. More information, as well as alternative remote support options, can be found at MSI COVID-19 Continuity Plan
3.0.1, 3.0.2, 3.1.0, 3.1.1, 3.1.1_intel_mkl, 3.1.3, 3.3.0, 3.2.1, 3.2.2, 3.4.4-tiff, 3.4.4, 4.0.0, 3.6.3, 3.3.2, 3.3.1, 3.5.2_mkl, 3.4.3, 3.2.5, 3.6.0, 3.3.3, 3.5.0
Monday, April 27, 2020
3.1.3, 3.3.0, 3.2.1, 3.2.2, 3.4.4-tiff, 3.4.4, 4.0.0, 3.6.3, 3.3.2, 3.3.1, 3.5.2_mkl, 3.4.3, 3.2.5, 3.6.0, 3.3.3, 3.5.0
R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.
To run this software interactively in a Linux environment run the commands:
module load R
Several versions of R are available, but the versions may be different on different platforms.To list all versions of R available on the machine, type
module avail R
We recommend that you install R packages in your home directory. It can be accomplished by typing the following in the R command prompt. You need to replace packagename with the actual package.
r <- getOption("repos");
r["CRAN"] <- "http://cran.rstudio.com/";
Some packages need external libraries such as gcc, gsl, fftw etc. You can find the requirements in the package documentation. These packages have to be loaded by using 'module load' command before using R. If you still experience issues, please contact email@example.com.
Programs can be submitted to a queue using PBS script such as the one below. You need to modify the parameters depending on the machine where the job is executed. By default, an R script runs only on one core. If you need to use multiple cores and/or multiple nodes, use packages that are listed in the CRAN page on high performance computing. The most popular R parallel packages are snow, snowfall, Rmpi and parallel.
#PBS -l nodes=1:ppn=8,mem=12gb,walltime=04:00:00
#PBS -m abe
module load R
R CMD BATCH myscript.R