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R

R is a free software environment for statistical computing and graphics..

RStudio in Umbrella On Demand

Using R via Rstudio interactive
(Graphical User Interface)

Use your browser to connect to Umbrella On Demand

Using R in SLURM batch jobs
(Command Line Interface)

Test R

Load the module(s)

[user@umbrella]$ module purge
[user@umbrella]$ module load R/4.5.0-gfbf-2024a

Check the version of R

[user@umbrella]$ R --version
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
...
Check Rscript 
[user@umbrella]$ Rscript -e 'print("Hello!")'
[1] "Hello!"

R SLURM sbatch jobscript example using 4 CPU

#!/bin/bash
#SBATCH --job-name=test_r
#SBATCH --output=test_r-%j.log
#SBATCH --partition=tue.default.q
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=4
#SBATCH --mem-per-cpu=2gb
#SBATCH --time=00:05:00

module purge
module load R/4.5.0-gfbf-2024a

Rscript simple.r
simple.r 
a=1;
b=2;
print(a + b);

Package installation

The Comprehensive R Archive Network (CRAN) has packages available that can be used to extend R. On the HPC cluster specific version of R can be loaded using modules. Packages are installed specific for the version of R that was active during install; when the version of R is changed the packages need to be reinstalled.

Create a Rlibs directory in your home directory 

mkdir Rlibs

Load the module with a s specific version of R 

module load R/4.5.0-gfbf-2024a

Install a package and its dependency, in this example Rmpfr depends on gmp 

Rscript -e "install.packages('gmp','~/Rlibs','http://ftp.ussg.iu.edu/CRAN')"
Rscript -e "install.packages('Rmpfr','~/Rlibs','http://ftp.ussg.iu.edu/CRAN')"

NOTE : In your job script, you don't need to install the package again! In the previous part you installed it in your home directory, which is also available on the compute nodes, hence the package is automatically also installed there.

Parallelize R code on a Slurm cluster (rslurm)

Many computing-intensive processes in R involve the repeated evaluation of a function over many items or parameter sets. These so-called embarrassingly parallel calculations can be run serially with the lapply or Map function, or in parallel on a single machine with mclapply or mcMap (from the parallel package).

rslurm package

The rslurm package simplifies the process of distributing this type of calculation across a computing cluster that uses the Slurm workload manager. Its main function, slurm_apply (and the related slurm_map) automatically divide the computation over multiple nodes and write the necessary submission scripts. The package also includes functions to retrieve and combine the output from different nodes, as well as wrappers for common Slurm commands.