R
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.
Warning
The CPU & GPU nodes have different CPU architectures (Intel & AMD respectively). Installing R packages on a CPU node will result in a failure if R is loaded and executed on a GPU node, and vice versa.
Interactive Usage
After connecting to Stanage (see Establishing a SSH connection), start an interactive session with the following command:
srun --pty bash -i
You can then load a specific version of R using:
module load R/4.0.0-foss-2020a
module load R/4.0.5-foss-2020b
module load R/4.2.1-foss-2022a
module load R/4.2.2-foss-2022b
R can then be run with:
$ R
Serial (one CPU) Batch usage
Here, we assume that you wish to run the program my_code.r on the system.
With batch usage it is recommended to load a specific version of R,
for example module load R/4.0.5-foss-2020b,
to ensure the expected output is achieved.
First, you need to write a batch submission file.
We assume you’ll call this my_job.slurm:
#!/bin/bash
#SBATCH --mem=4G # Request 4GB of memory
#SBATCH --mail-user=username@sheffield.ac.uk # Replace with your email address
module load R/4.0.5-foss-2020b # Recommended to load a specific version of R
R CMD BATCH my_code.r my_code.r.o$JOB_ID
Note that R must be called with both the CMD and BATCH options
which tell it to run an R program,
in this case my_code.r.
If you do not do this, R will attempt to open an interactive prompt.
The final argument, my_code.r.o$JOBID, tells R to send output to a file with this name.
Since $JOBID will always be unique, this ensures that all of your output files are unique.
Without this argument R sends all output to a file called my_code.Rout.
Ensuring that my_code.r and my_job.slurm are both in your current working directory,
submit your job to the batch system
sbatch my_job.slurm
Replace my_job.slurm with the name of your submission script.
Warning
By default, R will save variables in the workspace in the current directory
(in a file called .RData)
when a script exits and reload them when it starts from the same directory.
To disable this, add the --no-save and --no-restore options to your command
e.g. R CMD BATCH --no-save --no-restore my_code.r my_code.r.o$JOB_ID.
Graphical output
By default, graphical output from batch jobs is sent to a file called Rplots.pdf.
Installing additional packages
As you will not have permissions to install packages to the default folder,
additional R packages can be installed to your home folder ~/.
To create the appropriate folder,
install your first package in R in interactive mode.
Load an interactive R session as described above, and install a package with:
install.packages()
You will be prompted to create a personal package library. Choose ‘yes’. The package will download and install from a CRAN mirror (you may be asked to select a nearby mirror, which you can do simply by entering the number of your preferred mirror).
Once the chosen package has been installed,
additional packages can be installed either in the same way,
or by creating a .R script.
An example script might look like:
install.packages("dplyr")
install.packages("devtools")
Call this using source().
For example if your script is called packages.R and is stored in your home folder,
source this from an interactive R session with:
source("~/packages.R")
These additional packages will be installed without prompting to your personal package library.
To check your packages are up to date, and update them if necessary, run the following line from an R interactive session
update.packages(lib.loc = "~/R/x86_64-unknown-linux-gnu-library/3.6/")
The folder name after ~/R/ will likely change,
but this can be completed with tab autocompletion from the R session.
Ensure lib.loc folder is specified, or R will attempt to update the wrong library.
Warning
Notice that the personal package library path includes the version of R: if after installing some packages you switch to using a different major or minor version of R then you will need then to install those package for this new version.
R Packages that require external libraries
Some R packages require external libraries to be installed before you can install and use them
(e.g. rgdal, rgeos, hdf5r).
Since there are so many, we only install those libraries that have been explicitly requested by users of the system. The associated R packages are not included in the central installation of R.
To load external libraries you should search for a module which matches the build chain of the R version you are using to avoid load conflicts e.g. for R 4.0.5, foss-2020b.
To request the installation of dependencies for R packages that depend on non-R libraries
please contact research-it@sheffield.ac.uk.
Using the Rmath library in C Programs
The Rmath library allows you to access some of R’s functionality from a C program. For example, consider this C program:
#include <stdio.h>
#define MATHLIB_STANDALONE
#include "Rmath.h"
main(){
double shape1,shape2,prob;
shape1 = 1.0;
shape2 = 2.0;
prob = 0.5;
printf("Critical value is %lf\n",qbeta(prob,shape1,shape2,1,0));
}
This makes use of R’s qbeta function.
You can compile and run this on a worker node as follows.
Start a session on a worker node with srun --pty bash -i and load a version of R:
module load R/4.0.5-foss-2020b
Assuming the program is called test_rmath.c, compile with:
gcc test_rmath.c -lRmath -lm -o test_rmath
For full details about the functions made available by the Rmath library, see section 6.7 of the document Writing R extensions
Installation Notes
These notes are primarily for administrators of the system.
R/4.0.5-foss-2020b
R was installed using Easybuild 4.7.0, build details can be found in $EBROOTR/easyconfig.
Note: installed minus any of the configuration to install 700+ packages from CRAN
(i.e. just base R was installed).
NOTE: all R versions patched to address the CVE vulnerability using R-4.x_fix-CVE-2024-27322.patch