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==== R ====

  * Home page: [[https://www.r-project.org|The R Project for Statistical Computing]]
  * Licenza: GPL

Several versions of R are available:

^ R      ^
| 3.4.4  |
| 3.5.2  |
| 3.5.3  |
| 3.6.3  |
| 4.0.5  |
| 4.1.2  |

Compilation details:

^ R      ^ Compiler   ^ BLAS             ^
| 3.4.4  | GNU 5.4.0  | OpenBLAS 0.2.20  |
| 3.5.2  | GNU 5.4.0  | OpenBLAS 0.2.20  |
| 3.5.3  | GNU 5.4.0  | OpenBLAS 0.2.20  |
| 3.6.3  | GNU 5.4.0  | OpenBLAS 0.2.20  |
| 4.0.5  | GNU 5.4.0  | OpenBLAS 0.2.20  |
| 4.1.2  | GNU 5.4.0  | OpenBLAS 0.2.20  |
| 3.4.4  | GNU 7.3.0  | OpenBLAS 0.2.20  |
| 3.5.2  | GNU 7.3.0  | OpenBLAS 0.2.20  |
| 3.5.3  | GNU 7.3.0  | OpenBLAS 0.2.20  |
| 3.6.3  | GNU 7.3.0  | OpenBLAS 0.2.20  |
| 4.0.5  | GNU 7.3.0  | OpenBLAS 0.2.20  |
| 4.1.2  | GNU 7.3.0  | OpenBLAS 0.2.20  |
| 3.4.4  | GNU 8.3.0  | OpenBLAS 0.3.7   |
| 3.5.2  | GNU 8.3.0  | OpenBLAS 0.3.7   |
| 3.5.3  | GNU 8.3.0  | OpenBLAS 0.3.7   |
| 3.6.3  | GNU 8.3.0  | OpenBLAS 0.3.7   |
| 4.0.5  | GNU 8.3.0  | OpenBLAS 0.3.7   |
| 4.1.2  | GNU 8.3.0  | OpenBLAS 0.3.7   |

For example the three versions of R 4.1.2 have been compiled with:
  * GNU 5.4.0 tool chain and OpenBLAS 0.2.20
  * GNU 7.3.0 tool chain and OpenBLAS 0.2.20
  * GNU 8.3.0 tool chain and OpenBLAS 0.3.7

Environment modules:

^ R      ^ Prerequisites  ^ Module   ^
| 3.4.4  | gnu/5.4.0      | R/3.4.4  |
| 3.5.2  | gnu/5.4.0      | R/3.5.2  |
| 3.5.3  | gnu/5.4.0      | R/3.5.3  |
| 3.6.3  | gnu/5.4.0      | R/3.6.3  |
| 4.0.5  | gnu/5.4.0      | R/4.0.5  |
| 4.1.2  | gnu/5.4.0      | R/4.1.2  |
| 3.4.4  | gnu7/7.3.0     | R/3.4.4  |
| 3.5.2  | gnu7/7.3.0     | R/3.5.2  |
| 3.5.3  | gnu7/7.3.0     | R/3.5.3  |
| 3.6.3  | gnu7/7.3.0     | R/3.6.3  |
| 4.0.5  | gnu7/7.3.0     | R/4.0.5  |
| 4.1.2  | gnu7/7.3.0     | R/4.1.2  |
| 3.4.4  | gnu8/8.3.0     | R/3.4.4  |
| 3.5.2  | gnu8/8.3.0     | R/3.5.2  |
| 3.5.3  | gnu8/8.3.0     | R/3.5.3  |
| 3.6.3  | gnu8/8.3.0     | R/3.6.3  |
| 4.0.5  | gnu8/8.3.0     | R/4.0.5  |
| 4.1.2  | gnu8/8.3.0     | R/4.1.2  |

=== R_LIBS_USER environment variable ===

The R module defines the environment variable

R_LIBS_USER

with the default value

$HOME/local/libraries/R/<R_MAJOR_VERSION>.<R_MINOR_VERSION>

So if you intend to install additional R packages, you have to create the directory where the libraries will be installed:

''mkdir -p "$R_LIBS_USER"''

As you can see the value of ''R_LIBS_USER'' does not include the patch level of the software.

This means, for example, that the packages installed in

''$HOME/local/libraries/R/4.1''

will be suitable for all versions of R 4.1.x series.

=== R packages ===

== Installation of R packages ==

In this example we will see how to install two R packages.

Script ''install-packages.R'':

<code install-packages.R>
install.packages("parallel", repos="http://cran.mirror.garr.it/mirrors/CRAN")
install.packages("MASS"    , repos="http://cran.mirror.garr.it/mirrors/CRAN")
</code>

Script ''install-packages.sh'':

<code bash install-packages.sh>
#!/bin/bash

module load gnu8/8.3.0
module load R/4.1.2

mkdir -p "$R_LIBS_USER"

R CMD BATCH install-packages.R

rm -f install-packages.Rout
</code>

Executing ''install-packages.sh'':

<code>
bash install-packages.sh
</code>

=== R serial job ===

== Execution of an R serial program ==

In this example we will see how to submit a serial job.

R script ''hello.R'':

<code text hello.R>
#!/usr/bin/env Rscript

sayHello <- function(){
   print('hello')
}

sayHello()
</code>

Script ''slurm-R-vrt.sh'':

<code bash slurm-R-vrt.sh>
#!/bin/bash
#SBATCH --job-name=hello
#SBATCH --output=%x.o%j
#SBATCH --error=%x.e%j
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --mem=512M
#SBATCH --partition=vrt
#SBATCH --time=0-00:05:00
##SBATCH --account=<account>

module load gnu8/8.3.0
module load R/4.1.2

Rscript --no-save hello.R
</code>

Submitting ''slurm-R-vrt.sh'':

<code>
sbatch slurm-R-vrt.sh
</code>

=== R parallel job ===

== Execution of an R parallel program ==

In this example we will see how to submit a parallel job on a single node.

R script ''loop.R'':

<code text loop.R>
#!/usr/bin/env Rscript

library(parallel)
library(MASS)

args = commandArgs(trailingOnly=TRUE)

if (length(args)==0) {
  args[1] = 1
}
numCores <- args[1]

x <- iris[which(iris[,5] != "setosa"), c(1,5)]
trials <- seq(1, 10000)
boot_fx <- function(trial) {
  ind <- sample(100, 100, replace=TRUE)
  result1 <- glm(x[ind,2]~x[ind,1], family=binomial(logit))
  r <- coefficients(result1)
  res <- rbind(data.frame(), r)
}
system.time({
  results <- mclapply(trials, boot_fx, mc.cores = numCores)
})
</code>

Script ''slurm-R-cpu.sh'':

<code bash slurm-R-cpu.sh>
#!/bin/bash
#SBATCH --job-name=loop
#SBATCH --output=%x.o%j
#SBATCH --error=%x.e%j
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=4
#SBATCH --mem=512M
#SBATCH --partition=cpu
#SBATCH --time=0-00:05:00
##SBATCH --account=<account>

module load gnu8/8.3.0
module load R/4.1.2

Rscript --no-save loop.R ${SLURM_NTASKS_PER_NODE:-1}
</code>

Submitting ''slurm-R-cpu.sh'':

<code>
sbatch slurm-R-cpu.sh
</code>