Submitting R Jobs

Listing 1 Serial \(\pi\) Monte Carlo R Script.

monte_carlo_pi <- function(n) {
  x=runif(n)
  y=runif(n)
  z=sqrt(x^2+y^2)
  length(which(z<=1))*4/n
}

args = commandArgs(trailing=TRUE)
monte_carlo_pi(strtoi(args[1]))

Listing 2 Parallel \(\pi\) Monte Carlo R Script.

library(parallel)

monte_carlo_pi <- function(n) {
  z = sqrt(runif(1)^2+runif(1)^2)
  return(if(z<=1) 1 else 0)
}

args = commandArgs(trailing=TRUE)
n = strtoi(args[1])
c = strtoi(args[2])
cl = makeCluster(getOption("cl.cores", c))
result = clusterApply(cl, 1:n, fun=monte_carlo_pi)
sum(unlist(result))*4/n
stopCluster(cl)

Listing 3 Interactive sessions using srun.

module load r/4.0.2
srun -p htc --mem=6G --pty $SHELL

Listing 4 Using sbatch --wrap.

module load r/4.0.2
sbatch -p htc --mem=6G  --wrap "sleep 30; time Rscript pi_monte_carlo_serial.R 1000"

Listing 5 Serial job using using sbatch.

#!/bin/bash
#SBATCH -J R
#SBATCH -o R_%j.out
#SBATCH -p htc
#SBATCH --mem=6G

module purge
module load r/4.0.2

time Rscript pi_monte_carlo_serial.R 1000

Listing 6 Parallel job using using sbatch.

#!/bin/bash
#SBATCH -J pi
#SBATCH -o pi_%j.out
#SBATCH -p development
#SBATCH --cpus-per-task=2
#SBATCH --mem=6G

module purge
module load r/4.0.2

time Rscript pi_monte_carlo_parallel.R 10000000 ${SLURM_CPUS_PER_TASK}

Listing 7 Array job using using sbatch.

#!/bin/bash
#SBATCH -J pi_array
#SBATCH -o pi_array_%a-%A.out
#SBATCH --array=1-4%2
#SBATCH -p development
#SBATCH --mem=6G

module purge
module load r/4.0.2

time Rscript pi_monte_carlo_serial.R $((100**${SLURM_ARRAY_TASK_ID}))