Add example for multithreades matrix operation (OpenBLAS)

#OpenBLAS-multithreading.R

# This example illustrates the benefit of multi-threading in the context

# matrix operations (OpenBLAS).

library(RhpcBLASctl)  ## controls number of threads from within R

set.seed(2026)

X <- matrix(rnorm(5000^2), 5000)

# No multi-threading

blas_set_num_threads(1)

cat("Compute time for single-threaded OpenBLAS\n")

stime <- system.time({

   Xinv <- solve(X)

})[3]

print(stime)

# Two threads

blas_set_num_threads(2)

cat("Compute time for OpenBLAS with two threads\n")

system.time({

   Xinv <- solve(X)

})[3]

# Four threads

blas_set_num_threads(4)

cat("Compute time for OpenBLAS with four threads\n")

ptime <- system.time({

   Xinv <- solve(X)

})[3]

print(ptime)

cat(sprintf('Speed up for %d threads: %f\n',

            blas_get_num_procs(), round(stime / ptime, digits=2)))

#!/bin/bash

#

#SBATCH --job-name=r-openblas-multithreading

#SBATCH --comment="Multi-threading with OpenBLAS."

#SBATCH --partition=dev_cpu

#SBATCH --nodes=1

#SBATCH --tasks-per-node=4

#SBATCH --mem-per-cpu=1G

#SBATCH --time=00:05:00

# Make sure to specify the version

module purge

module load math/R/4.5.1

# Change to submission directory of this job (not needed)

cd "$SLURM_SUBMIT_DIR"

# Start program

R CMD BATCH --no-save --no-restore --slave OpenBLAS-multithreading.R