Julia

Julia

Julia is a high-level, high-performance, dynamic programming language. While it is a general-purpose language and can be used to write any application, many of its features are well suited for numerical analysis and computational science.

Slurm Script

#!/bin/bash
# This is a slurm script for running Julia across
# multiple cores of one compute node

#SBATCH -p CUIQue
####SBATCH -A hpc_build
#SBATCH --time=1:00:00
###SBATCH --mail-type=end
###SBATCH --mail-user=teh1m@virginia.edu
#SBATCH --job-name=multipleTest1
#SBATCH --output=multipleTest1_%A.out
#SBATCH --error=multipleTest1_%A.err
#SBATCH --nodes=4 #Number of nodes
#SBATCH --ntasks-per-node=1 #Number of cores per node
#SBATCH --cpus-per-task=8 #Number of cores per node

# Load Julia environment
module load julia/1.6.3

srun julia helloDistributed.jl

The Code helloDistributed.jl

using Distributed

# launch worker processes
num_cores = parse(Int, ENV["SLURM_CPUS_PER_TASK"])
addprocs(num_cores)

println("Number of cores: ", nprocs())
println("Number of workers: ", nworkers())

# each worker gets its id, process id and hostname
for i in workers()
id, pid, host = fetch(@spawnat i (myid(), getpid(), gethostname()))
println(id, " " , pid, " ", host)
end

# remove the workers
for i in workers()
rmprocs(i)
end

Submit the job to the scheduler as

sbatch YourJuliaScript.slurm

For managing your “job” , refer to this guide.

For more on Julia, refer to their official documentation
https://docs.julialang.org/en/v1/