====== Matlab ======

Simple examples for running Matlab tasks can be found in the ''/home/SOFT/modules/examples/Matlab/'' directory, which you can copy to your own using:
  cp -r /home/SOFT/modules/examples/Matlab/ ./
In the //single// directory there are two files, the Matlab script "montecarlo_single.m" and the script for //sbatch// "slurm.sh". By typing
  cd single
  sbatch slurm.sh
will start a program on the queue system on a single core that takes about 20-40s to run (kraken-m1,...-m6 machines are faster on this job).

There is a similar example in the "parallel" directory for a job parallelized over 8 cores within a single node. The script for sbatch is:

  #!/bin/bash
  #SBATCH -J example_matlab
  #SBATCH -N 1
  #SBATCH -n 8
  #SBATCH --time=2:00
  #SBATCH -o slurm.%N.%J.%u.out # STDOUT
  #SBATCH -e slurm.%N.%J.%u.err # STDERR
  matlab -nodisplay -r "montecarlo_parallel;quit;"
  
Running a Matlab job across multiple nodes is not possible because the "Matlab Parallel Server" is not purchased. Therefore, you must always keep the option in the startup script
  #SBATCH -N 1

=== Parallel task: parpool ===
Parallel methods in Matlab programs are initialized with the "parpool" function. In our setup, a program using 8 cores must contain
  parpool('local', 8);
However, automaticall loading of the number of cores allocated by Slurm is possible and recommended for beginers. Slurm stores the value defined by "#SBATCH -n" in the system variable "SLURM_NTASKS", which Matlab can read
  sz = str2num(getenv('SLURM_NTASKS'));
  parpool('local',sz);