Help and quick tips

Find here below some quick useful tips to submit jobs and compile your code. For any problem feel free to contact us.
The email should include as Subject: Kultrun Support.

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Modules system

Modules: basics

KULTRUN, has been configured to work on a module-based way. This allows users to easily set the environment needed to compile and run their codes.
The basic module command are


		module - shows the list of module commands

		module avail - shows a list of "available" modules

		module list - shows a list of loaded modules

		module load [name] - loads a module

		module unload [name] - unloads a module

		module help [name] - prints help for a module

		module whatis [name] - prints info about the module

		module purge - unload all modules

		module swap [name1] [name2] - swap two modules

Modules can be loaded automatically in the .bashrc file.

Modules available on Kultrun

In Kultrun we have all the basics modules to compile standard codes, hdf5 library, openmpi, mpich, fftw2, fftw3 the gsl libraries, GNU and Intel compilers.
We can install new modules when needed. See here below a list of the current available modules.


-------------------------- /opt/modulos/modulefiles ----------------------------

ansys/20.1            fftw/3.3.8_intel_mpi  gsl/2.4_intel         mpich/1.5             python/3.5.6

casa/5.3.0-143.el7    fftw/3.3.8_openmpi    hdf5/1.10.2           mpich/3.2.1           python/3.5.6_openmpi

fftw/2.1.5            gcc/4.9.4             hdf5/1.10.2_intel     openmpi/1.10.7

fftw/2.1.5_intel      gcc/5.5.0             intel/2018.3.222      openmpi/2.1.3

fftw/2.1.5_intel_mpi  gildas/jun19c         intel/impi-2018.3.222 openmpi/3.1.0

fftw/3.3.8            gsl/2.4               mercurial/4.6.1       python/2.7.16_intel

Typical batch scripts for Kultrun

To prepare job scripts you need so called "directives" and Slurm options.
Check it here for a comprehensive list.

MPI script INTEL env


#!/bin/bash

#SBATCH --job-name=test 

#SBATCH --partition=mapu 

#SBATCH -N 4 

#SBATCH --ntasks-per-node=32 



module load intel/2018.3.222

module load gsl/2.4_intel

module load hdf5/1.10.2_intel

module load fftw/2.1.5_intel



cd /home/user1/run_dir

srun --mpi=pmi2 ./code.exe input > output

MPI script GNU env


#!/bin/bash

#SBATCH --job-name=test_name 

#SBATCH --partition=kutral_amd

#SBATCH -N 1

#SBATCH --ntasks-per-node=32



module load openmpi/2.1.3



cd /home/user2/run_dir



mpiexec ./code input > ouput

MPI script on scratch dir


#!/bin/bash

#SBATCH --job-name=test_name 

#SBATCH --partition=kutral_amd

#SBATCH -N 1

#SBATCH --ntasks-per-node=32



module load openmpi/2.1.3



cd $SLURM_SUBMIT_DIR

export SCRDIR=/scratch/${SLURM_JOB_ID}

mkdir $SCRDIR

cp -rp * $SCRDIR/

cd $SCRDIR

mpiexec ./code input > ouput

cp -rp * $SLURM_SUBMIT_DIR

cd $SLURM_SUBMIT_DIR

rm -rf $SCRDIR

Hybrid (MPI+OpenMP)


#!/bin/bash

#SBATCH --job-name=hybrid 

#SBATCH --output=hydrid_job.txt

#SBATCH --ntasks=8

#SBATCH --cpus-per-task=5

#SBATCH --nodes=2



export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK



mpirun hello_hybrid.mpi

It is important to note that the usage of mpirun and mpiexec is identical.
On the opposite, for intel applications we strongly suggest to use srun with the option --mpi=pmi2 to let SLURM set the right environment (more here).