#!/bin/bash --login

###################################################################################################
# WARNING: Please adapt all relevant parameters so that they fit the requirements of your job(s). #
# Questions and Remarks welcome to Sebastian Kraus                                                #
###################################################################################################

# %x: job name; %j: job id; %N: node; %t: task id; %a: array id (and others)
# #SBATCH -o %x.%j.%N.out  # for debugging purposes: redirect SLURM's stdout (please see man 1 sbatch for explanation of replacement symbols)
# #SBATCH -e %x.%j.%N.err  # for debugging purposes: redirect SLURM's stderr (please see man 1 sbatch for explanation of replacement symbols)

# #SBATCH -D $PWD               # if needed change to current working directory

#SBATCH -J jobname              # job name
#SBATCH -n 1                    # total number of tasks/cores for your job
#SBATCH --hint=nomultithread     # IMPORTANT: hyper-threading is activated; switch off and attribute whole core to task
# #SBATCH --ntasks-per-node=1   # number of tasks per node
#SBATCH -N 1                    # number of nodes
# #SBATCH -p smp                # partition the job gets scheduled: standard (default), smp, gpu (uncomment, if you want your job to run on hosts in SMP partition)
#SBATCH --time=00:15:00         # job run (wall clock) time in HH:MM:SS
#SBATCH --mem=4GB               # amount of resident main memory PER NODE(!)
# #SBATCH --mem-per-cpu=1GB     # amount of resident main memory PER CORE(!) (set only, if needed)

# #SBATCH --gres=gpu:tesla:1    # GPU resources (only with gpu partition!)

# #SBATCH --mail-type=END       # if your want to receive notifications about job status (cf. man 1 sbatch)
# #SBATCH --mail-user=username


# and now your job definition ;-)

module add [your_modules]

[your_commands]