.launch-jupyter-slurm

#!/bin/bash

#SBATCH --qos=gpushort
#SBATCH --partition=gpu
#SBATCH --gres=gpu:v100:1
#SBATCH --job-name=jupyter
#SBATCH --account=dominoes
#SBATCH --nodes=1
#SBATCH --ntasks=1
##SBATCH --ntasks=16
#SBATCH --cpus-per-task=1
##SBATCH --mem=60000
#SBATCH --time=1-00:00:00
#SBATCH --output=jupyter-slurm-%j.log

###
# This script is to be submitted via "sbatch" on the cluster.
#
# Set --cpus-per-task above to match the size of your multiprocessing run, if any.
###

echo "Job started with SLURM ID $SLURM_JOBID"
echo "Running on node(s): $SLURM_NODELIST"
echo "------------------------------------------------------------"

cd $HOME

# Some initial setup
module purge
module load anaconda &> /dev/null  # suppress stdout # this is where the Jupyter client comes from

# optional: if you have a Conda env, activate it here:
#MY_CONDA_ENV=py2
MY_CONDA_ENV=py3

source activate $MY_CONDA_ENV

# set the port on which the browser will listen
BROWSERPORT=7071

# set a random port for the notebook, in case multiple notebooks are
# on the same compute node.
NOTEBOOKPORT=`shuf -i 8000-8500 -n 1`

# set a random port for tunneling, in case multiple connections are happening
# on the same login node.
#TUNNELPORT=`shuf -i 8501-9000 -n 1`
TUNNELPORT=8081

echo "On your local machine, run"
echo "    ssh -L localhost:$BROWSERPORT:localhost:$TUNNELPORT $(whoami)@$SLURM_SUBMIT_HOST.pik-potsdam.de -N"
echo "and point your browser to"
echo "    http://localhost:$BROWSERPORT"
echo "To stop this notebook, run"
echo "    scancel $SLURM_JOB_ID"
echo "------------------------------------------------------------"

# Set up a reverse SSH tunnel from the compute node back to the submitting host (login01 or login02)
# This is the machine we will connect to with SSH forward tunneling from our client.
echo "Setting up reverse SSH tunnel from compute node back to submitting host"
ssh -R$TUNNELPORT:localhost:$NOTEBOOKPORT $SLURM_SUBMIT_HOST -N -f

# Start the notebook
echo "Starting the notebook"
srun -n1 jupyter-notebook --no-browser --port=$NOTEBOOKPORT --NotebookApp.iopub_data_rate_limit=10000000000

wait