slurm_arr

#!/bin/bash
#! Name of the job:
#SBATCH -J Euclifer
#! Which project should be charged:
#SBATCH -A HANDLEY-SL3-CPU
#! How many whole nodes should be allocated?
#SBATCH --nodes=1
#! How many (MPI) tasks will there be in total? (<= nodes*32)
#! The skylake/skylake-himem nodes have 32 CPUs (cores) each.
#SBATCH --ntasks=1 --cpus-per-task=20
#! How much wallclock time will be required?
#SBATCH --time=12:00:00
#! Where do you store the output?
#SBATCH --output="./output/%a-slurm.out"
#! What types of email messages do you wish to receive?
#SBATCH --mail-type=END
#!ARRAY JOB
#SBATCH --array=1-20

#! Each task is allocated 1 core by default, and each core is allocated 5980MB (skylake)
#! and 12030MB (skylake-himem). If this is insufficient, also specify
#! --cpus-per-task and/or --mem (the latter specifies MB per node).


#! Number of nodes and tasks per node allocated by SLURM (do not change):
numnodes=$SLURM_JOB_NUM_NODES
numtasks=$SLURM_NTASKS
mpi_tasks_per_node=$(echo "$SLURM_TASKS_PER_NODE" | sed -e  's/^\([0-9][0-9]*\).*$/\1/')


#! ############################################################0
#! Modify the settings below to specify the application's environment, location
#! and launch method:

#! Optionally modify the environment seen by the application
. /etc/profile.d/modules.sh                # Leave this line (enables the module command)
module purge                               # Removes all modules still loaded
module load rhel7/default-peta4            # REQUIRED - loads the basic environment

#! Full path to application executable:
application="/home/mgv29/.conda/envs/myenv/bin/python"

#! Run options for the application:
options="main_hpc.py"

#! Work directory (i.e. where the job will run):
workdir="/home/mgv29/rds/hpc-work/Euclifer"

#! Are you using OpenMP (NB this is unrelated to OpenMPI)? If so increase this
#! safe value to no more than 32:
export OMP_NUM_THREADS=1

#! Number of MPI tasks to be started by the application per node and in total (do not change):
np=$[${numnodes}*${mpi_tasks_per_node}]

#! The following variables define a sensible pinning strategy for Intel MPI tasks -
#! this should be suitable for both pure MPI and hybrid MPI/OpenMP jobs:
export I_MPI_PIN_DOMAIN=omp:compact # Domains are $OMP_NUM_THREADS cores in size
export I_MPI_PIN_ORDER=scatter # Adjacent domains have minimal sharing of caches/sockets
#! Notes:
#! 1. These variables influence Intel MPI only.
#! 2. Domains are non-overlapping sets of cores which map 1-1 to MPI tasks.
#! 3. I_MPI_PIN_PROCESSOR_LIST is ignored if I_MPI_PIN_DOMAIN is set.
#! 4. If MPI tasks perform better when sharing caches/sockets, try I_MPI_PIN_ORDER=compact.


#! Uncomment one choice for CMD below (add mpirun/mpiexec options if necessary):

#! Choose this for a MPI code (possibly using OpenMP) using Intel MPI.
CMD="mpirun -ppn $mpi_tasks_per_node -np $np $application $options"

#! Choose this for a pure shared-memory OpenMP parallel program on a single node:
#! (OMP_NUM_THREADS threads will be created):
#CMD="$application $options"

#! Choose this for a MPI code (possibly using OpenMP) using OpenMPI:
#CMD="mpirun -npernode $mpi_tasks_per_node -np $np $application $options"


###############################################################
### You should not have to change anything below this line ####
###############################################################

cd $workdir
echo -e "Changed directory to `pwd`.\n"

JOBID=$SLURM_JOB_ID

echo -e "JobID: $JOBID\n======"
echo "Time: `date`"
echo "Running on master node: `hostname`"
echo "Current directory: `pwd`"

if [ "$SLURM_JOB_NODELIST" ]; then
        #! Create a machine file:
        export NODEFILE=`generate_pbs_nodefile`
        cat $NODEFILE | uniq > machine.file.$JOBID
        echo -e "\nNodes allocated:\n================"
        echo `cat machine.file.$JOBID | sed -e 's/\..*$//g'`
fi

echo -e "\nnumtasks=$numtasks, numnodes=$numnodes, mpi_tasks_per_node=$mpi_tasks_per_node (OMP_NUM_THREADS=$OMP_NUM_THREADS)"

echo -e "\nExecuting command:\n==================\n$CMD\n"

eval $CMD