ray_template/deployment_scripts/submit-ray-job.pbs

#!/bin/bash
#PBS -N ray-job
#PBS -l select=2:node_type=rome
#PBS -l walltime=1:00:00

export WS_DIR=<workspace_dir>
export PROJECT_DIR=$WS_DIR/<project_name>
export JOB_SCRIPT=monte-carlo-pi.py

export ENV_ARCHIVE=ray_env.tar.gz

export OBJECT_STORE_MEMORY=128000000000

# Environment variables after this line should not change

export SRC_DIR=$PROJECT_DIR/src
export PYTHON_FILE=$SRC_DIR/$JOB_SCRIPT
export DEPLOYMENT_SCRIPTS=$PROJECT_DIR/deployment_scripts
export ENV_PATH=/run/user/$PBS_JOBID/ray_env # We use the ram disk to extract the environment packages since a large number of files decreases the performance of the parallel file system.

mkdir -p $ENV_PATH
tar -xzf $WS_DIR/$ENV_ARCHIVE -C $ENV_PATH # This line extracts the packages to ram disk.
source $ENV_PATH/bin/activate

export IP_ADDRESS=`ip addr show ib0 | grep -oP '(?<=inet\s)\d+(\.\d+){3}' | awk '{print $1}'`

export RAY_ADDRESS=$IP_ADDRESS:6379
export REDIS_PASSWORD=$(openssl rand -base64 32)

export NCCL_DEBUG=INFO

ray start --disable-usage-stats \
        --head \
        --node-ip-address=$IP_ADDRESS \
        --port=6379 \
        --dashboard-host=127.0.0.1 \
        --redis-password=$REDIS_PASSWORD \
        --object-store-memory=$OBJECT_STORE_MEMORY

export NUM_NODES=$(sort $PBS_NODEFILE |uniq | wc -l)

for ((i=1;i<$NUM_NODES;i++)); do
        pbsdsh -n $i -- bash -l -c "'$DEPLOYMENT_SCRIPTS/ray-start-worker.sh' '$WS_DIR' '$ENV_ARCHIVE' '$RAY_ADDRESS' '$REDIS_PASSWORD' '$OBJECT_STORE_MEMORY'" &
done

python3 $PYTHON_FILE

ray stop --grace-period 30

rm -rf $ENV_PATH # It's nice to clean up before you terminate the job.