ray_template/deployment_scripts/dask-worker.sh
2023-12-07 10:26:25 +01:00

31 lines
1.2 KiB
Bash

#!/bin/bash
#Get the current workspace directory and the master node
export CURRENT_WORKSPACE=$1
export DASK_SCHEDULER_HOST=$2
# Path to localscratch
echo "[$(date '+%Y-%m-%d %H:%M:%S') - Worker $HOSTNAME] INFO: Setting up Dask environment"
export DASK_ENV="/localscratch/${PBS_JOBID}/dask"
mkdir -p $DASK_ENV
# Extract Dask environment in localscratch
echo "[$(date '+%Y-%m-%d %H:%M:%S') - Worker $HOSTNAME] INFO: Extracting Dask environment to $DASK_ENV"
tar -xzf $CURRENT_WORKSPACE/dask-env.tar.gz -C $DASK_ENV
chmod -R 700 $DASK_ENV
# Start the dask environment
echo "[$(date '+%Y-%m-%d %H:%M:%S') - Worker $HOSTNAME] INFO: Setting up Dask environment"
source $DASK_ENV/bin/activate
conda-unpack
# Start Dask worker
export DASK_SCHEDULER_PORT="8786" # Replace with the port on which the Dask scheduler is running
# Additional Dask worker options can be added here if needed
# Change local directory if memory is an issue
# Change directory to localscratch and start Dask worker
cd $DASK_ENV
echo "[$(date '+%Y-%m-%d %H:%M:%S') - Worker $HOSTNAME] INFO: Starting Dask worker at $DASK_SCHEDULER_HOST on port $DASK_SCHEDULER_PORT"
dask worker $DASK_SCHEDULER_HOST:$DASK_SCHEDULER_PORT