PyLauncherMPI

A simple MPI-based task scheduler for dynamically distributing commands across MPI processes.

How to use

Assuming there is access to HPC resources with MPI capabilities, PyLauncherMPI can be used to dynamically allocate tasks to processes. Tasks are defined as shell commands in a file, one line per task, like so:

taskfile

./my_program arg1 arg2 arg3
./my_program arg4 arg5 arg6
...

Two environment variables need to be speified, LAUNCHER_WORKDIR (the absolute path from which all tasks will be executed), and LAUNCHER_JOB_FILE (the path to the task file relative to LAUNCHER_WORKDIR).

The following is an example SLURM script using PyLauncherMPI.

#!/bin/bash
#SBATCH -J test_job        # Job name
#SBATCH -o test_job.o%j    # Name of stdout file
#SBATCH -e test_job.e%j    # Name of stderr error file
#SBATCH -p xyz             # Queue (partition) name
#SBATCH -N 3               # Total # of nodes
#SBATCH -n 144             # Total # of mpi tasks
#SBATCH -t 00:02:30        # Run time (hh:mm:ss)
##SBATCH --mail-user=username@address.xyz
##SBATCH --mail-type=all
#SBATCH -A allocation_name # Allocation name (req'd if you have more than 1)

source $HOME/.bashrc

micromamba activate rid_prj
# (Or use any other way to activate the environment where PyLauncherMPI is installed.)

export OMP_NUM_THREADS=1
export PYTHONPATH=$PYTHONPATH:$(pwd):$HOME/bin
export LAUNCHER_WORKDIR=/path/to/project/root/directory
export LAUNCHER_JOB_FILE=relative/path/name_of_taskfile

ibrun pylaunchermpi