Easily deploy Dask using MPI

The Dask-MPI project makes it easy to deploy Dask from within an existing MPI environment, such as one created with the common MPI command-line launchers mpirun or mpiexec. Such environments are commonly found in high performance supercomputers, academic research institutions, and other clusters where MPI has already been installed. Dask-MPI provides a convenient interface for launching your cluster either from within a batch script or directly from the command-line.


You can launch a Dask cluster directly from the command-line using the dask-mpi command and specifying a scheduler JSON file.

mpirun -np 4 dask-mpi --scheduler-file /path/to/scheduler.json

You can then access this cluster from a batch script or an interactive session (such as a Jupyter Notebook) by referencing the scheduler file.

from dask.distributed import Client
client = Client(scheduler_file='/path/to/scheduler.json')


Alternatively, you can turn your batch Python script into an MPI executable simply by using the initialize function.

from dask_mpi import initialize

from dask.distributed import Client
client = Client()  # Connect this local process to remote workers

which makes your Python script launchable directly with mpirun or mpiexec.

mpirun -np 4 python my_client_script.py