dask_mpi.core.initialize

dask_mpi.core.initialize(interface=None, nthreads=1, local_directory='', memory_limit='auto', nanny=False, bokeh=True, bokeh_port=8787, bokeh_prefix=None, bokeh_worker_port=8789)[source]

Initialize a Dask cluster using mpi4py

Using mpi4py, MPI rank 0 launches the Scheduler, MPI rank 1 passes through to the client script, and all other MPI ranks launch workers. All MPI ranks other than MPI rank 1 block while their event loops run and exit once shut down.

Parameters:
interface : str

Network interface like ‘eth0’ or ‘ib0’

nthreads : int

Number of threads per worker

local_directory : str

Directory to place worker files

memory_limit : int, float, or ‘auto’

Number of bytes before spilling data to disk. This can be an integer (nbytes), float (fraction of total memory), or ‘auto’.

nanny : bool

Start workers in nanny process for management

bokeh : bool

Enable Bokeh visual diagnostics

bokeh_port : int

Bokeh port for visual diagnostics

bokeh_prefix : str

Prefix for the bokeh app

bokeh_worker_port : int

Worker’s Bokeh port for visual diagnostics