MPI Parallelization

IDTxl provides MPI-parallelization for serial CPU estimators.

Requirements

mpi4py>=3.0.0

Usage

To use MPI, simply add a MPI=True flag in the Estimator settings dictionary (one can optionally provide a n_workers argument) and start the script using

mpiexec -n 1 -usize <max workers + 1> python

on systems with MPI>=2.0 or

mpiexec -n <max workers + 1> python -m mpi4py.futures

on legacy MPI 1 implementations.

Limitations

Internally, the class MPIEstimator serves as a decorator for arbitrary serial Estimators (is_parallel()==False) sending chunks of data to individual Estimator instances on MPI worker ranks using mpi4py.futures.

MPIEstimator does not yet properly work with Estimators which are already parallel themselves (is_parallel()==True). Also, GPU support has not yet been implemented