mpi-sppy

Optimization under uncertainty for Pyomo <https://pyomo.org>_ models.

Documentation is available at readthedocs <https://mpi-sppy.readthedocs.io/en/latest/>_ and a there is a paper <https://link.springer.com/article/10.1007/s12532-023-00247-3>_

Status for internal tests ^^^^^^^^^^^^^^^^^^^^^^^^^

.. image:: https://github.com/Pyomo/mpi-sppy/workflows/pyomo%20tracker/badge.svg :target: https://github.com/Pyomo/mpi-sppy/actions/workflows/pyotracker.yml

MPI ^^^

A recent version of MPI and a compatible version of mpi4py are needed.

Here are two methods that seem to work well for installation, at least when considering non-HPC platforms.

#. Install OpenMPI and mpi4py using conda.

• conda install openmpi; conda install mpi4py (in that order)

#. If you already have an existing version of MPI, it may be better compile mpi4py against it. This can be done by installing mpi4py though pip.

• pip install mpi4py

To test your installation, cd to the directory where you installed mpi-sppy (it is called mpi-sppy) and then give this command.

mpirun -n 2 python -m mpi4py mpi_one_sided_test.py

If you don't see any error messages, you might have an MPI installation that will work well. Note that even if there is an error message, mpi-sppy may still execute and return correct results. Per the comment below, the run-times may just be unnecessarily inflated.

Installing mpi-sppy ^^^^^^^^^^^^^^^^^^^

It is possible to pip install mpi-sppy; however, most users are better off getting the software from github because it is under active development.

Citing mpi-sppy ^^^^^^^^^^^^^^^ If you find mpi-sppy useful in your work, we kindly request that you cite the following paper <https://link.springer.com/article/10.1007/s12532-023-00247-3>_:

::

@article{mpi-sppy, title={A Parallel Hub-and-Spoke System for Large-Scale Scenario-Based Optimization Under Uncertainty}, author={Bernard Knueven and David Mildebrath and Christopher Muir and John D Siirola and Jean-Paul Watson and David L Woodruff}, journal = {Math. Prog. Comp.}, volume = {15}, pages = {591-–619}, year={2023} }

AN IMPORTANT NOTE FOR MPICH USERS ON HPC PLATFORMS ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

At least on some US Department of Energy (e.g., at Lawrence Livermore National Laboratory) compute clusters, users of mpi-sppy that are using an MPICH implementation of MPI may need to set the following in order for both (1) proper execution of the one-sided test referenced above and (2) rapid results when running any of the algorithms shipped with mpi-sppy:

export MPICH_ASYNC_PROGRESS=1

Without this setting, we have observed run-times increase by a factor of between 2 and 4, due to non-blocking point-to-point calls apparently being treated as blocking.

Further, without this setting and in situations with a large number of ranks (e.g., >> 10), we have observed mpi-sppy stalling once scenario instances are created.

2022 NOTICE ^^^^^^^^^^^

There was a disruptive change on August 11, 2022 concerning how options are accessed. See the file disruptions.txt for more information. If you are a new user, this will not affect you, regardless of how you install. If you are an existing user, you should consider the disruption before updating to the latest mpi-sppy. The documentation on readthedocs probably refers to the newest version.