With pylammpsmpi you can control a mpi4py parallel LAMMPS instance from a serial python process or a Jupyter
notebook. Internally pylammpsmpi leverages the executorlib communication interface to connect the serial python
process the user interacts with, with the mpi4py parallel LAMMPS instance. The advantage of separating the mpi4py
parallel LAMMPS instance from the rest of the workflow is that the workflow can be written as serial python code, while
still benefiting from the parallel performance of LAMMPS. Still this comes at the cost of additional data transfer, as
the LAMMPS pointers cannot be transferred this way and the linked data has to be copied instead. So copying large
atomistic structures can decrease the performance of the pylammpsmpi interface in comparison to writing your own fully
mpi4py parallel LAMMPS workflows.
The pylammpsmpi module implements three different interfaces for different use cases:
pylammpsmpi.LammpsBase: The most basic interface is theLammpsBase, it implements the same commands like the defaultlammps.lammpsinterface and returns the same datatypes. With this API compatibility to the standard interface, this interface is commonly the easiest way to accelerate a serial LAMMPS based workflow by leveragingmpi4pyparallel LAMMPS instances.pylammpsmpi.LammpsConcurrent: Inspired by theconcurrent.futuresmodule in the standard python library thepylammpsmpi.LammpsConcurrentinterface implements the same API as thepylammpsmpi.LammpsBaseclass but rather than holding the controlling process until thempi4pyparallel LAMMPS instance finishes the execution of a given set of commands, thepylammpsmpi.LammpsConcurrentinterface returns aconcurrent.futures.Futureobject. This enables the development of asynchronous / concurrent workflows.pylammpsmpi.LammpsLibrary: Finally, thepylammpsmpi.LammpsLibraryinterface adds a higher level interface on top of the defaultlammps.lammpsinterface. This higher level interface provides direct access to the commands and thermodynamic properties used in the LAMMPS input files. Especially for experienced LAMMPS users who are familiar with the LAMMPS input files this interface simplifies switching from file based input to using the python interface.
The choice of interface depends on the users background, experience and the simulation protocol the user wants to
implement. Still internally all three interfaces are based on the pylammpsmpi.LammpsConcurrent interface, so they use
an additional thread to connect the mpi4py parallel LAMMPS instance to the serial python process or Jupyter notebook.
pylammpsmpi is released under the BSD license https://github.com/pyiron/pylammpsmpi/blob/main/LICENSE . It is a
spin-off of the pyiron project https://github.com/pyiron/pyiron therefore if you use pylammpsmpi for calculation
which result in a scientific publication, please cite:
@article{pyiron-paper,
title = {pyiron: An integrated development environment for computational materials science},
journal = {Computational Materials Science},
volume = {163},
pages = {24 - 36},
year = {2019},
issn = {0927-0256},
doi = {https://doi.org/10.1016/j.commatsci.2018.07.043},
url = {http://www.sciencedirect.com/science/article/pii/S0927025618304786},
author = {Jan Janssen and Sudarsan Surendralal and Yury Lysogorskiy and Mira Todorova and Tilmann Hickel and Ralf Drautz and Jörg Neugebauer},
keywords = {Modelling workflow, Integrated development environment, Complex simulation protocols},
}