(656b) Designing a Python Interface for Molecular Dynamics and Monte Carlo Particle Simulations: HOOMD-Blue v3.0

HOOMD-blue [1] is a general-purpose toolkit that performs molecular dynamics and Monte Carlo simulations of particles. Much has changed in the scientific Python ecosystem since HOOMD-blue’s initial release in 2008. In this talk, we describe the design and implementation of the next major release of HOOMD-blue, v3.0. This release includes a new object-oriented Python interface, adds integrations with commonly used packages like NumPy, allows users to implement customizations to the simulation run loop, and offers a flexible system for accessing and logging computed quantities. As one example, HOOMD-blue v3.0 integrates with the MoSDeF [2] toolkit, allowing users to generate complex initial conditions with mBuild, atom-type the system with foyer, define force fields with gmso, and then run those simulations with HOOMD-blue – all in one Python script or notebook. I will also describe the software engineering practices we employ. We have made a major effort to increase the amount of testing we perform in v3.0 including new and rewritten unit and validation tests using the pytest framework that execute on continuous integration platforms. We provide binaries through Docker and Singularity images that support high performance computing clusters such as PSC Bridges2 and SDSC Expanse. We also provide generic container images for workstations as well as conda packages through conda-forge. To minimize developer effort, we use continuous integration systems to automate the release process.

[1]: Anderson, J. A., Glaser, J., & Glotzer, S. C. (2020). HOOMD-blue: A Python package for high-performance molecular dynamics and hard particle Monte Carlo simulations. Computational Materials Science, 173, 109363. http://glotzerlab.engin.umich.edu/hoomd-blue/

[2]: Thompson, M. W., Gilmer, J. B., Matsumoto, R. A., Quach, C. D., Shamaprasad, P., Yang, A. H., Iacovella, C. R., McCabe, C., & Cummings, P. T. (2020). Towards molecular simulations that are transparent, reproducible, usable by others, and extensible (TRUE). Molecular Physics, 118(9–10), e1742938. https://mosdef.org/