HOOMD-blue

HOOMD-blue is a general-purpose particle simulation toolkit. It scales from a single CPU core to thousands of GPUs. You define particle initial conditions and interactions in a high-level python script. Then tell HOOMD-blue how you want to execute the job and it takes care of the rest. Python job scripts give you unlimited flexibility to create custom initialization routines, control simulation parameters, and perform in situ analysis. Download and get started using HOOMD-blue today. Please cite HOOMD-blue if you use it published work.

Keywords for this software

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References in zbMATH (referenced in 6 articles )

Showing results 1 to 6 of 6.
Sorted by year (citations)

  1. Paret, Joris; Coslovich, Daniele: partycls: A Python package for structural clustering (2021) not zbMATH
  2. T. L. Underwood, J. A. Purton, J. R. H. Manning, A. V. Brukhno, K. Stratford, T. Düren, N. B. Wilding, S. C. Parker: dlmontepython: A Python library for automation and analysis of Monte Carlo molecular simulations (2021) arXiv
  3. Barrett, R.; Chakraborty, M.; Amirkulova, D.; Gandhi, H.; Wellawatte, G.; White, A.: HOOMD-TF: GPU-Accelerated, Online Machine Learning in the HOOMD-blue Molecular Dynamics Engine (2020) not zbMATH
  4. Fiore, Andrew M.; Swan, James W.: Fast Stokesian dynamics (2019)
  5. Vyas Ramasubramani; Sharon C. Glotzer: rowan: A Python package for working with quaternions (2018) not zbMATH
  6. Anderson, Joshua A.; Jankowski, Eric; Grubb, Thomas L.; Engel, Michael; Glotzer, Sharon C.: Massively parallel Monte Carlo for many-particle simulations on GPUs (2013)