Rigid body constraints realized in massively-parallel molecular dynamics on graphics processing units

Trung Dac Nguyen, Carolyn L. Phillips, Joshua A. Anderson, Sharon C. Glotzer*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

119 Scopus citations


Molecular dynamics (MD) methods compute the trajectory of a system of point particles in response to a potential function by numerically integrating Newton's equations of motion. Extending these basic methods with rigid body constraints enables composite particles with complex shapes such as anisotropic nanoparticles, grains, molecules, and rigid proteins to be modeled. Rigid body constraints are added to the GPU-accelerated MD package, HOOMD-blue, version 0.10.0. The software can now simulate systems of particles, rigid bodies, or mixed systems in microcanonical (NVE), canonical (NVT), and isothermal-isobaric (NPT) ensembles. It can also apply the FIRE energy minimization technique to these systems. In this paper, we detail the massively parallel scheme that implements these algorithms and discuss how our design is tuned for the maximum possible performance. Two different case studies are included to demonstrate the performance attained, patchy spheres and tethered nanorods. In typical cases, HOOMD-blue on a single GTX 480 executes 2.5-3.6 times faster than LAMMPS executing the same simulation on any number of CPU cores in parallel. Simulations with rigid bodies may now be run with larger systems and for longer time scales on a single workstation than was previously even possible on large clusters.

Original languageEnglish (US)
Pages (from-to)2307-2313
Number of pages7
JournalComputer Physics Communications
Issue number11
StatePublished - Nov 1 2011


  • CUDA
  • GPU
  • Molecular dynamics
  • Rigid body

ASJC Scopus subject areas

  • Hardware and Architecture
  • Physics and Astronomy(all)

Fingerprint Dive into the research topics of 'Rigid body constraints realized in massively-parallel molecular dynamics on graphics processing units'. Together they form a unique fingerprint.

Cite this