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

doi:10.1016/j.cpc.2011.06.005

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

Chemical and Biological Engineering

Research output: Contribution to journal › Article › peer-review

166 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	2307-2313
Number of pages	7
Journal	Computer Physics Communications
Volume	182
Issue number	11
DOIs	https://doi.org/10.1016/j.cpc.2011.06.005
State	Published - Nov 2011

Funding

We thank Aaron Keys for helpful discussions on the FIRE algorithm for rigid bodies and Anthony Sheh for helping with the CPU implementation of the quaternion scheme. This research was supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering , under award DE-FG02-02ER46000 , the U.S. Department of Energy Computational Science Graduate Fellowship , and DOD/DDRE under the National Security Science & Engineering Faculty Fellowship award N00244-09-1-0062 . Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the DOD/DDRE. T.D.N. also acknowledges the Vietnam Education Foundation . The authors acknowledge support from the James S. McDonnell Foundation 21st Century Science Research Award/Studying Complex Systems .

Keywords

CUDA
GPGPU
GPU
Molecular dynamics
Rigid body

ASJC Scopus subject areas

Hardware and Architecture
General Physics and Astronomy

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10.1016/j.cpc.2011.06.005

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title = "Rigid body constraints realized in massively-parallel molecular dynamics on graphics processing units",

abstract = "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.",

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author = "Nguyen, {Trung Dac} and Phillips, {Carolyn L.} and Anderson, {Joshua A.} and Glotzer, {Sharon C.}",

note = "Funding Information: We thank Aaron Keys for helpful discussions on the FIRE algorithm for rigid bodies and Anthony Sheh for helping with the CPU implementation of the quaternion scheme. This research was supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering , under award DE-FG02-02ER46000 , the U.S. Department of Energy Computational Science Graduate Fellowship , and DOD/DDRE under the National Security Science & Engineering Faculty Fellowship award N00244-09-1-0062 . Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the DOD/DDRE. T.D.N. also acknowledges the Vietnam Education Foundation . The authors acknowledge support from the James S. McDonnell Foundation 21st Century Science Research Award/Studying Complex Systems .",

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N2 - 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.

AB - 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.

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

Abstract

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Keywords

ASJC Scopus subject areas

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