GPU-accelerated Tersoff potentials for massively parallel Molecular Dynamics simulations
Abstract
The Tersoff potential is one of the empirical many-body potentials that has been widely used in simulation studies at atomic scales. Unlike pair-wise potentials, the Tersoff potential involves three-body terms, which require much more arithmetic operations and data dependency. In this contribution, we have implemented the GPU-accelerated version of several variants of the Tersoff potential for LAMMPS, an open-source massively parallel Molecular Dynamics code. Compared to the existing MPI implementation in LAMMPS, the GPU implementation exhibits a better scalability and offers a speedup of 2.2X when run on 1000 compute nodes on the Titan supercomputer. On a single node, the speedup ranges from 2.0 to 8.0 times, depending on the number of atoms per GPU and hardware configurations. The most notable features of our GPU-accelerated version include its design for MPI/accelerator heterogeneous parallelism, its compatibility with other functionalities in LAMMPS, its ability to give deterministic results and to support both NVIDIA CUDA- and OpenCL-enabled accelerators. Our implementation is now part of the GPU package in LAMMPS and accessible for public use.
- Authors:
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1565556
- DOE Contract Number:
- AC05-00OR22725
- Resource Type:
- Journal Article
- Journal Name:
- Computer Physics Communications
- Additional Journal Information:
- Journal Volume: 212; Journal Issue: C; Journal ID: ISSN 0010-4655
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- Computer Science; Physics
Citation Formats
Nguyen, Trung Dac. GPU-accelerated Tersoff potentials for massively parallel Molecular Dynamics simulations. United States: N. p., 2017.
Web. doi:10.1016/j.cpc.2016.10.020.
Nguyen, Trung Dac. GPU-accelerated Tersoff potentials for massively parallel Molecular Dynamics simulations. United States. https://doi.org/10.1016/j.cpc.2016.10.020
Nguyen, Trung Dac. 2017.
"GPU-accelerated Tersoff potentials for massively parallel Molecular Dynamics simulations". United States. https://doi.org/10.1016/j.cpc.2016.10.020.
@article{osti_1565556,
title = {GPU-accelerated Tersoff potentials for massively parallel Molecular Dynamics simulations},
author = {Nguyen, Trung Dac},
abstractNote = {The Tersoff potential is one of the empirical many-body potentials that has been widely used in simulation studies at atomic scales. Unlike pair-wise potentials, the Tersoff potential involves three-body terms, which require much more arithmetic operations and data dependency. In this contribution, we have implemented the GPU-accelerated version of several variants of the Tersoff potential for LAMMPS, an open-source massively parallel Molecular Dynamics code. Compared to the existing MPI implementation in LAMMPS, the GPU implementation exhibits a better scalability and offers a speedup of 2.2X when run on 1000 compute nodes on the Titan supercomputer. On a single node, the speedup ranges from 2.0 to 8.0 times, depending on the number of atoms per GPU and hardware configurations. The most notable features of our GPU-accelerated version include its design for MPI/accelerator heterogeneous parallelism, its compatibility with other functionalities in LAMMPS, its ability to give deterministic results and to support both NVIDIA CUDA- and OpenCL-enabled accelerators. Our implementation is now part of the GPU package in LAMMPS and accessible for public use.},
doi = {10.1016/j.cpc.2016.10.020},
url = {https://www.osti.gov/biblio/1565556},
journal = {Computer Physics Communications},
issn = {0010-4655},
number = C,
volume = 212,
place = {United States},
year = {Wed Mar 01 00:00:00 EST 2017},
month = {Wed Mar 01 00:00:00 EST 2017}
}