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Title: 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}
}