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Title: Implementation of metal-friendly EAM/FS-type semi-empirical potentials in HOOMD-blue: A GPU-accelerated molecular dynamics software

We present an implementation of EAM and FS interatomic potentials, which are widely used in simulating metallic systems, in HOOMD-blue, a software designed to perform classical molecular dynamics simulations using GPU accelerations. We first discuss the details of our implementation and then report extensive benchmark tests. We demonstrate that single-precision floating point operations efficiently implemented on GPUs can produce sufficient accuracy when compared against double-precision codes, as demonstrated in test simulations of calculations of the glass-transition temperature of Cu 64.5Zr 35.5, and pair correlation function of liquid Ni 3Al. Our code scales well with the size of the simulating system on NVIDIA Tesla M40 and P100 GPUs. Compared with another popular software LAMMPS running on 32 cores of AMD Opteron 6220 processors, the GPU/CPU performance ratio can reach as high as 4.6. In conclusion, the source code can be accessed through the HOOMD-blue web page for free by any interested user.
Authors:
ORCiD logo [1] ;  [2] ;  [2] ;  [1] ;  [1]
  1. Iowa State Univ., Ames, IA (United States). Dept. of Physics; Ames Lab., Ames, IA (United States)
  2. Ames Lab., Ames, IA (United States)
Publication Date:
Report Number(s):
IS-J-9610
Journal ID: ISSN 0021-9991; PII: S0021999118300251
Grant/Contract Number:
AC02-07CH11358
Type:
Accepted Manuscript
Journal Name:
Journal of Computational Physics
Additional Journal Information:
Journal Volume: 359; Journal Issue: C; Journal ID: ISSN 0021-9991
Publisher:
Elsevier
Research Org:
Ames Laboratory (AMES), Ames, IA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22). Materials Sciences & Engineering Division
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; Molecular dynamics; Embedded atom method; GPU computing; Metallic system simulation
OSTI Identifier:
1433659

Yang, Lin, Zhang, Feng, Wang, Cai-Zhuang, Ho, Kai-Ming, and Travesset, Alex. Implementation of metal-friendly EAM/FS-type semi-empirical potentials in HOOMD-blue: A GPU-accelerated molecular dynamics software. United States: N. p., Web. doi:10.1016/j.jcp.2018.01.015.
Yang, Lin, Zhang, Feng, Wang, Cai-Zhuang, Ho, Kai-Ming, & Travesset, Alex. Implementation of metal-friendly EAM/FS-type semi-empirical potentials in HOOMD-blue: A GPU-accelerated molecular dynamics software. United States. doi:10.1016/j.jcp.2018.01.015.
Yang, Lin, Zhang, Feng, Wang, Cai-Zhuang, Ho, Kai-Ming, and Travesset, Alex. 2018. "Implementation of metal-friendly EAM/FS-type semi-empirical potentials in HOOMD-blue: A GPU-accelerated molecular dynamics software". United States. doi:10.1016/j.jcp.2018.01.015.
@article{osti_1433659,
title = {Implementation of metal-friendly EAM/FS-type semi-empirical potentials in HOOMD-blue: A GPU-accelerated molecular dynamics software},
author = {Yang, Lin and Zhang, Feng and Wang, Cai-Zhuang and Ho, Kai-Ming and Travesset, Alex},
abstractNote = {We present an implementation of EAM and FS interatomic potentials, which are widely used in simulating metallic systems, in HOOMD-blue, a software designed to perform classical molecular dynamics simulations using GPU accelerations. We first discuss the details of our implementation and then report extensive benchmark tests. We demonstrate that single-precision floating point operations efficiently implemented on GPUs can produce sufficient accuracy when compared against double-precision codes, as demonstrated in test simulations of calculations of the glass-transition temperature of Cu64.5Zr35.5, and pair correlation function of liquid Ni3Al. Our code scales well with the size of the simulating system on NVIDIA Tesla M40 and P100 GPUs. Compared with another popular software LAMMPS running on 32 cores of AMD Opteron 6220 processors, the GPU/CPU performance ratio can reach as high as 4.6. In conclusion, the source code can be accessed through the HOOMD-blue web page for free by any interested user.},
doi = {10.1016/j.jcp.2018.01.015},
journal = {Journal of Computational Physics},
number = C,
volume = 359,
place = {United States},
year = {2018},
month = {1}
}