Molecular dynamics simulations with many-body potentials on multiple GPUs – the implementation, package and performance
Key Lab of Radiation Physics and Technology, Institute of Nuclear Science and Technology, Sichuan University, Chengdu 610064, China
arXiv:1212.6332 [physics.comp-ph], (27 Dec 2012)
@article{2012arXiv1212.6332H,
author={Hou}, Q. and {Li}, M. and {Zhou}, Y. and {Cui}, J. and {Cui}, Z. and {Wang}, J.},
title={"{Molecular dynamics simulations with many-body potentials on multiple GPUs – the implementation, package and performance}"},
journal={ArXiv e-prints},
archivePrefix={"arXiv"},
eprint={1212.6332},
primaryClass={"physics.comp-ph"},
keywords={Physics – Computational Physics},
year={2012},
month={dec},
adsurl={http://adsabs.harvard.edu/abs/2012arXiv1212.6332H},
adsnote={Provided by the SAO/NASA Astrophysics Data System}
}
Molecular dynamics (MD) is an important research tool extensively applied in materials science. Running MD on a graphics processing unit (GPU) is an attractive new approach for accelerating MD simulations. Currently, GPU implementations of MD usually run in a one-host-process-one-GPU (OHPOG) scheme. This scheme may pose a limitation on the system size that an implementation can handle due to the small device memory relative to the host memory. In this paper, we present a one-host-process-multiple-GPU (OHPMG) implementation of MD with embedded-atom-model or semi-empirical tight-binding many-body potentials. Because more device memory is available in an OHPMG process, the system size that can be handled is increased to a few million or more atoms. In comparison with the CPU implementation, in which Newton’s third law is applied to improve the computational efficiency, our OHPMG implementation has achieved a 28.9x~86.0x speedup in double precision, depending on the system size, the cut-off ranges and the number of GPUs. The implementation can also handle a group of small boxes in one run by combining the small boxes into a large box. This approach greatly improves the GPU computing efficiency when a large number of MD simulations for small boxes are needed for statistical purposes.
January 2, 2013 by hgpu
