Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-28T03:06:32.309Z Has data issue: false hasContentIssue false
  • English
  • Français

Parallelization of Molecular-Dynamics Simulations Using Tasks

Published online by Cambridge University Press:  12 February 2015

Ralf Meyer  and
Chris M. Mangiardi
Ralf Meyer
Affiliation:
Department of Mathematics and Computer Science, Laurentian University, Sudbury, ON P3E 2C6, Canada Department of Physics, Laurentian University, Sudbury, ON P3E 2C6, Canada
Chris M. Mangiardi
Affiliation:
Department of Mathematics and Computer Science, Laurentian University, Sudbury, ON P3E 2C6, Canada
Get access

Abstract

This article discusses novel algorithms for molecular-dynamics (MD) simulations with short-ranged forces on modern multi- and many-core processors like the Intel Xeon Phi. A task-based approach to the parallelization of MD on shared-memory computers and a tiling scheme to facilitate the SIMD vectorization of the force calculations is described. The algorithms have been tested with three different potentials and the resulting speed-ups on Intel Xeon Phi coprocessors are shown.

Keywords

simulationstructuralmetal
Type
Articles
Information
MRS Online Proceedings Library (OPL) , Volume 1753: Symposium NN – Mathematical and Computational Aspects of Materials Science , 2015 , mrsf14-1753-nn10-09
Copyright
Copyright © Materials Research Society 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Meyer, R., Phys. Rev. E 88, 053309 (2013); J. Phys.: Conf. Ser. 540, 012006(2014).Google Scholar
Allen, M. P. and Tildesley, D. J., Computer Simulations of Liquids, REP edition (Clarendon, Oxford, 1989) pp. 149–152.Google Scholar
Ackland, G. J., D’Mellow, K., Daraszewicz, S. L., Hepburn, D. J., Uhrin, M., and Stratford, K., Comp. Phys. Comm. 182, 2587 (2011).CrossRefGoogle Scholar
Cleri, F. and Rosato, V., Phys. Rev. B 48, 22 (1993).CrossRefGoogle Scholar
Mendelev, M. I., Han, S., Srolovitz, D. J., Ackland, G. J., Sun, D. Y., and Asta, M., Phil. Mag. 83, 3977 (2003).CrossRefGoogle Scholar
Lennard-Jones, J. E., Proc. Roy. Soc. Lond. A 106, 463 (1924); Proc. Phys. Soc. 43, 461(1931).Google Scholar
Allen, M. P. and Tildesley, D. J., Computer Simulations of Liquids, REP edition (Clarendon, Oxford, 1989) p. 9.Google Scholar
Allen, M. P. and Tildesley, D. J., Computer Simulations of Liquids, REP edition (Clarendon, Oxford, 1989) p. 29.Google Scholar
Jeffers, J. and Reinders, J., Intel ® Xeon Phi™ Coprocessor High-Performance Programming (Morgan Kaufman, New York 2013) pp. 31–32; R. Rahman, Intel ® Xeon Phi™ Coprocessor Architecture and Tools, (APress, 2013) p. 55.Google Scholar