Hostname: page-component-848d4c4894-pftt2 Total loading time: 0 Render date: 2024-05-12T14:42:13.926Z Has data issue: false hasContentIssue false
  • English
  • Français

Parallel Algorithms for Molecular-Dynamics Simulations of Coulombic Systems

Published online by Cambridge University Press:  01 January 1992

Wei Li ,
Rajiv K. Kalia ,
Simon De Leeuw ,
Aiichiro Nakano ,
Donald Greenwell  and
Priya Vashishta
Wei Li
Affiliation:
Concurrent Computing Laboratory for Material Simulations, Department of Physics & Astronomy, and Department of Computer Science, Louisiana State University, Baton Rouge, LA 70803
Rajiv K. Kalia
Affiliation:
Concurrent Computing Laboratory for Material Simulations, Department of Physics & Astronomy, and Department of Computer Science, Louisiana State University, Baton Rouge, LA 70803
Simon De Leeuw
Affiliation:
Concurrent Computing Laboratory for Material Simulations, Department of Physics & Astronomy, and Department of Computer Science, Louisiana State University, Baton Rouge, LA 70803
Aiichiro Nakano
Affiliation:
Concurrent Computing Laboratory for Material Simulations, Department of Physics & Astronomy, and Department of Computer Science, Louisiana State University, Baton Rouge, LA 70803
Donald Greenwell
Affiliation:
Concurrent Computing Laboratory for Material Simulations, Department of Physics & Astronomy, and Department of Computer Science, Louisiana State University, Baton Rouge, LA 70803
Priya Vashishta
Affiliation:
Concurrent Computing Laboratory for Material Simulations, Department of Physics & Astronomy, and Department of Computer Science, Louisiana State University, Baton Rouge, LA 70803
Get access

Abstract

In molecular-dynamics simulations for the long-range Coulomb interaction, a great deal of effort is devoted to reducing the computational complexity of the usual N2 operations in the direct calculation. For bulk systems, we have designed a parallel algorithm based on the domain-decomposition strategy for the Ewald summation. The performance of the algorithm is evaluated on the in-house iPSC/860 system. We find that this algorithm reduces the computational complexity to O(N). For a 64,000-particle plasma in three dimension, the execution time on an 8-node system is 27.4 sec per MD time step. The interprocessor communication is a small fraction of the total execution time. We find linear speedups and a parallel efficiency of 0.85. For comparison, parallel algorithms are also designed for the Fast Multipole Method (FMM) - a divide and conquer scheme in which the system is divided into cubic subdomains and interactions between distant charged regions are calculated with a truncated multipole expansion. The performance of the FMM on Touchstone Delta machine is discussed.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 291: Symposium O – Materials Theory and Modeling , 1992 , 267
Copyright
Copyright © Materials Research Society 1993

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

1. Allen, M.P. and Tildesley, DJ.,Computer Simulation of Liquids,Clarendon Press,Oxford,1987.Google Scholar
2. de Leeuw, S.W., Perram, J. W., and Smith, E. R.,Proc. R. Soc. London, A373 (1980) 27.Google Scholar
3. Appel, A. W.,SIAM J. Sci. Stat. Comput. 6, (1985) 85.Google Scholar
4. Barnes, J. and Hut, P.,Nature, 324, No.4, (1986) 446.Google Scholar
5. Fox, G. C., Hipes, P. and Salmon, J.,Proceedings of Supercomputing '89,(1989) 58.Google Scholar
6. Pfalzner, S. and Gibbon, P., Computer Physics Communication,(1992), in press.Google Scholar
7. Warren, Michael and Salmon, John, CSCC Updata, 13, No.3, (1992) 1.Google Scholar
8. Greengard, L., The Rapid Evaluations of Potential Fields in Particle Systems, ACM 1987 Distinguished Dissertation, The MIT Press Google Scholar
9. Greengard, L. and Rokhlin, V., J. of Computatioal Physics, 73, (1987) 325.Google Scholar
10. Greengard, L. and Gropp, W. D., Parallel Processing for Scientific Computing, Rodrigue, G.Ed., SIAM (1989)Google Scholar
11. Greengard, L., Computers in Physics, Mar/Apr, (1990) 142.Google Scholar
12. Schmidt, K.E. and Lee, M. A., J. of Statistical Physics, 63, 1223, (1991)Google Scholar
13. Zhao, F. and Johnsson, S. L., SIAM J. Sci. Stat. Comput.,12, No.6, (1991) 1420.Google Scholar
14. Kalia, R. K., de Leeuw, S. W., Nakano, A., and Vashishta, P., SIAM J. Sci. Stat. Comput.(1992) in press.Google Scholar