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Dynamic domain decomposition and load balancing for parallel simulations of long-chained molecules

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1041))

Abstract

It is clear that the use of parallelism for scientific computing will increase in the future as it is the only method available to tackle large scale problems. However, employing parallel methods to produce viable scientific tools brings about its own inherent problems which are not present in sequential implementations. Primary among these are problems in selecting the parallelisation method to be used, and inefficiencies brought about by load imbalance. In this paper we look at both these issues when applied to simulations of long-chained molecules. We introduce a decomposition scheme, dynamic domain decomposition (DDD), which parallelises a molecular simulation using geometrical information, and when combined with a migration function leads to reduced communications. We present a load balancing algorithm, positional scan load balancing (PSLB), which equalises processor work load to increase the efficiency, and present some experimental results.

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References

  1. A. Baumgartner. Statics and dynamics of the freely jointed polymer chain with lennard-jones interaction. Journal of Chemical Physics, 72(2):871–879, Jan. 1980.

    Google Scholar 

  2. E.S. Biagioni. Scan Directed Load Balancing. PhD thesis, University of North Carolina at Chapel Hill, 1991.

    Google Scholar 

  3. T. Blank. The MasPar MP-1 Architecture. In Proceedings of CompCon, 35th IEEE Computer Society International Meeting, pages 20–24. IEEE, Computer Society Press, February 1990.

    Google Scholar 

  4. G.E. Blelloch. Scans as primitive parallel operations. IEEE Transactions on Computers, 38, November 1989.

    Google Scholar 

  5. A. Byrne, P. Kiernan, and K.A. Dawson. Kinetics of homopolymer collapse. Journal of Chemical Physics, 102:573–577, January 1995.

    Google Scholar 

  6. W.J. Camp, S.J. Plimpton, B.A. Hendrickson, and R.W. Leland. Massivelly Parallel Methods for Engineering and Science Problems. Communication of the ACM, 37(4):31–41, April 1994.

    Google Scholar 

  7. C. Che Chen, J.P. Singh, W.B. Poland, and R.B. Altman. Parallel Protein Structure Determination from Uncertain Data. In Proceedings of Supercomputing'94

    Google Scholar 

  8. P. Christy. Software to Support Massively Parallel Computing on the MasPar MP-1. In Proceedings of CompCon, 35th IEEE International Computer Society Meeting, pages 29–33. IEEE, Computer Society Press, Febrary 1990.

    Google Scholar 

  9. E.A. Colbourn. Computer Simulation of Polymers. Longman Scientific Technical, 1994.

    Google Scholar 

  10. M. Furuichi, K. Taki, and N. Ichiyoshi. A Multi-level Load Balancing Scheme for OR-Parallel Exhaustive Search Programs on the Multi-PSI. In Proceedings of the 2nd ACM SIGPLAN Symposium on Priciples and Practice of Parallel Programming, pages 50–59, 1990.

    Google Scholar 

  11. G. Karypis and V. Kumar. Unstructured Tree Search on SIMD Parallel Computers. Technical Report 92-21, Department of Computer Science, University of Minnesota Minneapolis, MN 55455, April 1992.

    Google Scholar 

  12. T. Kechadi, A. Moskalenko, D.F. Hegarty, and K.A. Dawson. On the Optimal Solution for Connected Graph partitioning. Technical Report TR-9504, Advanced Computational Research Group, University College Dublin, Ireland, July 1995.

    Google Scholar 

  13. B.W. Kernighan and S. Lin. An Efficient Heuristic Procedure for Partitioning Graphs. Bell Systems Technical Journal, 49:291–306, February 1970.

    Google Scholar 

  14. D. E. Keyes and W. D. Gropp. A Comparison of Domain Decomposition Techniques for Elliptic Partial Differential Equations and their Parallel Implementation. SIAM Journal of Scientific and Statistical Computing, 8:166–202, March 1987.

    Google Scholar 

  15. V. Kumar and A. Gupta. Analyzing Scalability of Parallel Algorithms and Architectures. In Proceedings of the International Conference on Supercomputing, Germany, 1991.

    Google Scholar 

  16. M.H. Willebeek-Le Mair and A.P. Reeves. Strategies for Dynamic Load Balancing on Highly Parallel Computers. IEEE Transactions on Parallel and Distributed Systems, 4(9), September 1993.

    Google Scholar 

  17. J. Mazur and F.L. McCrackin. Monte Carlo Studies of Configurational and Thermodynamic Properties of Self-Interacting Linear Polymer Chains. The Journal of Chemical Physics, 49:648–665, July 1968.

    Google Scholar 

  18. B. Ostrovsky, M.A. Smith, and Y. Bar-Yam. Applications of Parallel Computing to Biological Problems. Annual Reviews of Biophysics and Biomolecular Structure, 1995.

    Google Scholar 

  19. S. Patil and P. Banerjee. A Parallel Branch and Bound Algorithm for Test Generation. IEEE Transactions on Computer Aided Design, 9(9), March 1990.

    Google Scholar 

  20. A. Pothen, H. Simon, and K.P. Liou. Partitioning Sparse Matrices with eigenvectors of graphs. SIAM J. Mat. Anal. Appl., 11:430–452, 1990.

    Google Scholar 

  21. W. Shu and L.V. kale. A Dynamic Scheduling Strategy for the Chare-kernel System. In Proceedings of Supercomputing'89, pages 389–398, 1989.

    Google Scholar 

  22. B.W. Wah and Y.W. Eva Ma. MANIP — A Multicomputer Architecture for Solving Combinatorial Extremum-Search Problems. IEEE Transactions on Computers, C-33(5), May 1984.

    Google Scholar 

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Jack Dongarra Kaj Madsen Jerzy Waśniewski

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© 1996 Springer-Verlag Berlin Heidelberg

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Hegarty, D.F., Kechadi, M.T., Dawson, K.A. (1996). Dynamic domain decomposition and load balancing for parallel simulations of long-chained molecules. In: Dongarra, J., Madsen, K., Waśniewski, J. (eds) Applied Parallel Computing Computations in Physics, Chemistry and Engineering Science. PARA 1995. Lecture Notes in Computer Science, vol 1041. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60902-4_33

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  • DOI: https://doi.org/10.1007/3-540-60902-4_33

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60902-5

  • Online ISBN: 978-3-540-49670-0

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