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Issue No.04 - July-Aug. (2013 vol.15)
pp: 48-56
Mingze Bai , University of Electronic Science and Technology of China
Shixin Sun , University of Electronic Science and Technology of China
Hong Tang , Chongqing University of Posts and Telecommunications
Yusheng Dou , Chongqing University of Posts and Telecommunications
Glenn V. Lo , Nicholls State University
ABSTRACT
The efficiency and scalability of early efforts to parallelize molecular dynamics calculations on shared-memory systems using OpenMP have been limited by attempts to avoid data race. Recent work has produced better performance, but involves significant revisions to the serial code. A new algorithm addresses these limitations.
INDEX TERMS
Computational modeling, Molecular computing, Heuristic algorithms, Biological system modeling, Multicore processing, Message systems,spatial decomposition, molecular dynamics, parallel computing, OpenMP, SPMD-like, single program multiple data
CITATION
Mingze Bai, Shixin Sun, Hong Tang, Yusheng Dou, Glenn V. Lo, "An SPMD-Like Algorithm for Parallelizing Molecular Dynamics Using OpenMP", Computing in Science & Engineering, vol.15, no. 4, pp. 48-56, July-Aug. 2013, doi:10.1109/MCSE.2012.66
REFERENCES
1. S. Plimpton, “Fast Parallel Algorithms for Short-Range Molecular Dynamics,” J. Computational Physics, vol. 117, no.1, 1995, pp. 1-19.
2. K.J. Bowers, R.O. Dror, and D.E. Shaw, “The Midpoint Method for Parallelization of Particle Simulations,” J. Computational Physics, vol. 124, no. 18, 2006, pp. 184109-01–184109-11.
3. R.L. Graham, “The MPI 2.2 Standard and the Emerging MPI 3 Standard,” Proc. 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface, Springer-Verlag, 2009, doi:10.1007/978-3-642-03770-2_2.
4. D. Buntinas, G. Mercier, and W. Gropp, “Implementation and Evaluation of Shared-Memory Communication and Synchronization Operations in MPICH2 Using the Nemesis Communication Subsystem,” Parallel Computing, vol. 33, no. 9, 2007, pp. 634-644.
5. K. Berlin et al., “Evaluating the Impact of Programming Language Features on the Performance of Parallel Applications on Cluster Architectures,” LNCS 2958, Springer, 2004, pp. 194-208.
6. J. Reinders, Intel Threading Building Blocks: Outfitting C++ for Multi-core Processor Parallelism, O`Reilly, 2007.
7. K.B. Tarmyshov and F. Muller-Plathe, “Parallelizing a Molecular Dynamics Algorithm on a Multiprocessor Workstation Using OpenMP,” J. Chemical Information and Modeling, vol. 45, no. 6, 2005, pp. 1943–1952.
8. S. Bai, L. Ran, and K. Lu, “Parallelization and Performance Tuning of Molecular Dynamics Code with OpenMP,” J. Central South University of Technology, vol. 13, no. 3, 2006, pp. 260-264.
9. C. Hu, Y. Liu, and J. Li, “Efficient Parallel Implementation of Molecular Dynamics with Embedded Atom Method on Multi-core Platforms,” Proc. Int'l Conf. Parallel Processing Workshops, IEEE CS, 2009, pp. 121-129.
10. G.J. Ackland, K. D'Mellow, and S.L. Daraszewicz, “The MOLDY Short-Range Molecular Dynamics Package,” Computer Physics Comm., vol. 182, no. 12, 2011, pp. 2587-2604.
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