Demonstrating the Scalability of a Molecular Dynamics Application on a Petaflops Computer


The IBM Blue Gene/C parallel computer aims to demonstrate the feasibility of a cellular architecture computer with millions of concurrent threads of execution. One of the major challenges in this project is showing that applications can successfully scale to this massive amount of parallelism. In this paper we demonstrate that the simulation of protein folding using classical molecular dynamics falls in this category. Starting from the sequential version of a well known molecular dynamics code, we developed a new parallel implementation that exploited the multiple levels of parallelism present in the Blue Gene/C cellular architecture. We performed both analytical and simulation studies of the behavior of this application when executed on a very large number of threads. As a result, we demonstrate that this class of applications can execute efficiently on a large cellular machine.

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  1. 1.

    T. Sterling and L. Bergman, A Design of a Hybrid Technology Multithreaded Architecture for Petaflops Scale Computation, Proc. Int'l. Conf. Supercomputing (June 1999).

  2. 2.

    F. Allen et al., Blue Gene: A Vision for Protein Science Using a Petaflop Supercomputer, IBM Syst. J., 40(2):310–328 (2001).

    Google Scholar 

  3. 3.

    The Blue Gene project,

  4. 4.

    Y. Kang, M. Huang, S.-M. Yoo, Z. Ge, D. Keen, V. Lam, P. Pattnaik, and J. Torrellas, FlexRAM: Toward an Advanced Intelligent Memory System, Int'l. Conf. Computer Design (ICCD) (October 1999).

  5. 5.

    J. Torrellas, L. Yang, and A.-T. Nguyen, Toward a Cost-Effective DSM Organization that Exploits Processor-Memory Integration, Sixth Int'l. Symp. High-Performance Computer Architecture (January 2000).

  6. 6.

    M. W. Hall, P. Kogge, J. Koller, P. Diniz, J. Chame, J. Draper, J. LaCross, J. Brockman, W. Athas, A. Srivasava, V. Freech, J. Shin, and J. Park, Mapping Irregular Applications to DIVA, A PIM-Based Data-Intensive Architecture, Proc. SC99 (November 1999).

  7. 7.

    D. Patterson, T. Anderson, N. Cardwell, R. Fromm, K. Keeton, C. Kozyrakis, R. Thomas, and K. Yelick, A Case for Intelligent RAM: IRAM, Proc. IEEE Micro (April 1997).

  8. 8.

    V. E. Taylor, R. Stevens, and K. Arnold, Parallel Molecular Dynamics: Implications for Massively Parallel Machines, J. Parallel Distribut. Comput., 45(2):166–175 (September 1997).

    Google Scholar 

  9. 9.

    P. B. Moore, CM3D CM MMD Code.'moore/code/code.html.

  10. 10.

    M. P. Allen and D. J. Tildesley, Computer Simulation of Liquids, Oxford Science Publications, Oxford, United Kingdom (1987).

    Google Scholar 

  11. 11.

    P. Ewald, Die Berechnung Optischer und Elektrostatischer Gitterpotentiale, Ann. Phys., 64: 253–287 (1921).

    Google Scholar 

  12. 12.

    S. Plimpton, Fast Parallel Algorithms for Short-range Molecular Dynamics, J. Comp.Phys., 117:1–19 (1995).

    Google Scholar 

  13. 13.

    M. E. Tuckerman and B. J. Berne, Molecular Dynamics in Systems with Multiple Time Scales, J. Comp. Chem., 95:8362–8364 (May 1992).

    Google Scholar 

  14. 14.

    M. E. Tuckerman, B. J. Berne, and G. J. Martyna, Reversible Multiple Time Scale Molecular Dynamics, J. Chem. Phys., 97:1990–2001 (1992).

    Google Scholar 

  15. 15.

    L. R. Scolnick, A. M. Clements, J. Liao, L. Crenshaw, M. Hellberg, J. May, T. R. Dean, and D. W. Christianson, Novel Binding Mode of Hydroxamate Inhibitors to Human Carbonic Anhydrase II, J. Am. Chem. Soc., 119:850–851 (1997).

    Google Scholar 

  16. 16.

    B. R. Brooks, R. E. Bruccoleri, B. D. Olafson, D. J. States, S. Swaminathan, and M. Karplus, CHARMM: A Program for Macromolecular Energy Minimization, and Dynamics Calculations, J. Comput. Chem., 4: 187–217 (1983).

    Google Scholar 

  17. 17.

    L. Verlet, Computer Experiments on Classical Fluids. I. Thermodynamical Properties of Lennard-Jones Molecules, Phys. Rev., 159: 98–103 (1967).

    Google Scholar 

  18. 18.

    A. Agarwal, Raw Computation, Sci. Amer. (August 1999).

  19. 19.

    E. Waingold, M. Taylor, D. Srikrishna, V. Sarkar, W. Lee, V. Lee, J. Kim, M. Frank, P. Finch, R. Barua, J. Babb, S. Amarasinghe, and A. Agarwal, Baring it All to Software: Raw Machines, IEEE Computer, pp. 86–93 (September 1997).

  20. 20.

    P. M. Kogge, The EXECUBE Approach to Massively Parallel Processing, Int'l. Conf.Parallel Processing (August 1994).

  21. 21.

    P. Kogge, S. Bass, J. Brockman, D. Chen, and E. Sha, Pursuing a Petaflop: Point Designs for 100 TF Computers Using PIM Technologies, Frontiers of Massively Parallel Computation Symp. (1996).

  22. 22.

    S. Rixner, W. Dally, U. Kapasi, B. Khailany, A. Lopez-Lagunas, P. Mattson, and J. Owens, A Bandwidth-Efficient Architecture for Media Processing, 31st Int'l. Symp.Microarchitecture (November 1998).

  23. 23.

    M. Oskin, F. T. Chong, and T. Sherwood, Active Pages: A Computation Model for Intelligent Memory, Int'l. Symp. Computer Architecture, pp. 192–203 (1998).

  24. 24.

    H. P. Zima and T. Sterling, The Gilgamesh Processor-In-Memory Architecture and its Execution Model, Workshop on Compilers for Parallel Computers, Edinburgh, Scotland, United Kingdom (June 2001).

    Google Scholar 

  25. 25.

    M. Tremblay, MAJC: Microprocessor Architecture for Java Computing, Presentation at Hot Chips (August 1999).

  26. 26.

    L. Barroso, K. Gharachorloo, R. McNamara, A. Nowatzyk, S. Qadeer, B. Sano, S. Smith, R. Stets, and B. Verghese, Piranha: A Scalable Architecture Based on Single-Chip Multiprocessing, 27th Ann. Int'l. Symp. Computer Architecture, pp. 282–293 (June 2000).

  27. 27.

    S. Eggers, J. Emer, H. Levy, J. Lo, R. Stamm, and D. Tullsen, Simultaneous Multithreading: A Platform for Next-generation Processors, IEEE Micro, pp. 12–18 (September 1997).

  28. 28.

    D. M. Tullsen, S. J. Eggers, and H. M. Levy, Simultaneous Multithreading: Maximizing On-Chip Parallelism, Proc. 22nd Ann. Int'l. Symp. Computer Architecture, pp. 392–403 (June 1995).

  29. 29.

    A. Snavely, L. Carter, J. Boisseau, A. Majumdar, K. S. Gatlin, N. Mitchel, J. Feo, and B. Koblenz, Multiprocessor Performance on the Tera MTA, Proc. Supercomputing, Orlando, Florida (November 7-13, 1998).

    Google Scholar 

  30. 30.

    A. Snavely, G. Johnson, and J. Genetti, Data Intensive Volume Visualization on the Tera MTA and Cray T3E, Proc. High Performance Computing Symp. (HPC), pp. 59–64 (1999).

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Almasi, G.S., Caşcaval, C., Castaños, J.G. et al. Demonstrating the Scalability of a Molecular Dynamics Application on a Petaflops Computer. International Journal of Parallel Programming 30, 317–351 (2002).

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  • Massively parallel computing
  • molecular dynamics
  • performance evaluation
  • cellular architecture