Anton, a special-purpose machine for molecular dynamics simulation

Abstract

The ability to perform long, accurate molecular dynamics (MD) simulations involving proteins and other biological macro-molecules could in principle provide answers to some of the most important currently outstanding questions in the fields of biology, chemistry, and medicine. A wide range of biologically interesting phenomena, however, occur over timescales on the order of a millisecond---several orders of magnitude beyond the duration of the longest current MD simulations.

We describe a massively parallel machine called Anton, which should be capable of executing millisecond-scale classical MD simulations of such biomolecular systems. The machine, which is scheduled for completion by the end of 2008, is based on 512 identical MD-specific ASICs that interact in a tightly coupled manner using a specialized highspeed communication network. Anton has been designed to use both novel parallel algorithms and special-purpose logic to dramatically accelerate those calculations that dominate the time required for a typical MD simulation. The remainder of the simulation algorithm is executed by a programmable portion of each chip that achieves a substantial degree of parallelism while preserving the flexibility necessary to accommodate anticipated advances in physical models and simulation methods.

References

1. Adcock, S.A. and McCammon, J.A. Molecular dynamics: Survey of methods for simulating the activity of proteins. Chemical Review, 106:1589--1615, 2006.
2. Bhatele, A., Kumar, S., Mei, C., Phillips, J.C., Zheng, G., and Kale, L.V. Overcoming scaling challenges in biomolecular simulations across multiple platforms, to appear in Proceedings of the IEEE International Parallel and Distributed Processing Symposium (IPDPS 2008), Miami, FL, 2008.
3. Bowers, K.J., Chow, E., Xu, H., Dror, R.O., Eastwood, M.P., Gregersen, B.A., Klepeis, J.L., Kolossvary, I., Moraes, M.A., Sacerdoti, F.D., Salmon, J.K., Shan, Y., and Shaw, D.E. Scalable algorithms for molecular dynamics simulations on commodity clusters. Proceedings of the ACM//IEEE Conference on Supercomputing (SC06). Tampa, FL, 2006.
4. Bowers, K.J., Dror, R.O., and Shaw, D.E. Zonal methods for the parallel execution of range-limited N-body problems. Journal of Computational Physics, 221(1):303--329, 2007.
5. Fitch, B.G., Rayshubskiy, A., Eleftheriou, M., Ward, T.J.C., Giampapa, M.E., Pitman, M.C., Pitera, J.W., Swope, W.C., and Germain, R.S. Blue matter: scaling of N-body simulations to one atom per node. IBM Journal of Research and Development, 52(1/2), 2008.
6. Fine, R.D., Dimmler, G., and Levinthal, C. FASTRUN: A special purpose, hardwired computer for molecular simulation. Proteins: Structure, Function, and Genetics, 11(4):242--253, 1991 (erratum: 14(3):421--422, 1992).
7. Germain, R.S., Fitch, B., Rayshubskiy, A., Eleftheriou, M., Pitman, M.C., Suits, F., Giampapa, M., and Ward, T.J.C. Blue matter on blue gene/L: Massively parallel computation for biomolecular simulation. Proceedings of the Third IEEE/ACM/ IFIP International Conference on Hardware/Software Codesign and System Synthesis (CODES + ISSS '05), New York, NY, 2005.
8. Hess, B., Kutzner, C., van der Spoel, D., and Lindahl, E. GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. Journal of Chemical Theory and Computation, 4(2):435--447, 2008.
9. Jorgensen, W.L., Maxwell, D.S., and Tirado-Rives, J. Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. Journal of the American Chemical Society, 118(45):11225--11236, 1996.
10. Kalé, L., Skeel, R., Bhandarkar, M., Brunner, R., Gursoy, A., Krawetz, N., Phillips, J., Shinozaki, A., Varadarajan, K., and Schulten, K., NAMD2: Greater scalability for parallel molecular dynamics. Journal of Computational Physics, 151(1):283--312, 1999.
11. Kollman, P.A., Dixon, R.W., Cornell, W.D., Fox, T., Chipot, C., and Pohorille, A. The development/ application of a "Minimalist" organic/ biomolecular mechanic forcefield using a combination of ab initio calculations and experimental data, in Computer Simulation of Biomolecular Systems: Theoretical and Experimental Applications, van Gunsteren, W.F. and Weiner, P.K. eds., Dordrecht, Netherlands:ESCOM, pp. 83--96, 1997.
12. Kuskin, J.S., Young, C., Grossman, J.P., Batson, B., Deneroff, M.M., Dror, R.O., and Shaw, D.E. Incorporating flexibility in Anton, a specialized machine for molecular dynamics simulation. Proceedings of the 14th International Symposium on HighPerformance Computer Architecture (HPCA-14), Salt Lake City, UT, 2008.
13. Larson, R.H., Salmon, J.K., Dror, R.O., Deneroff, M.M., Young. C., Grossman, J.P., Shan, Y., Klepeis, J.L., and Shaw, D.E. High-throughput pairwise point interactions in Anton, a specialized machine for molecular dynamics simulation. Proceedings of the 14th International Symposium on High-Performance Computer Architecture (HPCA-14), Salt Lake City, UT, 2008.
14. Liem, S.Y., Brown, D., and Clarke, J.H.R. Molecular dynamics simulations on distributed memory machines. Computer Physics Communications, 67(2):261--267, 1991.
15. MacKerell, A.D. Jr., Bashford, D., Bellott, M., Dunbrack, R.L., Evanseck, J.D., Field, M.J., Fischer, S., Gao, J., Guo, H., Ha, S., Joseph-McCarthy, D., Kuchnir, L., Kuczera, K., Lau, F.T.K., Mattos, C., Michnick, S., Ngo, T., Nguyen, D.T., Prodhom, B., Reiher, III, W.E., Roux, B., Schlenkrich, M., Smith, J.C., Stote, R., Straub, J., Watanabe, M., Wiórkiewicz-Kuczera, J., Yin, D., and Karplus, M.J. All-atom empirical potential for molecular modeling and dynamics studies of proteins. Journal of Physical Chemistry B, 102(18):3586--3616, 1998.
16. Pande, V.S., Baker, I., Chapman, J., Elmer, S.P., Khaliq, S., Larson, S.M., Rhee, Y.M., Shirts, M.R., Snow, C.D., Sorin, E.J., and Zagrovic, B. Atomistic protein folding simulations on the submillisecond time scale using worldwide distributed computing. Biopolymers, 68(1):91--109, 2003.
17. Plimpton, S.J., Attaway, S., Hendrickson, B., Swegle, J., Vaughan, C., and Gardner, D. Transient dynamics simulations: Parallel algorithms for contact detection and smoothed particle hydrodynamics. Proceedings of the ACM//IEEE Conference on Supercomputing (Supercomputing '96), Pittsburgh, PA, 1996.
18. Shan, Y., Klepeis, J.L., Eastwood, M.P., Dror, R.O., and Shaw, D.E. Gaussian split Ewald: A fast Ewald mesh method for molecular simulation. Journal of Chemical Physics, 122:054101, 2005.
19. Shaw, D.E. A fast, scalable method for the parallel evaluation of distance-limited pairwise particle interactions. Journal of Computational Chemistry, 26(13):1318--1328, 2005.
20. Shaw, D.E., Deneroff, M.M., Dror, R.O., Kuskin, J.S., Larson, R.H., Salmon, J.K., Young, C., Batson, B., Bowers, K.J., Chao, J.C., Eastwood, M.P., Gagliardo, J., Grossman, J.P., Ho, C.R., lerardi, D.J., Kolossváry, I., Klepeis, J.L., Layman, T., McLeavey, C., Moraes, M.A., Mueller, R., Priest, E.C., Shan, Y., Spengler, J., Theobald, M., Towles, B., and Wang, S.C., Anton, a special purpose machine for molecular dynamics simulation. Proceedings of the 34th Annual International Symposium on Computer Architecture (ISCA '07), San Diego, CA, 2007.
21. Snir, M. A Note on N-body computations with cutoffs. Theory of Computing Systems, 37:295--318, 2004.
22. Taiji, M., Narumi, T., Ohno, Y., Futatsugi, N., Suenaga, A., Takada, N., and Konagaya, A., Protein explorer: A petaflops special-purpose computer system for molecular dynamics simulations. Proceedings of the ACM/IEEE Conference on Supercomputing (SC03), Phoenix, AZ, 2003.
23. Toyoda, S., Miyagawa, H., Kitamura, K., Amisaki, T., Hashimoto, E., Ikeda, H., Kusumi, A., and Miyakawa, N. Development of MD engine: High-speed accelerator with parallel processor design for molecular dynamics simulations. Journal Computational Chemistry, 20(2): 185--199, 1999.
24. Wang, W. and Skeel, R.D. Fast evaluation of polarizableforces. Journal of Chemical Physics, 123(16):164107, 2005.
25. Zhou, R., Harder, E., Xu, H., and Berne, B.J. Efficient multiple time step method for use with Ewald and particle mesh Ewald for large biomolecular systems. Journal of Chemical Physics, 115(5): 2348--2358, 2001.

Index Terms

• Applied computing

  • Life and medical sciences

• Computer systems organization

  • Architectures

    • Parallel architectures

  • Embedded and cyber-physical systems

  • Real-time systems