OpenAtom: Scalable Ab-Initio Molecular Dynamics with Diverse Capabilities

  • Nikhil Jain
  • Eric Bohm
  • Eric Mikida
  • Subhasish Mandal
  • Minjung Kim
  • Prateek Jindal
  • Qi Li
  • Sohrab Ismail-Beigi
  • Glenn J. Martyna
  • Laxmikant V. Kale
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9697)

Abstract

The complex interplay of tightly coupled, but disparate, computation and communication operations poses several challenges for simulating atomic scale dynamics on multi-petaflops architectures. OpenAtom addresses these challenges by exploiting overdecomposition and asynchrony in Charm++, and scales to thousands of cores for realistic scientific systems with only a few hundred atoms. At the same time, it supports several interesting ab-initio molecular dynamics simulation methods including the Car-Parrinello method, Born-Oppenheimer method, k-points, parallel tempering, and path integrals. This paper showcases the diverse functionalities as well as scalability of OpenAtom via performance case studies, with focus on the recent additions and improvements to OpenAtom. In particular, we study a metal organic framework (MOF) that consists of 424 atoms and is being explored as a candidate for a hydrogen storage material. Simulations of this system are scaled to large core counts on Cray XE6 and IBM Blue Gene/Q systems, and time per step as low as \(1.7\,s\) is demonstrated for simulating path integrals with 32-beads of MOF on 262,144 cores of Blue Gene/Q.

References

  1. 1.
    Acun, B., Gupta, A., Jain, N., Langer, A., Menon, H., Mikida, E., Ni, X., Robson, M., Sun, Y., Totoni, E., Wesolowski, L., Kale, L.: Parallel programming with migratable objects: Charm++ in practice. In: SC (2014)Google Scholar
  2. 2.
    Agarwal, T., Sharma, A., Kalé, L.V.: Topology-aware task mapping for reducing communication contention on large parallel machines. In: Proceedings of IEEE International Parallel and Distributed Processing Symposium 2006, April 2006Google Scholar
  3. 3.
    Alam, S., Bekas, C., Boettiger, H., Curioni, A., Fourestey, G., Homberg, W., Knobloch, M., Laino, T., Maurer, T., Mohr, B., Pleiter, D., Schiller, A., Schulthess, T., Weber, V.: Early experiences with scientific applications on the IBM Blue Gene/Q supercomputer. IBM J. Res. Dev. 57(1/2), 14:1–14:9 (2013). doi:10.1147/JRD.2012.2234331 CrossRefGoogle Scholar
  4. 4.
    Bhatele, A.: Automating topology aware mapping for supercomputers. Ph.D. thesis, Department of Computer Science, University of Illinois, August 2010. http://hdl.handle.net/2142/16578
  5. 5.
    Bhatele, A., Bohm, E., Kale, L.V.: Optimizing communication for Charm++ applications by reducing network contention. Concurr. Computat.: Pract. Exp. 23(2), 211–222 (2011)CrossRefGoogle Scholar
  6. 6.
    Bohm, E., Bhatele, A., Kale, L.V., Tuckerman, M.E., Kumar, S., Gunnels, J.A., Martyna, G.J.: Fine grained parallelization of the Car-Parrinello ab initio MD method on Blue Gene/L. IBM J. Res. Dev.: Appl. Massively Parallel Syst. 52(1/2), 159–174 (2008)CrossRefGoogle Scholar
  7. 7.
    Car, R., Parrinello, M.: Unified approach for molecular dynamics and density functional theory. Phys. Rev. Lett. 55(22), 2471 (1985)CrossRefGoogle Scholar
  8. 8.
    Carloni, P., Bloechl, P., Parrinello, M.: Electronic structure of the Cu, Zn superoxide dimutase active site and its interactions with the substrate. J. Phys. Chem. 99, 1338–1348 (1995)CrossRefGoogle Scholar
  9. 9.
  10. 10.
    Earl, D.J., Deem, M.: Parallel tempering: theory, applications, and new perspectives. Phys. Chem. Chem. Phys. 7, 3910–3916 (2005)CrossRefGoogle Scholar
  11. 11.
    Brugé, F., Bernasconi, M., Michele, P.: Ab initio simulation of rotational dynamics of solvated ammonium ion in water. J. Am. Chem. Soc. 121, 10883–10888 (1999)CrossRefGoogle Scholar
  12. 12.
    Fitch, B.G., Rayshubskiy, A., Eleftheriou, M., Ward, T.J.C., Giampapa, M., Pitman, M.C.: Blue matter: approaching the limits of concurrency for classical molecular dynamics. In: SC 2006: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing. ACM, New York (2006)Google Scholar
  13. 13.
    Gygi, F., Draeger, E.W., Schulz, M., de Supinski, B.R., Gunnels, J.A., Austel, V., Sexton, J.C., Franchetti, F., Kral, S., Ueberhuber, C.W., Lorenz, J.: Large-scale electronic structure calculations of high-Z metals on the BlueGene/L platform. In: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing, SC 2006. ACM, New York (2006). http://doi.acm.org/10.1145/1188455.1188502
  14. 14.
    Gygi, F., Draeger, E.W., Schulz, M., Supinski, B.R.D., Gunnels, J.A., Austel, V., Sexton, J.C., Franchetti, F., Kral, S., Ueberhuber, C., Lorenz, J.: Large-scale electronic structure calculations of high-Z metals on the Blue Gene/L platform. In: Proceedings of the International Conference in Supercomputing. ACM Press (2006)Google Scholar
  15. 15.
    Hoefler, T., Snir, M.: Generic topology mapping strategies for large-scale parallel architectures. In: Proceedings of the International Conference on Supercomputing, ICS 2011, pp. 75–84. ACM, New York (2011)Google Scholar
  16. 16.
    IBM Blue Gene Team: Overview of the IBM Blue Gene/P project. IBM J. Res. Dev. 52(1/2) (2008)Google Scholar
  17. 17.
    Kale, L.V., Zheng, G., Lee, C.W., Kumar, S.: Scaling applications to massively parallel machines using projections performance analysis tool. Future Gener. Comput. Syst. Spec. Issue: Large-Scale Syst. Perform. Model. Anal. 22, 347–358 (2006)CrossRefGoogle Scholar
  18. 18.
    Kumar, S., Shi, Y., Bohm, E., Kale, L.V.: Scalable, fine grain, parallelization of the Car-Parrinello ab initio molecular dynamics method. Technical report, UIUC, Department of Computer Science (2005)Google Scholar
  19. 19.
    Lee, H.S., Tuckerman, M., Martyna, G.: Efficient evaluation of nonlocal pseudopotentials via Euler exponential spline interpolation. Chem. Phys. Chem. 6, 1827–1835 (2005)Google Scholar
  20. 20.
    Marx, D., Parrinello, M.: Ab initio path integral molecular dynamics. Z. Phys. B 95, 143–144 (1994)CrossRefGoogle Scholar
  21. 21.
    Payne, M.C., Teter, M.P., Allan, D.C., Arias, T.A., Joannopoulos, J.D.: Iterative minimization techniques for ab initio total-energy calculations: molecular dynamics and conjugate gradients. Rev. Mod. Phys. 64, 1045 (1992)CrossRefGoogle Scholar
  22. 22.
    Rosi, N.L., Eckert, J., Eddaoudi, M., Vodak, D.T., Kim, J., O’Keeffe, M., Yaghi, O.M.: Hydrogen storage in microporous metal-organic frameworks. Science 300(5622), 1127–1129 (2003). http://www.sciencemag.org/content/300/5622/1127.abstract CrossRefGoogle Scholar
  23. 23.
    Vadali, R.V., Shi, Y., Kumar, S., Kale, L.V., Tuckerman, M.E., Martyna, G.J.: Scalable fine-grained parallelization of plane-wave-based ab initio molecular dynamics for large supercomputers. J. Compt. Chem. 25(16), 2006–2022 (2004)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Nikhil Jain
    • 1
  • Eric Bohm
    • 1
  • Eric Mikida
    • 1
  • Subhasish Mandal
    • 2
  • Minjung Kim
    • 2
  • Prateek Jindal
    • 1
  • Qi Li
    • 3
  • Sohrab Ismail-Beigi
    • 2
  • Glenn J. Martyna
    • 3
  • Laxmikant V. Kale
    • 1
  1. 1.Department of Computer ScienceUniversity of Illinois at Urbana-ChampaignChampaignUSA
  2. 2.Department of Applied PhysicsYale UniversityNew HavenUSA
  3. 3.IBM TJ Watson LaboratoryYorktown HeightsUSA

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