Abstract
The rapidly improving compute capability of contemporary processors and accelerators is providing the opportunity for significant increases in the accuracy and fidelity of scientific calculations. In this paper we present performance studies of a new molecular dynamics (MD) potential called SNAP.
The SNAP potential has shown great promise in accurately reproducing physics and chemistry not described by simpler potentials. We have developed new algorithms to exploit high single-node concurrency provided by three different classes of machine: the Titan GPU-based system operated by Oak Ridge National Laboratory, the combined Sequoia and Vulcan BlueGene/Q machines located at Lawrence Livermore National Laboratory, and the large-scale Intel Sandy Bridge system, Chama, located at Sandia.
Our analysis focuses on strong scaling experiments with approximately 246,000 atoms over the range 1 −122,880 nodes on Sequoia/Vulcan and 40 −18,630 nodes on Titan. We compare these machine in terms of both simulation rate and power efficiency. We find that node performance correlates with power consumption across the range of machines, except for the case of extreme strong scaling, where more powerful compute nodes show greater efficiency.
This study is a unique assessment of a challenging, scientifically relevant calculation running on several of the world’s leading contemporary production supercomputing platforms.
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References
TOP500 Supercomputer Site, http://www.top500.org
Bartok, A.P., Payne, M.C., Risi, K., Csanyi, G.: Gaussian Approximation Potentials: the Accuracy of Quantum Mechanics, without the Electrons. Physical Review Letters 104, 136403 (2010)
Glosli, J.N., Richards, D.F., Caspersen, K.J., Rudd, R.E., Gunnels, J.A., Streitz, F.H.: Extending Stability Beyond CPU Millennium: A Micron-scale Atomistic Simulation of Kelvin-Helmholtz Instability. In: Proceedings of the 2007 ACM/IEEE Conference on Supercomputing, SC 2007, pp. 58:1–58:11. ACM, New York (2007)
Goedecker, G.: Linear Scaling Electronic Structure Methods. Rev. Mod. Phys. 71, 1085 (1999)
Griebel, M., Knapek, S., Zumbusch, G.: Numerical Simulation in Molecular Dynamics. Springer, Heidelberg (2007)
Hamada, T., Narumi, T., Yokota, R., Yasuoka, K., Nitadori, K., Taiji, M.: 42 TFlops Hierarchical N-body Simulations on GPUs with Applications in Both Astrophysics and Turbulence. In: Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis, SC 2009, pp. 62:1–62:12. ACM, New York (2009)
Kadau, K., Germann, T.C., Lomdahl, P.S.: Molecular Dynamics Comes of Age: 320 Billion Atom Simulation on BlueGene/L. International Journal of Modern Physics C 17(12), 1755–1761 (2006)
LAMMPS. LAMMPS molecular dynamics package WWW site, lammps.sandia.gov , Potential benchmarks, lammps.sandia.gov/bench.html
Mattsson, A.E., Schultz, P.A., Desjarlais, M.P., Mattsson, T.R., Leung, K.: Designing Meaningful Density Functional Theory Calculations in Material Science–A Primer. Modelling Simul. Mater. Sci. Eng. 31, R1–R31 (2005)
Plimpton, S.: Fast Parallel Algorithms For Sort-Range Molecular-Dynamics. J. Comput. Phys. 117(1), 1–19 (1995)
Swaminarayan, S., Germann, T.C., Kadau, K., Fossum, G.C.: 369 Tflop/s Molecular Dynamics Simulations on the Roadrunner General-Purpose Heterogeneous Supercomputer, pp. 1–10 (November 2008)
Thompson, A.P., Swiler, L.P., Trott, C.R., Foiles, S.M., Tucker, G.: A new Quantum-Accurate Interatomic Potential for Tantalum (2014) (in preparation)
Wang, L.-W., Lee, B., Shan, H., Zhao, Z., Meza, J., Strohmaier, E., Bailey, D.H.: Linearly scaling 3d fragment method for large-scale electronic structure calculations. In: Proceedings of the 2008 ACM/IEEE Conference on Supercomputing. SC 2008, pp. 65:1–65:10. IEEE Press, Piscataway (2008)
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Trott, C.R., Hammond, S.D., Thompson, A.P. (2014). SNAP: Strong Scaling High Fidelity Molecular Dynamics Simulations on Leadership-Class Computing Platforms. In: Kunkel, J.M., Ludwig, T., Meuer, H.W. (eds) Supercomputing. ISC 2014. Lecture Notes in Computer Science, vol 8488. Springer, Cham. https://doi.org/10.1007/978-3-319-07518-1_2
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DOI: https://doi.org/10.1007/978-3-319-07518-1_2
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