DOI: https://doi.org/10.26089/NumMet.v16r454

Efficiency of ARM processors for classical molecular dynamics

Authors

  • V.P. Nikolskiy
  • V.V. Stegailov

Keywords:

ARM architecture
floating point operations
efficiency
molecular dynamics
Advanced RISC Machine

Abstract

Supercomputing of the exascale era is inevitably limited by power efficiency. Nowadays, different CPU architectures are considered as possible choices for these purposes. Recently, the development of ARM processors has come to the point when their floating point performance can be seriously considered for a range of scientific applications. In this paper, we present an analysis of the floating point performance of the latest ARM cores and their efficiency for the algorithms of classical molecular dynamics.

New computational technologies

Downloads

Published

2015-10-10

Issue

Vol. 16 (2015): Issue 4.

Section

Section 1. Numerical methods and applications

Author Biographies

V.P. Nikolskiy

National Research University «Higher School of Economics»
• Student

V.V. Stegailov

National Research University «Higher School of Economics»
• Professor

References

  1. V. Sadovnichy, A. Tikhonravov, Vl. Voevodin, and V. Opanasenko, “’Lomonosov’: Supercomputing at Moscow State University,” in Contemporary High Performance Computing: From Petascale toward Exascale (CRC Press, Boca Raton, 2013), pp. 283-307.
  2. V. V. Stegailov and G. E. Norman, “Challenges to the Supercomputer Development in Russia: a HPC User Perspective,” Program. Sistemy: Teoriya Prilozh. 5 (1), 111-152 (2014).
  3. J. Fitzpatrick, “An Interview with Steve Furber,” Commun. ACM 54 (5), 34-39 (2011).
  4. G. Mitra, B. Johnston, A. P. Rendell, et al., “Use of SIMD Vector Operations to Accelerate Application Code Performance on Low-Powered ARM and Intel Platforms,” in Proc. IEEE 27th Int. Symposium on Parallel and Distributed Processing Workshops and PhD Forum, Cambridge, MA, USA, May 20-24, 2013 (IEEE Press, Washington, DC, 2013), pp. 1107-1116.
  5. A. V. Yanilkin, P. A. Zhilyaev, A. Yu. Kuxin, et al, “Application of Supercomputers for the Molecular Dynamics Simulation of Processes in Condensed Matter,” Vychisl. Metody Programm. 11, 111-116 (2010).
  6. P. A. Zhilyaev and V. V. Stegailov, “Ab Initio Molecular Dynamics: Application Perspectives of Multi-CPU and Hybrid Supercomputers,” Vychisl. Metody Programm. 13, 37-45 (2012).
  7. A. Y. Kuksin, A. V. Lankin, I. V. Morozov, et al., “Predictive Modeling and Simulation of Properties and Multi-Scale Processes in Materials Science. Tasks for Exaflops-Era Supercomputers,” Program. Sistemy: Teoriya Prilozh. 5 (1), 191-244 (2014).
  8. G. E. Norman and V. V. Stegailov, “Stochastic Theory of the Classical Molecular Dynamics Method,” Mat. Model. 24 (6), 3-44 (2012) [Math. Models Comput. Simul. 5 (4), 305-333 (2013)].
  9. W. Eckhardt, A. Heinecke, R. Bader, et al., “591 TFLOPS Multi-Trillion Particles Simulation on SuperMUC,” in Lecture Notes in Computer Science (Springer, Heidelberg, 2013), Vol. 7905, pp. 1-12.
  10. S. Piana, J. L. Klepeis, and D. E. Shaw, “Assessing the Accuracy of Physical Models Used in Protein-Folding Simulations: Quantitative Evidence from Long Molecular Dynamics Simulations,” Curr. Opin. Struct. Biol. 24, 98-105 (2014).
  11. V. O. Podryga, S. V. Polyakov, and D. V. Puzyrkov, “Supercomputer Molecular Modeling of Thermodynamic Equilibrium in Gas-Metal Microsystems,” Vychisl. Metody Programm. 16, 123-138 (2015).
  12. H. J. Curnow and B. A. Wichmann, “A Synthetic Benchmark,” Comput. J. 19 (1), 43-49 (1976).
  13. D. Kozlov-Kononov, “Processor Core Cortex: Combination of High Performance and Low Power Consumption,” Elektronika, No. 8, 16-24 (2010).
  14. R. Garg, “Exploring the Floating Point Performance of Modern ARM Processors,”
    http://www.anandtech.com/show/6971/exploring-the-floating-point-performance-of-modern-arm-processors . Cited October 30, 2015.
  15. R. Garg, “RgbenchMM - Android Apps on Google Play,”
    https://play.google.com/store/apps/details?id=org.codedivine.rgbench{&}hl=en . Cited October 30, 2015.
  16. R. Garg, “Prelim Analysis of RgbenchMM,”
    http://codedivine.org/2012/09/25/prelim-analysis-rgbenchmm . Cited October 30, 2015.
  17. Swedroid - Nordens Största Android-Community.
    http://www.swedroid.se . Cited October 30, 2015.
  18. V. A. Mikheev, S. P. Izgalin, A. I. Slutskin, et al., “Preliminary Results of Evaluation Testing of the Angara High-Speed Communication Network,”
    http://2014.nscf.ru/TesisAll/1_Apparatura/05_165_SemenovAS.pdf . Cited October 30, 2015.
  19. V. V. Stegailov, N. D. Orehkov, and G. S. Smirnov, “HPC Hardware Efficiency for Quantum and Classical Molecular Dynamics,” in Lecture Notes in Computer Science (Springer, Heidelberg, 2013), Vol. 9251, pp. 469-473.
  20. G. S. Smirnov and V. V. Stegailov, “Efficiency of Classical Molecular Dynamics on HPC Hardware,” Mat. Model. 28 (2016) (in press).
  21. One-Processor Timings on the Lennard-Jones Liquid Benchmark.
    http://lammps.sandia.gov/bench/lj_one.html . Cited October 30, 2015.
  22. D. Abdurachmanov, K. Arya, J. Bendavid, et al., “Explorations of the Viability of ARM and Xeon Phi for Physics Processing,” J. Phys.: Conf. Ser. 513 (2014).
    doi 10.1088/1742-6596/513/5/052008
  23. Supermicro - Ivy Bridge Based DCO SuperServer Power {&} Cost Savings.
    http://www.supermicro.com/white_paper/white_paper_Ivy-Bridge-Power.pdf . Cited October 30, 2015.
  24. Intel Xeon E5-2600 V3 Review: Haswell-EP Redefines Fast.
    http://www.tomshardware.com/reviews/intel-xeon-e5-2600-v3-haswell-ep, 3932-9.html . Cited October 30, 2015.