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GPU-Accelerated Molecular Dynamics: Energy Consumption and Performance

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Supercomputing (RuSCDays 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 687))

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Abstract

Energy consumption of hybrid systems is an actual problem of modern high-performance computing. The trade-off between power consumption and performance becomes more and more prominent. In this paper, we discuss the energy and power efficiency of two modern hybrid minicomputers Jetson TK1 and TX1. We use the Empirical Roofline Tool to obtain peak performance data and the molecular dynamics package LAMMPS as an example of a real-world benchmark. Using the precise wattmeter, we measure Jetsons power consumption profiles. The effectiveness of DVFS is examined as well. We determine the optimal GPU and DRAM frequencies that give the minimum energy-to-solution value.

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Acknowledgments

HSE and MIPT provided funds for purchasing the hardware used in this study. The work was supported by the grant No. 14-50-00124 of the Russian Science Foundation.

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Authors and Affiliations

  1. Joint Institute for High Temperatures of RAS, Moscow, Russia

    Vyacheslav Vecher, Vsevolod Nikolskii & Vladimir Stegailov

  2. Moscow Institute of Physics and Technology (State University), Dolgoprudny, Russia

    Vyacheslav Vecher

  3. National Research University Higher School of Economics, Moscow, Russia

    Vsevolod Nikolskii

Authors
  1. Vyacheslav Vecher
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  2. Vsevolod Nikolskii
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  3. Vladimir Stegailov
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Correspondence to Vyacheslav Vecher .

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Editors and Affiliations

  1. Research Computing Center (RCC), Moscow State University, Moscow, Russia

    Vladimir Voevodin

  2. Moscow State University, Moscow, Russia

    Sergey Sobolev

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Vecher, V., Nikolskii, V., Stegailov, V. (2016). GPU-Accelerated Molecular Dynamics: Energy Consumption and Performance. In: Voevodin, V., Sobolev, S. (eds) Supercomputing. RuSCDays 2016. Communications in Computer and Information Science, vol 687. Springer, Cham. https://doi.org/10.1007/978-3-319-55669-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-55669-7_7

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