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Combining Task-based Parallelism and Adaptive Mesh Refinement Techniques in Molecular Dynamics Simulations

Published: 13 August 2018 Publication History

Abstract

Modern parallel architectures require applications to generate massive parallelism so as to feed their large number of cores and their wide vector units. We revisit the extensively studied classical Molecular Dynamics N-body problem in the light of these hardware constraints. We use Adaptive Mesh Refinement techniques to store particles in memory, and to optimize the force computation loop using multi-threading and vectorization-friendly data structures. Our design is guided by the need for load balancing and adaptivity raised by highly dynamic particle sets, as typically observed in simulations of strong shocks resulting in material micro-jetting. We analyze performance results on several simulation scenarios, over nodes equipped by Intel Xeon Phi Knights Landing (KNL) or Intel Xeon Skylake (SKL) processors. Performance obtained with our OpenMP implementation outperforms state-of-the-art implementations (LAMMPS) on both steady and micro-jetting particles simulations. In the latter case, our implementation is 4.7 times faster on KNL, and 2 times faster on SKL.

References

[1]
M.P. Allen and D.J. Tildesley. 1987. Computer Simulation of Liquids. Clarendon Press.
[2]
Herman JC Berendsen, David van der Spoel, and Rudi van Drunen. 1995. GROMACS: a message-passing parallel molecular dynamics implementation. Computer Physics Communications 91, 1-3 (1995), 43--56.
[3]
M. Berger and P. Colella. 1989. Local adaptive mesh refinement for shock hydrodynamics. J. Comput. Phys. (1989).
[4]
M. Berger and J. Oliger. 1984. Adaptive mesh refinement for hyperbolic partial differential equations. J. Comput. Phys. 53 (1984).
[5]
Marsha J Berger and Shahid H Bokhari. 1987. A partitioning strategy for nonuniform problems on multiprocessors. IEEE Trans. Comput. 5 (1987), 570--580.
[6]
W Michael Brown, Jan-Michael Y Carrillo, Nitin Gavhane, Foram M Thakkar, and Steven J Plimpton. 2015. Optimizing legacy molecular dynamics software with directive-based offload. Computer Physics Communications 195 (2015), 95--101.
[7]
Greg L Bryan, Michael L Norman, Brian W O'Shea, Tom Abel, John H Wise, Matthew J Turk, Daniel R Reynolds, David C Collins, Peng Wang, Samuel W Skillman, et al. 2014. Enzo: An adaptive mesh refinement code for astrophysics. The Astrophysical Journal Supplement Series 211, 2 (2014), 19.
[8]
P Colella, DT Graves, TJ Ligocki, DF Martin, D Modiano, DB Serafini, and B Van Straalen. 2000. Chombo software package for amr applications-design document.
[9]
K Coulomb, M Faverge, J Jazeix, O Lagrasse, J Marcoueille, P Noisette, A Redondy, and C Vuchener. 2009. Visual trace explorer (vite). Technical Report. Technical report.
[10]
Jack Doweck, Wen-Fu Kao, Allen Kuan-yu Lu, Julius Mandelblat, Anirudha Rahatekar, Lihu Rappoport, Efraim Rotem, Ahmad Yasin, and Adi Yoaz. 2017. Inside 6th-Generation Intel Core: New Microarchitecture Code-Named Skylake. IEEE Micro 37, 2 (2017), 52--62.
[11]
Marie Durand, Bruno Raffin, and François Faure. 2012. A packed memory array to keep moving particles sorted. In 9th Workshop on Virtual Reality Interaction and Physical Simulation (VRIPHYS). The Eurographics Association, 69--77.
[12]
Olivier Durand, S Jaouen, L Soulard, Olivier Heuze, and Laurent Colombet. 2017. Comparative simulations of microjetting using atomistic and continuous approaches in the presence of viscosity and surface tension. Journal of Applied Physics 122, 13 (2017), 135107.
[13]
A. Dubey et al. 2014. A survey of high level frameworks in block-structured adaptive mesh refinement packages. J. Parallel Distrib. Comput.74 (2014).
[14]
Dennis Gannon, William Jalby, and Kyle Gallivan. 1988. Strategies for cache and local memory management by global program transformation. J. Parallel and Distrib. Comput. 5, 5 (1988), 587--616.
[15]
Dennis B Gannon and William Jalby. 1987. The influence of memory hierarchy on algorithm organization: Programming FFTs on a vector multiprocessor. University of Illinois at Urbana-Champaign, Center for Supercomputing Research and Development.
[16]
Michael A Heroux, Douglas W Doerfler, Paul S Crozier, James M Willenbring, H Carter Edwards, Alan Williams, Mahesh Rajan, Eric R Keiter, Heidi K Thornquist, and Robert W Numrich. 2009. Improving performance via mini-applications. Sandia National Laboratories, Tech. Rep. SAND2009-5574 3 (2009).
[17]
Changjun Hu, Xianmeng Wang, Jianjiang Li, Xinfu He, Shigang Li, Yangde Feng, Shaofeng Yang, and He Bai. 2017. Kernel optimization for short-range molecular dynamics. Computer Physics Communications 211 (2017), 31--40.
[18]
J. Reinders J. Jeffers and A. Sodani. 2016. Intel Xeon Phi Porcessor High Performance Programing. Chapter 20, 443--470.
[19]
J. E. Jones. 1924. On the Determination of Molecular Fields. II. From the Equation of State of a Gas. Proceedings of the Royal Society of London. Series A, 463--477.
[20]
Sandia National Laboratorie. {n. d.}. LAMMPS Molecular Dynamics Simulator. http://lammps.sandia.gov.
[21]
Benedict J. Leimkuhler, Sebastian Reich, and Robert D. Skeel. 1996. Integration Methods for Molecular Dynamics. In Mathematical Approaches to Biomolecular Structure and Dynamics, Jill P. Mesirov, Klaus Schulten, and De Witt Sumners (Eds.). The IMA Volumes in Mathematics and its Applications, Vol. 82. Springer New York, 161--185.
[22]
M Lijewski, A Nonaka, and J Bell. 2011. Boxlib.
[23]
Chris M Mangiardi and Ralf Meyer. 2017. A hybrid algorithm for parallel molecular dynamics simulations. Computer Physics Communications (2017).
[24]
Edward A. Mason. 1954. Transport Properties of Gases Obeying a Modified Buckingham (Exp-Six) Potential. The Journal of Chemical Physics 22, 2 (1954), 169--186.
[25]
Simone Meloni, Mario Rosati, and Luciano Colombo. 2007. Efficient particle labeling in atomistic simulations.
[26]
Ralf Meyer. 2014. Efficient parallelization of molecular dynamics simulations with short-ranged forces. In Journal of Physics: Conference Series, Vol. 540. IOP Publishing, 012006.
[27]
J Mohd-Yusof. 2012. CoDesign Molecular Dynamics (CoMD) Proxy App Deep Dive. In Exascale Research Conference.
[28]
Philip M. Morse. 1929. Diatomic Molecules According to the Wave Mechanics. II. Vibrational Levels. Phys. Rev. 34 (1929), 57--64. Issue 1.
[29]
Guy M Morton. 1966. A computer oriented geodetic data base and a new technique in file sequencing. International Business Machines Company New York.
[30]
Yehoshua Perl and Stephen R Schach. 1981. Max-min tree partitioning. Journal of the ACM (JACM) 28, 1 (1981), 5--15.
[31]
E. Cieren L. Colombet S. Pitoiset and R. Namyst. 2014. ExaStamp: A Parallel Framework for Molecular Dynamics on Heterogeneous Clusters, Lecture Notes in Computer Science (Ed.), Vol. 8806. Euro-Par 2014: Parallel Processing Workshops, Springer International Publishing, 121--132.
[32]
Steve Plimpton. 1995. Fast parallel algorithms for short-range molecular dynamics. Journal of computational physics 117, 1 (1995), 1--19.
[33]
Lewis Fry Richardson. 1911. The approximate arithmetical solution by finite differences of physical problems involving differential equations, with an application to the stresses in a masonry dam. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character 210 (1911), 307--357.
[34]
R. Meyer. 2013. Efficient parallelization of short-range molecular dynamics simulation on many-core system. PHYSICAL REVIEW (2013).
[35]
W Smith, TR Forester, and IT Todorov. 2012. The DL POLY Classic user manual. STFC, STFC Daresbury Laboratory, Daresbury, Warrington, Cheshire, WA4 4AD, United Kingdom, version 1 (2012).
[36]
Avinash Sodani. 2015. Knights landing (KNL): 2nd Generation Intel® Xeon Phi processor. In Hot Chips 27 Symposium (HCS), 2015 IEEE. IEEE, 1--24.
[37]
Loup Verlet. 1967. Computer" experiments" on classical fluids. I. Thermodynamical properties of Lennard-Jones molecules. Physical review 159, 1 (1967), 98.
[38]
D. Wolff and W. G. Rudd. 1999. Tabulated Potentials in Molecular Dynamics Simulations. Computer Physics Communications 120, 1 (1999), 20--32.

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cover image ACM Other conferences
ICPP '18: Proceedings of the 47th International Conference on Parallel Processing
August 2018
945 pages
ISBN:9781450365109
DOI:10.1145/3225058
Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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  • University of Oregon: University of Oregon

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 August 2018

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Author Tags

  1. Adaptive Mesh Refinement
  2. Molecular Dynamics
  3. Task Parallelism

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ICPP 2018

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ICPP '18 Paper Acceptance Rate 91 of 313 submissions, 29%;
Overall Acceptance Rate 91 of 313 submissions, 29%

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  • (2023)Micro-jetting: A semi-analytical model to calculate the velocity and density of the jet from a triangular grooveJournal of Applied Physics10.1063/5.0142057133:8Online publication date: 22-Feb-2023
  • (2022)A task programming implementation for the particle in cell code smileiProceedings of the Platform for Advanced Scientific Computing Conference10.1145/3539781.3539788(1-13)Online publication date: 27-Jun-2022
  • (2022)Molecular dynamics study of the impact of a solid drop on a solid targetJournal of Applied Physics10.1063/5.0083266131:13Online publication date: 1-Apr-2022
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  • (2020)Towards Data-Flow Parallelization for Adaptive Mesh Refinement Applications2020 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/CLUSTER49012.2020.00042(314-325)Online publication date: Sep-2020
  • (2020)Influence of the phase transitions of shock-loaded tin on microjetting and ejecta production using molecular dynamics simulationsJournal of Applied Physics10.1063/5.0003744127:17Online publication date: 1-May-2020
  • (2020)Observation of phase transitions in shocked tin by molecular dynamicsJournal of Applied Physics10.1063/5.0003089127:16Online publication date: 23-Apr-2020
  • (2020)Optimization of the N-Body Simulation on Intel’s Architectures Based on AVX-512 Instruction SetComputer Science – CACIC 201910.1007/978-3-030-48325-8_3(37-52)Online publication date: 14-May-2020

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