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High Performance Computing in Science and Engineering '20 pp 513–525Cite as

Project Report on “Load-Balancing for Large-Scale Soot Particle Agglomeration Simulations” (Reprint)

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Abstract

In this reporting period, we have combined several previous efforts to simulate a large-scale soot particle agglomeration with a dynamic, multi-scale turbulent background flow field. We have built upon previous simulations which include 3.2 million particles and have implemented load-balancing within a versatile simulation software. We have furthermore contributed tests of the load-balancing mechanisms for the agglomeration scenario. We have significantly increased the simulation to 109.85 million particles, superposing short-ranged MD with a dynamically changing multi-scale background flow field. Based on extensive software enhancements for the molecular dynamics software ESPResSo, we have started simulating on the Cray XC40 at HLRS. To verify that our setup reproduces essential physics, we have evaluated load-balancing for a scenario, for which we have scaled down the influence of the flow field to make the scenario mostly homogeneous on the subdomain scale. Finally, we have shown that load-balancing still pays off even for the homogenized version of our dynamic soot particle agglomeration scenario. Reprinted from Publication Advances in Parallel Computing, Volume 36: Parallel Computing: Technology Trends, Steffen Hirschmann, Andreas Kronenburg, Colin W. Glass, Dirk Pflüger, “Load-Balancing for Large-Scale Soot Particle Agglomeration Simulations”, pages 147–156, Copyright 2020, with permission from IOS Press [1]. The publication is available at IOS Press through  http://dx.doi.org/10.3233/APC200035.

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Notes

  1. 1.

    Extensible Simulation Package for Research on Soft Matter, http://www.espressomd.org.

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Acknowledgements

The authors gratefully acknowledge financial support provided by the German Research Foundation (DFG) as part of the former Collaborative Research Center (SFB) 716, and the computing time on “Hazel Hen” granted by the High Performance Computing Center Stuttgart (HLRS). Special thanks go to Rudolf Weeber from the ICP, University of Stuttgart, for his expertise and fruitful discussions.

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Authors and Affiliations

  1. Institute for Parallel and Distributed Systems, University of Stuttgart, Universitätsstraße 38, Stuttgart, 70569, Germany

    Steffen Hirschmann & Dirk Pflüger

  2. Institute for Combustion Technology, University of Stuttgart, Herdweg 51, Stuttgart, 70174, Germany

    Andreas Kronenburg

  3. Department of Mechanical Engineering, Helmut Schmidt University Hamburg, Holstenhofweg 85, 22043, Hamburg, Germany

    Colin W. Glass

Authors
  1. Steffen Hirschmann
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  2. Andreas Kronenburg
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  3. Colin W. Glass
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  4. Dirk Pflüger
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Corresponding author

Correspondence to Steffen Hirschmann .

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Editors and Affiliations

  1. Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH), Technische Universität Dresden, Dresden, Germany

    Wolfgang E. Nagel

  2. Abteilung für Angewandte Mathematik, Universität Freiburg, Freiburg, Germany

    Dietmar H. Kröner

  3. Höchstleistungsrechenzentrum Stuttgart (HLRS), Universität Stuttgart, Stuttgart, Germany

    Michael M. Resch

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Hirschmann, S., Kronenburg, A., Glass, C.W., Pflüger, D. (2021). Project Report on “Load-Balancing for Large-Scale Soot Particle Agglomeration Simulations” (Reprint). In: Nagel, W.E., Kröner, D.H., Resch, M.M. (eds) High Performance Computing in Science and Engineering '20. Springer, Cham. https://doi.org/10.1007/978-3-030-80602-6_34

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