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Transparent Model-Driven Provisioning of Computing Resources for Numerically Intensive Simulations

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Simulation Science (SimScience 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 889))

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Abstract

Many simulations require large amounts of computing power to be executed. Traditionally, the computing power is provided by large high performance computing clusters that are solely built for this purpose. However, modern data centers do not only provide access to these high performance computing systems, but also offer other types of computing resources e.g., cloud systems, grid systems, or access to specialized computing resources, such as clusters equipped with accelerator hardware. Hence, the researcher is confronted with the choice of picking a suitable computing resource type for his simulation and acquiring the knowledge on how to access and manage his simulation on the resource type of choice. This is a time consuming and cumbersome process and could greatly benefit from supportive tooling. In this paper, we introduce a framework that allows to describe the simulation application in a resource-independent manner. It furthermore helps to select a suitable resource type according to the requirements of the simulation application and to automatically provision the required computing resources. We demonstrate the feasibility of the approach by providing a case study from the area of fluid mechanics.

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Notes

  1. 1.

    At the time of this writing, two versions of the TOSCA standard exist, a formalized version [12] in XML and a simplified rendering in YAML [13]. GroupTemplates and GroupTypes are currently part of the TOSCA YAML rendering, but not part of the TOSCA XML specification.

  2. 2.

    https://www.ansible.com/.

  3. 3.

    http://cloudify.co.

  4. 4.

    http://www.openstack.org.

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Acknowledgements

We thank the Simulationswissenschaftliches Zentrum Clausthal-Göttingen (SWZ) for financial support.

Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Goettingen, 37077, Goettingen, Germany

    Fabian Korte & Jens Grabowski

  2. Institute of Applied Mechanics, Clausthal University of Technology, 38678, Clausthal-Zellerfeld, Germany

    Alexander Bufe & Gunther Brenner

  3. Gesellschaft fuer wissenschaftliche Datenverarbeitung mbH Goettingen (GWDG), 37077, Goettingen, Germany

    Christian Köhler & Philipp Wieder

Authors
  1. Fabian Korte
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  2. Alexander Bufe
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  3. Christian Köhler
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  4. Gunther Brenner
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  5. Jens Grabowski
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  6. Philipp Wieder
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Corresponding author

Correspondence to Fabian Korte .

Editor information

Editors and Affiliations

  1. Institute of Computer Science, University of Göttingen, Göttingen, Lower Saxony, Germany

    Marcus Baum

  2. Institute of Applied Mechanics, TU Clausthal, Clausthal-Zellerfeld, Lower Saxony, Germany

    Gunther Brenner

  3. Institute of Computer Science, Universität Göttingen, Göttingen, Lower Saxony, Germany

    Jens Grabowski

  4. Institute of Applied Stochastics and Operations Research, TU Clausthal, Clausthal-Zellerfeld, Lower Saxony, Germany

    Thomas Hanschke

  5. Institute of Applied Mechanics, TU Clausthal, Clausthal-Zellerfeld, Lower Saxony, Germany

    Stefan Hartmann

  6. Institute for Numerical and Applied Mathematics, Universität Göttingen, Göttingen, Lower Saxony, Germany

    Anita Schöbel

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Korte, F., Bufe, A., Köhler, C., Brenner, G., Grabowski, J., Wieder, P. (2018). Transparent Model-Driven Provisioning of Computing Resources for Numerically Intensive Simulations. In: Baum, M., Brenner, G., Grabowski, J., Hanschke, T., Hartmann, S., Schöbel, A. (eds) Simulation Science. SimScience 2017. Communications in Computer and Information Science, vol 889. Springer, Cham. https://doi.org/10.1007/978-3-319-96271-9_11

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  • DOI: https://doi.org/10.1007/978-3-319-96271-9_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96270-2

  • Online ISBN: 978-3-319-96271-9

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