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Dynamic Optimization of Linear Solver Parameters in Mathematical Modelling of Unsteady Processes

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Supercomputing (RuSCDays 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 793))

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Abstract

The optimization of linear solver parameters in unsteady multiphase groundflow modelling is considered. Two strategies of dynamic parameters setting for the linear solver are proposed when the linear systems properties are modified during simulation in the INMOST framework. It is shown that the considered algorithms for dynamic selection of linear solver parameters provide a more efficient solution than any prescribed set of parameters. The results of numerical experiments on the INM RAS cluster are presented.

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Acknowledgements

This work has been supported in part by RFBR grant 17-01-00886, Russian Federation President Grant MK-2951.2017.1, and ExxonMobil Upstream Research Company.

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Authors and Affiliations

  1. Institute of Numerical Mathematics of the Russian Academy of Sciences, Moscow, 119333, Russia

    Dmitry Bagaev, Igor Konshin & Kirill Nikitin

  2. Lomonosov Moscow State University, Moscow, 119991, Russia

    Dmitry Bagaev

  3. Dorodnicyn Computing Centre, FRC CSC RAS, Moscow, 119333, Russia

    Igor Konshin

Authors
  1. Dmitry Bagaev
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  2. Igor Konshin
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  3. Kirill Nikitin
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Corresponding author

Correspondence to Dmitry Bagaev .

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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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Bagaev, D., Konshin, I., Nikitin, K. (2017). Dynamic Optimization of Linear Solver Parameters in Mathematical Modelling of Unsteady Processes. In: Voevodin, V., Sobolev, S. (eds) Supercomputing. RuSCDays 2017. Communications in Computer and Information Science, vol 793. Springer, Cham. https://doi.org/10.1007/978-3-319-71255-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-71255-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71254-3

  • Online ISBN: 978-3-319-71255-0

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