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Parallelization of Large Scale Adaptive Finite Element Computations

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Parallel Processing and Applied Mathematics (PPAM 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3019))

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Abstract

The paper discusses general principles for parallelization of finite element codes and presents a model architecture for computational kernels of parallel adaptive programs. The model is based on message passing and domain decomposition. Parallel adaptivity, load balancing and multi-level (multigrid) solvers for systems of linear equations are included into the model. Numerical examples, computed using a prototype implementation of the proposed architecture, illustrate capabilities of the approach.

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Author information

Authors and Affiliations

  1. Section of Applied Mathematics, Institute of Computer Modeling, Cracow University of Technology, Warszawska 24, 31-155, Kraków, Poland

    Krzysztof Banaś

Authors
  1. Krzysztof Banaś
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Editor information

Editors and Affiliations

  1. Institute of Computational and Information Sciences, Czestochowa University of Technology,  

    Roman Wyrzykowski

  2. Computer Science Department, University of Tennessee, TN 37996-3450, Knoxville, USA

    Jack Dongarra

  3. Systems Research Institute, Polish Academy of Science, Warsaw, Poland

    Marcin Paprzycki

  4. Informatics & Mathematical Modeling, Technical University of Denmark, DK-2800, Lyngby, Denmark

    Jerzy Waśniewski

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© 2004 Springer-Verlag Berlin Heidelberg

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Banaś, K. (2004). Parallelization of Large Scale Adaptive Finite Element Computations. In: Wyrzykowski, R., Dongarra, J., Paprzycki, M., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2003. Lecture Notes in Computer Science, vol 3019. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24669-5_56

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  • DOI: https://doi.org/10.1007/978-3-540-24669-5_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21946-0

  • Online ISBN: 978-3-540-24669-5

  • eBook Packages: Springer Book Archive

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