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High Performance Computing and Numerical Modelling

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Star Formation in Galaxy Evolution: Connecting Numerical Models to Reality

Part of the book series: Saas-Fee Advanced Course ((SAASFEE,volume 43))

Abstract

Numerical methods play an ever more important role in astrophysics.

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Notes

  1. 1.

    A linear system of first-order PDEs can be written in the generic form

    figure a

    where \(A_{ij}\) is the coefficient matrix.

  2. 2.

    Named after the enigmatic word AREPO in the Latin palindromic sentence sator arepo tenet opera rotas, the ‘Sator Square’.

  3. 3.

    https://computing.llnl.gov/tutorials/openMP.

  4. 4.

    We note that normally one would of course not hard-code the rank numbers like this, but rather design the communication such that the program can run with different numbers of MPI tasks.

  5. 5.

    For example: https://computing.llnl.gov/tutorials/mpi.

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Authors and Affiliations

  1. ZAH, ARI, Heidelberg University, Heidelberg, Germany

    Volker Springel

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  1. Volker Springel
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Correspondence to Volker Springel .

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Editors and Affiliations

  1. Laboratoire d’astrophysique, École Polytechnique Fédérale de Lausanne (EPFL) Observatoire de Sauverny, Sauverny, Switzerland

    Yves Revaz

  2. École Polytechnique Fédérale de Lausanne Laboratoire d’astrophysique, Observatoire de Sauverny, Versoix, Switzerland

    Pascale Jablonka

  3. Center for Theoretical Astrophysics and Cosmology Institute for Computational Science, University of Zurich, Zurich, Switzerland

    Romain Teyssier

  4. Center for Theoretical Astrophysics and Cosmology Institute for Computational Science, University of Zurich, Zurich, Switzerland

    Lucio Mayer

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Springel, V. (2016). High Performance Computing and Numerical Modelling. In: Revaz, Y., Jablonka, P., Teyssier, R., Mayer, L. (eds) Star Formation in Galaxy Evolution: Connecting Numerical Models to Reality. Saas-Fee Advanced Course, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47890-5_3

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