IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v54y2000i4p269-277.html
   My bibliography  Save this article

Numerical engineering: design of PDE black-box solvers

Author

Listed:
  • Schönauer, Willi

Abstract

The design of PDE black-box solvers (for nonlinear systems of elliptic and parabolic PDEs) needs many compromises between efficiency and robustness which we call ‘Numerical Engineering’. The requirements for a black-box solver are formulated and the way how to meet them is presented, guided by many years of practical experience in the design of the program packages fidisol/cadsol, vecfem and linsol. The basic approach to the new finite difference element method (fdem) program package, an FDM on an unstructured FEM grid, is discussed. The common feature of all these methods is the error equation that allows a transparent balancing of all errors. The discretization errors are estimated from difference formulae of different consistency orders. The error balancing must include the iterative solution of the large and sparse linear systems by the linsol program package. The real challenge is the parallelization on distributed memory parallel computers which is solved by corresponding data structures with optimal communication patterns and redistribution after each grid refinement cycle.

Suggested Citation

  • Schönauer, Willi, 2000. "Numerical engineering: design of PDE black-box solvers," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 54(4), pages 269-277.
  • Handle: RePEc:eee:matcom:v:54:y:2000:i:4:p:269-277
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475400001889
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    G4 Mathematical software; Algorithm design and analysis; Efficiency; Parallel and vector implementations; Reliability and robustness;
    All these keywords.

    JEL classification:

    • G4 - Financial Economics - - Behavioral Finance

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:matcom:v:54:y:2000:i:4:p:269-277. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.