Advertisement

Towards a Unified Framework for Scientific Computing

  • Peter Bastian
  • Mark Droske
  • Christian Engwer
  • Robert Klöfkorn
  • Thimo Neubauer
  • Mario Ohlberger
  • Martin Rumpf
Part of the Lecture Notes in Computational Science and Engineering book series (LNCSE, volume 40)

Summary

Most finite element, or finite volume software is built around a fixed mesh data structure. Therefore, each software package can only be used efficiently for a relatively narrow class of applications. For example, implementations supporting unstructured meshes allow the approximation of complex geometries but are in general much slower and require more memory than implementations using structured meshes. In this paper we show how a generic mesh interface can be defined such that one algorithm, e. g. a discretization scheme, works on different mesh implementations. For a cell centered finite volume scheme we show that the same algorithm runs thirty times faster on a structured mesh implementation than on an unstructured mesh and is only four times slower than a non-generic version for a structured mesh. The generic mesh interface is realized within the Distributed Unified Numerics Environment DUNE.

Keywords

Unstructured Mesh Structure Mesh Volume Scheme Abstract Interface Grid Interface 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Amira. Amira 3.0 Visualization Software. http://www.amiravis.com/, 2002.Google Scholar
  2. J. Barton and L. Nackman. Scientific and Engineering C++. Addison-Wesley, 1994.Google Scholar
  3. P. Bastian et al. UG-A flexible software toolbox for solving partial differential equations. Computing and Visualization in Science, 1:27–40, 1997.MATHCrossRefGoogle Scholar
  4. BLAST. Basic Linear Algebra Subprograms Technical (BLAST) Forum Standard. http://www.netlib.org/blas/blast-forum/, 2001.Google Scholar
  5. F. P. Brooks. The Mythical Man-Month: Essays on Software Engineering. Addison-Wesley, 1975.Google Scholar
  6. T. Geßner et al. A procedural interface for multiresolutional visualization of general numerical data. Report 28, SFB 256, Bonn, 1999.Google Scholar
  7. D. R. Musser, G. J. Derge, and A. Saini. STL Tutorial and Reference Guide. Addison-Wesley, 2001.Google Scholar
  8. A. Schmidt and K. Siebert. ALBERT — An adaptive hierarchical finite element toolbox. Preprint 06/2000 Freiburg, 2000.Google Scholar
  9. T. Veldhuizen. Techniques for scientific C++. Technical Report 542, Indiana University Computer Science, 2000. http://osl.iu.edu/~tveldhui/ papers/techniques/.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Peter Bastian
    • 1
  • Mark Droske
    • 2
  • Christian Engwer
    • 1
  • Robert Klöfkorn
    • 3
  • Thimo Neubauer
    • 1
  • Mario Ohlberger
    • 3
  • Martin Rumpf
    • 2
  1. 1.Interdisziplinäres Zentrum für Wissenschaftliches RechnenUniversität HeidelbergHeidelberg
  2. 2.Fachbereich MathematikDuisburg
  3. 3.Abteilung für Angewandte MathematikUniversität FreiburgFreiburg

Personalised recommendations