Cluster Computation for Flood Simulations1

  • Ladislav Hluchy
  • Giang T. Nguyen
  • Ladislav Halada
  • Viet D. Tran
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2110)


Simulation of the water flood problems often leads to solving of large sparse systems of partial differential equations. For such systems, the numerical method is very CPU-time consuming. Therefore, the parallel simulation is essential for water flood study with satisfactory accuracy. In this paper, we present some experimental results of parallel numerical solutions done on Linux clusters. Our measurements indicate that Linux cluster can provide satisfactory power for parallel numerical solutions, especially for large problems. We also provide experimental results done on a SGI Origin2000 machine for comparison with Linux clusters.


Partial Differential Equation Algorithm Analysis Large Problem Water Flood System Implementation 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    FLDWAV: 1D flood wave simulation program
  2. 2.
    Mike21: 2D engineering modeling tool for rivers, estuaries and coastal waters
  3. 3.
    SMS: 2D surface water modeling package
  4. 4.
    Tran V.D., Hluchy L., Nguyen G.T.: Parallel Program Model and Environment, ParCo’99, Imperial College Press, pp. 697–704, August 1999, TU Delft, The Netherlands.Google Scholar
  5. 5.
    I.S. Duff, H.A. van der Vorst: Developments and Trends in the Parallel Solution of Linear Systems, Parallel Computing, Vol 25(13-14), pp.1931–1970, 1999.CrossRefMathSciNetGoogle Scholar
  6. 6.
    A. Agarwal, D.A. Kranz, V. Natarajan: Automatic Partitioning of Parallel Loops and Data Arrays for Distributed Shared-Memory Multiprocessors, IEEE Trans. on Parallel and Distributed Systems, Vol. 6,No. 9, September 1995, pp. 943.962.CrossRefGoogle Scholar
  7. 7.
    G.M. Megson, X. Chen, Automatic parallelization for a class of regular computations. World Scientific, 1997.Google Scholar
  8. 8.
    T.L. Freeman, C. Phillips: Parallel Numerical Algorithms. Prentice Hall 1992.Google Scholar
  9. 9.
    MPICH-A Portable Implementation of MPI
  10. 10.
    Selim G. Akl: Parallel Computation Models and Methods, Prentice Hall 1997.Google Scholar
  11. 11.
  12. 12.
    Pfister G.F.: In Search of Clusters, Second Edition. Prentice Hall PTR, ISBN 0-13-899709-8, 1998.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Ladislav Hluchy
  • Giang T. Nguyen
  • Ladislav Halada
    • 1
  • Viet D. Tran
    • 1
  1. 1.Institute of Informatics, Slovak Academy of SciencesBratislavaSlovakia

Personalised recommendations