Distributed Numerical Simulation on Workstation Networks

  • W. Huber
  • R. Hüttl
  • M. Schneider
  • C. Zenger
Part of the Notes on Numerical Fluid Mechanics (NNFM) book series (NONUFM, volume 48)


Networks of workstations are an interesting and valuable tool for studying and executing parallel programs. This paper investigates their use for the numerical simulation of complicated processes in various fields of technical applications. It is demonstrated that the limited communication rate in comparison to dedicated parallel computers is not always a serious bottleneck in this area of applications. Moreover, there are also advantages of this approach which in practice may be much more important than its deficiencies.


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  1. [1]
    A. G. A. Beguelin, J. Dongarra, R. Manchek, and V. Sunderam, A user’s guid to PVM, technical report, ORNL/TM-11826, Mathematical Science Section, Oak Ridge National Laboratory, 1991.Google Scholar
  2. [2]
    L. M. Adams and R. G. Voigt, A methodology for exploiting parallelism in the finite element process, in NATO ASI, Vol. F7, Springer Verlag, 1984.Google Scholar
  3. [3]
    I. Babuska and W. C. Rheinboldt, Error estimates for adaptive finite element computations, in SIAM J. Num. Anal, Vol. 15, pp. 736–754, 1978.MathSciNetzbMATHCrossRefGoogle Scholar
  4. [4]
    H. Bungartz, An adaptive Poisson solver using hierarchical bases and sparse grids, in Proceedings of the IMACS International Symposium on Iterative Methods in Linear Algebra, P. de Groen and R. Beauwens, ed., Amsterdam, Elsevier, 1992.Google Scholar
  5. [5]
    H. Bungartz, Dünne Gitter und deren Anwendung bei der adaptiven Lösung der dreidimen-sionalen Poisson-Gleichung, Dissertation, Institut für Informatik, TU München, 1992.Google Scholar
  6. [6]
    D. S. Burnett, Finite element analysis, Addison-Wesley Publishing Company, 1987.zbMATHGoogle Scholar
  7. [7]
    R. H. Dodds and L. A. Lopez, Substructuring in linear and nonlinear analysis, in International Journal for Numerical Methods in Engineering, Vol. 15, pp. 583–597, 1980.zbMATHCrossRefGoogle Scholar
  8. [8]
    U. Feldmann, U. Wever, Q. Zheng, R. Schultz, and H. Wriedt, Algorithms for modern circuit simulation, in Archiv für Elektronik und Ubertragungstechnik, Vol. 46, No. 4, pp. 274–285, 1992.Google Scholar
  9. [9]
    M. Griebel, W. Huber, U. Rüde, and T. Störtkuhl, The Combination Technique for Parallel Sparse-Grid-Preconditioning and -Solution of PDEs on Multiprocessor Machines and Workstation Networks, in Proceedings of the Second Joint International Conference on Vector and Parallel Processing CONPAR/VAPP V 92, L. Bouge, M. Cosnard, Y. Robert and D. Trystram, ed., Springer Verlag, 1992. Also available as SFB Bericht 342/11/92 A.Google Scholar
  10. [10]
    M. Griebel, W. Huber, T. Stortkuhl, and C. Zenger, On the parallel solution of 3D PDEs on a network of workstations and on vector computers, in Lecture Notes in Computer Science, Computer Architecture: Theory, Hardware, Software, Applications, A. Bode and M. DalCin, ed., Springer Verlag, 1993.Google Scholar
  11. [11]
    M. Griebel, M. Schneider, and C. Zenger, A combination technique for the solution of sparse grid problems, in Iterative Methods in Linear Algebra, P. de Groen and R. Beauwens, ed., IMACS, Elsevier, North Holland, 1992, pp. 263–281. Also published in: SFB Bericht 342/19/90.Google Scholar
  12. [12]
    M. Griebel and V. Thurner, The efficient solution of fluid dynamics problems by the combination technique, SFB Bericht 342/1/93 A, Institut für Informatik, TU München, 1993. To be published in Int. J. Num. Meth. for Heat and Fluid Flow.Google Scholar
  13. [13]
    R. Hüttl and M. Schneider, Parallel adaptive numerical simulation, SFB Bericht 342/01/94 A, Institut für Informatik, TU München, 1994.Google Scholar
  14. [14]
    M. Schneider, U. Wever, and Q. Zheng, Solving large and sparse linear blockmatrix systems in anlog circuit simulation on a cluster of workstations, in The Computer Journal, Vol. 36, No. 8, pp.685–689, 1993.CrossRefGoogle Scholar
  15. [15]
    C. Zenger, Sparse grids, in Parallel Algorithms for Partial Differential Equations, Proceedings of the Sixth GAMM-Seminar, Kiel, January 19–21, 1990, W. Hackbusch, ed., Braunschweig, 1991, Vieweg Verlag.Google Scholar

Copyright information

© Friedr. Vieweg & Sohn Verlagsgesellschaft mbH, Braunschweig/Wiesbaden 1994

Authors and Affiliations

  • W. Huber
    • 1
  • R. Hüttl
    • 1
  • M. Schneider
    • 1
  • C. Zenger
    • 1
  1. 1.Institut für Informatik, Lehrstuhl für Ingenieuranwendungen in der InformatikTechnische Universität MünchenMünchenGermany

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