Model Optimization and Parameter Estimation with Nimrod/O

  • David Abramson
  • Tom Peachey
  • Andrew Lewis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3991)


Optimization problems where the evaluation step is computationally intensive are becoming increasingly common in both engineering design and model parameter estimation. We describe a tool, Nimrod/O, that expedites the solution of such problems by performing evaluations concurrently, utilizing a range of platforms from workstations to widely distributed parallel machines. Nimrod/O offers a range of optimization algorithms adapted to take advantage of parallel batches of evaluations. We describe a selection of case studies where Nimrod/O has been successfully applied, showing the parallelism achieved by this approach.


Execution Time Fatigue Life Parameter Sweep Parallel Batch Future Generation Computer System 


  1. 1. (accessed August 3, 2005)
  2. 2. (accessed August 3 , 2005)
  3. 3.
  4. 4.
    Abramson, D., et al.: The Nimrod computational workbench: A case study in desktop metacomputing. In: Australian Computer Science Conference (ACSC 1997), Macquarie University, Sydney, pp. 17–26 (February 1997)Google Scholar
  5. 5.
    Abramson, D.A., Lewis, A., Peachey, T.: Nimrod/O: a tool for automatic design optimisation using parallel and distributed systems. In: Proceedings of the 4th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2000), pp. 497–508. World Scientific Publishing Co., Singapore (2000)Google Scholar
  6. 6.
    Abramson, D., Giddy, J., Kotler, L.: High performance parametric modeling with Nimrod/G: Killer application for the global grid? In: International Parallel and Distributed Processing Symposium (IPDPS) (May 2000)Google Scholar
  7. 7.
    Abramson, D.A., Lewis, A., Peachey, T.: Case studies in automatic design optimisation using the P-BFGS algorithm. In: Tentner, A. (ed.) Proceedings of the High Performance Computing Symposium - HPC 2001, Seattle, April 2001, pp. 22–26 (2001); The International Society for Modeling and SimulationGoogle Scholar
  8. 8.
    Abramson, D.A., Lewis, A., Peachey, T., Fletcher, C.: An automatic design optimization tool and its application to computational fluid dynamics. In: Supercomputing, Denver (November 2001)Google Scholar
  9. 9.
    Abramson, D., Buuya, R., Giddy, J.: A computational economy for grid computing and its implementation in the Nimrod-G resource broker. Future Generation Computer Systems 18(8) (October 2002)Google Scholar
  10. 10.
    Burton, F.W.: Speculative computation, parallelism and functional programming. IEEE Transactions on Computers, C 34, 1190–1193 (1985)Google Scholar
  11. 11.
    Chong, E.K.P., Żak, S.H.: An Introduction to Optimization. Wiley, Chichester (1996)MATHGoogle Scholar
  12. 12.
    Lewis, A., Abramson, D.A., Simpson, R.: Parallel non-linear optimization: towards the design of a decision support system for air quality management. In: IEEE Supercomputing 1997, California, pp. 1–13 (1997)Google Scholar
  13. 13.
    Lewis, A., Abramson, D., Peachey, T.: An evolutionary programming algorithm for automatic engineering design. In: Parallel Processing and Applied Mathematics: 5th International Conference (PPAM 2003), Czestochowa, Poland (2003)Google Scholar
  14. 14.
    Lewis, A., Abramson, D.A., Peachey, T.: RSCS: A parallel simplex algorithm for the Nimrod/O optimization toolset. In: Proceedings of the Third International Symposium on Parallel and Distributed Computing (ISPDC 2004), Cork, Ireland, pp. 71–78. IEEE Computer Society, Los Alamitos (2004)Google Scholar
  15. 15.
    Peachey, T.C., Abramson, D., Lewis, A.: Heuristics for parallel simulated annealing by speculation. Technical report, Monash University (2001)Google Scholar
  16. 16.
    Peachey, T., Abramson, D.A., Lewis, A., Kurniawan, D., Jones, R.: Optimization using Nimrod/O and its application to robust mechanical design. In: Wyrzykowski, R., Dongarra, J., Paprzycki, M., Waśniewski, J. (eds.) PPAM 2004. LNCS, vol. 3019, pp. 730–737. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  17. 17.
    Peachey, T.C., Abramson, D., Lewis, A.: Parallel Line Search. Springer, Heidelberg (to appear)Google Scholar
  18. 18.
    Peachey, T.C., Enticott, C.M.: Determination of the best constant in an inequality of Hardy, Littlewood and Polya. Experimental Mathematics (to appear)Google Scholar
  19. 19.
    Peachey, T.C.: The Nimrod/O Users’ Manual v2.6. Monash University (2005),
  20. 20.
    Press, W.H., et al.: Numerical Recipes in C, 2nd edn., Cambridge (1993)Google Scholar
  21. 21.
    Sudholt, W., et al.: Applying grid computing to the parameter sweep of a group difference pseudopotential. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2004. LNCS, vol. 3036, pp. 148–155. Springer, Heidelberg (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • David Abramson
    • 1
  • Tom Peachey
    • 1
  • Andrew Lewis
    • 2
  1. 1.Caulfield School of Information TechnologyMonash UniversityMelbourneAustralia
  2. 2.Division of Information ServicesGriffith UniversityBrisbaneAustralia

Personalised recommendations