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Adaptive scheduling strategy optimizer for parallel rolling bearing simulation

  • Dag Fritzson
  • Patrik Nordling
Track C1: (Industrial) End-user Applications of HPCN
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1593)

Abstract

Rolling bearing simulations are very computationally intensive and need to utilize the potential of parallel computing.

The load distribution over the processors in a rolling bearing simulation is very dynamic. In this paper we present the Adaptive Scheduling Strategy Optimizer (ASSO) for scheduling parallel simulations. The result of this is that the application can automatically select a near optimal scheduling strategy (with respect to the available scheduling strategies). The ASSO is used daily in real bearing simulations.

Keywords

Test Suite Parallel Machine Schedule Strategy Rolling Bearing Rolling Element 
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.

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References

  1. [1]
    Kai Hwang and Fayé A. Briggs. Computer Architecture and Parallel Processing. McGraw Hill, 1984.Google Scholar
  2. [2]
    Marc H. Willebeek-LeMair and Anthony P. Reeves. Strategies for Dynamic Load Balancing on Highly Parallel Computers. IEEE Transactions on Parallel and Distributed System. Vol. 4, No. 9, Sept. 1993.Google Scholar
  3. [3]
    Yong Yan and Canming Jin and Xiaodong Zhang. Adaptively Scheduling Parallel Loops in Distributed Shared-Memory Systems. IEEE Transactions on Parallel and Distributed System. Vol. 8, No. 1, Jan. 1997.Google Scholar

Copyright information

© Springer-Verlag 1999

Authors and Affiliations

  • Dag Fritzson
    • 1
  • Patrik Nordling
    • 2
  1. 1.SKF Engineering & Research Centre B.V.NieuwegeinThe Netherlands
  2. 2.Department of Computer and Information ScienceLinköping UniversityLinköpingSweden

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