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Adaptive scheduling strategy optimizer for parallel rolling bearing simulation

  • Track C1: (Industrial) End-user Applications of HPCN
  • Conference paper
  • First Online:
High-Performance Computing and Networking (HPCN-Europe 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1593))

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  • 2 Citations

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.

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References

  1. Kai Hwang and Fayé A. Briggs. Computer Architecture and Parallel Processing. McGraw Hill, 1984.

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  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.

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  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.

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Peter Sloot Marian Bubak Alfons Hoekstra Bob Hertzberger

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© 1999 Springer-Verlag

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Fritzson, D., Nordling, P. (1999). Adaptive scheduling strategy optimizer for parallel rolling bearing simulation. In: Sloot, P., Bubak, M., Hoekstra, A., Hertzberger, B. (eds) High-Performance Computing and Networking. HPCN-Europe 1999. Lecture Notes in Computer Science, vol 1593. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0100570

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  • DOI: https://doi.org/10.1007/BFb0100570

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65821-4

  • Online ISBN: 978-3-540-48933-7

  • eBook Packages: Springer Book Archive

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