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Optimal Stochastic Scaling of CAE Parallel Computations

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Rough Sets and Current Trends in Computing (RSCTC 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1424))

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Abstract

The meshless strategy of CAE problem partitioning is presented. It offers significant decrement of time complexity in comparison with usual mesh decomposition algorithms, and therefore may be applied in on-line processing. The effective IE graph solid representation is applied as well as the stochastic performance forecast system for parallel MIMD computer nodes. The main scaling problem is formulated as the optimal fuzzy graph matching and it is proposed to be solved by efficient ETPL(k) parsers.

The research was supported from the ESPRIT Project 20288-13.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Jagiellonian University, Cracow, Poland

    Mariusz Flasiñski & Robert Schaefer

  2. Cracow University of Technology, Cracow, Poland

    Wojciech Toporkiewicz (PhD student)

Authors
  1. Mariusz Flasiñski
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  2. Robert Schaefer
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  3. Wojciech Toporkiewicz
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Editor information

Editors and Affiliations

  1. Institute of Mathematics, Warsaw University of Technology, Pl. Politechniki 1, 00-665, Warszawa, Poland

    Lech Polkowski

  2. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warszawa, Poland

    Andrzej Skowron

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© 1998 Springer-Verlag Berlin Heidelberg

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Flasiñski, M., Schaefer, R., Toporkiewicz, W. (1998). Optimal Stochastic Scaling of CAE Parallel Computations. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_77

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  • DOI: https://doi.org/10.1007/3-540-69115-4_77

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64655-6

  • Online ISBN: 978-3-540-69115-0

  • eBook Packages: Springer Book Archive

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