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Fine Grained Parallel Processing for Soft Computing

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Knowledge-Based and Intelligent Information and Engineering Systems (KES 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5712))

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Abstract

This paper considers an approach to fine grained parallel processing for soft computing that mainly deals with large-scale stochastic optimization problems. In the detailed steps of the computation, there are a lot of useless calculations that has no influence upon final results. Removing such a wasted process must be effective to reduce the computational cost. The key is asynchronization of data processing by using redundancy of variables and priority-based processing. A typical system architecture to support this approach is presented and discussed for its application.

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References

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Author information

Authors and Affiliations

  1. Department of Arts and Sciences, Osaka Kyoiku University, 4-698-1 Asahigaoka, Kashiwara, Osaka, 581-8582, Japan

    Osamu Fujita & Koji Jinya

Authors
  1. Osamu Fujita
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  2. Koji Jinya
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Editor information

Editors and Affiliations

  1. University of Chile, Republica 701, 8370439, Santiago, Chile

    Juan D. Velásquez  & Sebastián A. Ríos  & 

  2. University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2009 Springer-Verlag Berlin Heidelberg

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Fujita, O., Jinya, K. (2009). Fine Grained Parallel Processing for Soft Computing. In: Velásquez, J.D., Ríos, S.A., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science(), vol 5712. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04592-9_95

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  • DOI: https://doi.org/10.1007/978-3-642-04592-9_95

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04591-2

  • Online ISBN: 978-3-642-04592-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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