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Effective Parallelism Rate by Reversible PCA Dynamics

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Cellular Automata (ACRI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8751))

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Abstract

Probabilistic Cellular Automata generalise CA by implementing an updating rule defined through a probability. It means a synchronous updating of the constituting cells/sites’ states is possible. PCA differ from the interacting particle systems where in general at most one site is possibly updated at a time. For a family of reversible (in a stochastic sense) PCA dynamics, we study through numerical simulations the effective flips occurring. When infinitely many sites are considered, there are two regime: an ergodic one and a phase transition regime. When finitely many interacting sites are considered, these regimes corresponds to very different effective parallelism rate. We quantify these changes. When phase transition holds, PCA dynamics is in fact an α-asynchronous one.

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Authors and Affiliations

  1. Laboratoire de Mathématiques et Applications, UMR 7348, Université de Poitiers & CNRS, Téléport 2, BP 30179, Boulevard Marie et Pierre Curie, 86962 Technopole du Futuroscope de Poitiers, Chasseneuil Cedex, France

    Pierre-Yves Louis

Authors
  1. Pierre-Yves Louis
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Editors and Affiliations

  1. Dept. of Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059, Krakow, Poland

    Jarosław Wąs

  2. Dept. of Electrical and Computer Engineering, Democritus University of Thrace, 67100, Xanthi, Greece

    Georgios Ch. Sirakoulis

  3. CSAI - Complex Systems and Artificial Intelligence Research Center, University of Milano-Bicocca, 20126, Milan, Italy

    Stefania Bandini

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© 2014 Springer International Publishing Switzerland

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Louis, PY. (2014). Effective Parallelism Rate by Reversible PCA Dynamics. In: Wąs, J., Sirakoulis, G.C., Bandini, S. (eds) Cellular Automata. ACRI 2014. Lecture Notes in Computer Science, vol 8751. Springer, Cham. https://doi.org/10.1007/978-3-319-11520-7_61

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  • DOI: https://doi.org/10.1007/978-3-319-11520-7_61

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11519-1

  • Online ISBN: 978-3-319-11520-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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