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Feasible models of computation: Three-dimensionality and energy consumption

  • Workshop 04+08+13: Parallel and Distributed Algorithms
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  • First Online: 01 January 2005
  • pp 384–388
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Euro-Par'97 Parallel Processing (Euro-Par 1997)
Feasible models of computation: Three-dimensionality and energy consumption
  • Peter Sanders1,
  • Roland Vollmar1 &
  • Thomas Worsch1 

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1300))

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  • European Conference on Parallel Processing
  • 522 Accesses

Abstract

Starting with cellular automata as a model of parallel machines we investigate the constraints for the energy consumption of r- dimensional machines which are motivated by fundamental physical limitations for the case r = 3. Depending on the operations which must be considered to dissipate energy (state changes, communication), relations between the relative performance of 2-D and 3-D machines are derived.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Karlsruhe, 76128, Karlsruhe, Germany

    Peter Sanders, Roland Vollmar & Thomas Worsch

Authors
  1. Peter Sanders
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  2. Roland Vollmar
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  3. Thomas Worsch
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Editor information

Christian Lengauer Martin Griebl Sergei Gorlatch

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© 1997 Springer-Verlag Berlin Heidelberg

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Sanders, P., Vollmar, R., Worsch, T. (1997). Feasible models of computation: Three-dimensionality and energy consumption. In: Lengauer, C., Griebl, M., Gorlatch, S. (eds) Euro-Par'97 Parallel Processing. Euro-Par 1997. Lecture Notes in Computer Science, vol 1300. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0002761

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  • DOI: https://doi.org/10.1007/BFb0002761

  • Published: 26 September 2005

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63440-9

  • Online ISBN: 978-3-540-69549-3

  • eBook Packages: Springer Book Archive

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Keywords

  • Energy Consumption
  • Cellular Automaton
  • Cellular Automaton
  • Cellular Automaton Model
  • Deterministic Finite Automaton

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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