Skip to main content

Implementing a Margolus Neighborhood Cellular Automata on a FPGA

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2687))

Abstract

Margolus neighborhood is the easiest form of designing Cellular Automata Rules with features such as invertibility or particle conserving. In this paper we introduce a notation to describe completely a rule based on this neighborhood and implement it in two ways: The first corresponds to a classical RAM-based implementation, while the second, based on concurrent cells, is useful for smaller systems in which time is a critical parameter. This implementation has the feature that the evolution of all the cells in the design is performed in the same clock cycle.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wolfram, S.: Cellular Automata. Los Alamos Science, 9 (1983) 2–21

    Google Scholar 

  2. Wolfram, S.: Statistical mechanics of cellular automata. Reviews of Modern Physics, 55 (1983) 601–644

    Article  MathSciNet  MATH  Google Scholar 

  3. Margolus, N.: Physics-Like models of computation. Physica 10D (1984) 81–95

    MathSciNet  MATH  Google Scholar 

  4. Toffoli, T.: Cellular Automata as an alternative to (rather tah an approximation of) Differential Equations in Modeling Physics. Physica 10D (1984) 117–127

    MathSciNet  MATH  Google Scholar 

  5. Toffoli, T.: Occam, Turing, von Neumann, Jaynes: How much can you get for how little? (A conceptual introduction to cellular automata). The Inter journal (October 1994)

    Google Scholar 

  6. Toffoli, T., Margolus, N.: Invertible cellular automata: a review. Physica D, Nonlinear Phenomena, 45 (1990) 1–3

    Article  MathSciNet  MATH  Google Scholar 

  7. Gruau, F. C, Tromp, J. T.: Cellular Gravity. Parallel Processing Letters, Vol. 10, No. 4 (2000) 383–393

    Article  MathSciNet  Google Scholar 

  8. Smith, M. A.: Cellular Automata Methods in Mathematical Physics. Ph.D. Thesis. MIT Department of Physics (May 1994).

    Google Scholar 

  9. Wolfram, S.: Cryptography with Cellular Automata. Advances in Cryptology: Crypto’ 85 Proceedings, Lecture Notes in Computer Science, 218 (Springer-Verlag, 1986) 429–432

    Google Scholar 

  10. Sarkar, P.: A brief history of cellular automata. ACM Computing Surveys, Vol. 32, Issue 1 (2000) 80–107

    Article  Google Scholar 

  11. Shackleford, B., Tanaka, M., Carter, R.J., Snider, G.: FPGA Implementation of Neighborhood-of-Four Cellular Automata Random Number Generators. Proceedings of FPGA 2002 (2002) 106–112

    Google Scholar 

  12. Vichniac, G. Y.: Simulating Physics with Cellular Automata. Physica 10D (1984) 96–116

    MathSciNet  MATH  Google Scholar 

  13. Popovici, A., Popovici, D.: Celluar Automata in Image Processing. Proceedings of MTNS 2002 (2002)

    Google Scholar 

  14. Wolfram, S.: A New Kind of Science. Wolfram media (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cerda, J., Gadea, R., Paya, G. (2003). Implementing a Margolus Neighborhood Cellular Automata on a FPGA. In: Mira, J., Álvarez, J.R. (eds) Artificial Neural Nets Problem Solving Methods. IWANN 2003. Lecture Notes in Computer Science, vol 2687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44869-1_16

Download citation

  • DOI: https://doi.org/10.1007/3-540-44869-1_16

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40211-4

  • Online ISBN: 978-3-540-44869-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics