Skip to main content

Reconfigurable Parallel Architecture for Genetic Algorithms: Application to the Synthesis of Digital Circuits

  • Conference paper
Reconfigurable Computing: Architectures, Tools and Applications (ARC 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4419))

Included in the following conference series:

Abstract

This work presents a proposal and implementation of a reconfigurable parallel architecture, using Genetic Algorithms and applied to synthesis of combinational digital circuits. This reconfigurable parallel architecture uses concepts of computer architecture and parallel processing to obtain a scalable performance. It is developed in VHDL and implemented totally in hardware using FPGA devices. The concept of reconfigurable and parallel architecture enables an easy hardware adaptation to different project requirements. This approach allows applies with flexibility different strategies to synthesis of combinational digital circuits problem.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cantú-Paz, E.: Efficient and Accurate Parallel Genetic Algorithms, vol. 1. Kluwer Academic, Norwel (2001)

    Google Scholar 

  2. Coello-Coello, C.A., Aguirre, A.H.: On the use of a population-based particle swarm optimizer to design combinational logic circuits. In: Proc. NASA/DoD Conference on Evolvable Hardware, pp. 183–190 (2004)

    Google Scholar 

  3. Dongarra, J., et al.: Sourcebook of parallel computing. Morgan Kaufmann, San Francisco (2003)

    Google Scholar 

  4. Goldberg, D.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison Wesley, Reading (1989)

    MATH  Google Scholar 

  5. Graham, P., Nelson, B.: A Hardware genetic algorithm for the traveling salesman problem on Splash 2. In: Moore, W., Luk, W. (eds.) FPL 1995. LNCS, vol. 975, pp. 352–361. Springer, Heidelberg (1995)

    Google Scholar 

  6. Hartenstein, R.: A Decade of reconfigurable computing: a visionary retrospective. In: Proc. IEEE Conf. on Design, Automation and Test in Europe, pp. 642–649. IEEE Computer Society Press, Los Alamitos (2001)

    Google Scholar 

  7. Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, East Lansing (1975)

    Google Scholar 

  8. Lysaght, P., Rosenstiel, W.: New algorithms, Architectures and Applications for Reconfigurable Computing. Springer, New York (2005)

    Book  Google Scholar 

  9. Gokhale, M., Graham, P.S.: Reconfigurable Computing: Accelerating Computation with Field-Programmable Gate Arrays. Springer, Berlin (2005)

    Google Scholar 

  10. Matsumoto, M., Nishimura, T.: Mersenne twister: a 623-dimensionally equidistributed uniform pseudorandom number generator. ACM Transactions on Modeling and Computer Simulations, 3–30 (1998)

    Google Scholar 

  11. Miller, J.F., Thomson, P.: Cartesian genetic programming. In: Poli, R., et al. (eds.) EuroGP 2000. LNCS, vol. 1802, pp. 121–132. Springer, Heidelberg (2000)

    Google Scholar 

  12. Murdocca, M.J., Heuring, V.P.: Principles of Computer Architecture. Prentice Hall, Englewood Cliffs (2001)

    Google Scholar 

  13. Pedroni, V.A.: Circuit Design with VHDL. MIT Press, Cambridge (2004)

    Google Scholar 

  14. Sekanina, L., Ruzicka, R.: Easily testable image operators: the class of circuits where evolution beats engineers. In: Proc. NASA/DoD Conference on Evolvable Hardware, pp. 135–144 (2003)

    Google Scholar 

  15. Tang, W., Yip, L.: Hardware implementation of genetic algoritms using FPGA. In: Proc. 47th Midwest Symposium on Circuits and Systems, vol 1, pp. 549–552 (2004)

    Google Scholar 

  16. Yue, K.K., Lilja, D.J.: Designing multiprocessor scheduling algorithms using a distributed genetic algorithm system. Evolutionary Algorithms in Engineering Applications 33, 39–40 (1997)

    Google Scholar 

  17. Zhang, Y., Smith, S.L., Tyrrell, A.M.: Digital circuit design using intrinsic evolvable hardware. In: Proc. NASA/DoD Conference on Evolvable Hardware, pp. 55–62 (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Pedro C. Diniz Eduardo Marques Koen Bertels Marcio Merino Fernandes João M. P. Cardoso

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Berlin Heidelberg

About this paper

Cite this paper

Ferlin, E.P., Lopes, H.S., Lima, C.R.E., Cichaczewski, E. (2007). Reconfigurable Parallel Architecture for Genetic Algorithms: Application to the Synthesis of Digital Circuits. In: Diniz, P.C., Marques, E., Bertels, K., Fernandes, M.M., Cardoso, J.M.P. (eds) Reconfigurable Computing: Architectures, Tools and Applications. ARC 2007. Lecture Notes in Computer Science, vol 4419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71431-6_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-71431-6_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71430-9

  • Online ISBN: 978-3-540-71431-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics