Skip to main content
SpringerLink
Log in

Using Genetic Programming and High Level Synthesis to Design Optimized Datapath

  • Conference paper
  • First Online:
Evolvable Systems: From Biology to Hardware (ICES 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2606))

Included in the following conference series:

Abstract

This paper presents a methodology to design optimized electronic digital systems from high abstraction level descriptions. The methodology uses Genetic Programming in addition to high-level synthesis tools to automatically improve design structural quality (area measure). A two-stage, multiobjective optimization algorithm is used to search for circuits with the desired functionality subjected additionally to chip area constraints. Experiment with a squareroot approximation datapath design targeted to FPGA exemplifies the proposed methodology.

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

Access this chapter

Log in via an institution
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. Y-L Lin, Recent Development in High Level Synthesis, ACM Transactions on Design Automation of Electronic Systems, Vol. 2, No. 1, 1997.

    Google Scholar 

  2. D. Gajski, N. Dutt, A. Wu and S. Lin, High Level Synthesis: Introduction to Chip and System Design, Kluver Academic Publishers, 1992.

    Google Scholar 

  3. D. Gajski, J. Zhu and R. Dörner, Special Issues in Codesign, Technical Report ICS-97-26, 1997.

    Google Scholar 

  4. IEEE Std. 1076-1993, VHDL Language Reference Manual, 1993.

    Google Scholar 

  5. Z. Navabi, VHDL: Analysis and Modeling of Digital Systems, McGraw Hill, 2d Edition, 1998.

    Google Scholar 

  6. D. Gajski, I. Tadatoshi, V. Chaiyakul, H. Juan and T. Hadley, A Design Methodology and Environment for Interactive Behavioral Synthesis, Technical Report 96-29, 1996.

    Google Scholar 

  7. K. Kuusilinna, T. Hämäläinen and J. Saarinen, Practical VHDL Optimization for Timing Critical FPGA Applications, Microprocessors and Microsystems 23, pp. 459–469, 1999.

    Article  Google Scholar 

  8. D. Landis, Programmable Logic and Application Specific Integrated Circuits, Handbook of Components for Electronics, Chapter II, Vol. 1, 1995.

    Google Scholar 

  9. Synopsys Inc., Synopsys Online Documentation, 2001.

    Google Scholar 

  10. H. DeGaris, Evolvable Hardware: Genetic Programming of a Darwin Machine, McGraw-Hill, Artificial Neural Nets and Genetic Algorithms, Springer-Verlag, NY, 1993.

    Google Scholar 

  11. R. Zebulum, M. Pacheco and M. Vellasco, Evolvable Systems in Hardware Design Taxonomy, Survey and Applications, Evolvable Systems: From Biology to Hardware, (ICES96), pp. 344–358, 1996.

    Google Scholar 

  12. F. Bennett III, J. Koza, J. Yu and W. Mydlowec, Automatic Synthesis, Placement and Routing of an Amplifier Circuit by Means of Genetic Programming, Proc. of the Third Int. Conf. on Evolvable Systems, ICES 2000, pp. 1–10, Edinburgh, Scotland, UK, 2000.

    Google Scholar 

  13. J. Miller, P. Thomson and T. Fogarty, Designing Electronic Circuits Using Evolutionary Algorithms. Arithmetic Circuits: A Case Study, Genetic Algorithms and Evolution Strategies in Engineering and Computer Science, edited by D. Quagliarella et al., Publisher: Wiley, 1997.

    Google Scholar 

  14. T. Kalganova and J. Miller, Evolving More Efficient Digital Circuits by Allowing Circuit Layout Evolution and Multi-Objective Fitness, Proc. of the First NASA/DoD Workshop on Evolvable Hardware, pp. 54–63, Los Alamitos, CA, IEEE Computer Society Press, 1999.

    Google Scholar 

  15. C. Coello, A. Aguirre and B. Buckles, Evolutionary Multiobjective Design of Combinational Logic Circuits, Proc. of the Second NASA/DoD Workshop on Evolvable Hardware, pp. 161–170, IEEE Computer Society, Los Alamitos, CA, 2000.

    Google Scholar 

  16. B. Hounsell and T. Arslan, A Novel Evolvable Hardware Framework for the Evolution of High Performance Digital Circuits, GECCO-2000, pp. 525–532, 2000.

    Google Scholar 

  17. H. Hemmi, J. Mizoguchi and K. Shimohara, M. Tomassini, Development and Evolution of Hardware Behaviors, Towards Evolvable Hardware: The Evolutionary Engineering Approach, Int. Workshop, Lausanne, edited by E. Sanchez and M. Tomassini, Springer-Verlag, LNCS 1062, pp. 250–265, 1996.

    Google Scholar 

  18. J. Rosca, Hierarchical Learning with Procedural Abstractions Mechanisms, PhD Thesis, University of Rochester, New York, 1997.

    Google Scholar 

  19. M. Tomassini, Evolutionary Algorithms, Towards Evolvable Hardware: The Evolutionary Engineering Approach, Int. Workshop, Lausanne, edited by E. Sanchez and M. Tomassini, Springer-Verlag, LNCS 1062, pp. 19–47, 1996.

    Google Scholar 

  20. J. Holland, Adaptation in Natural and Artificial Systems, The University of Michigan, 1st Edition, 1975.

    Google Scholar 

  21. J. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, 1992.

    Google Scholar 

  22. W. Banzhaf, P. Nordin, R. Keller and F. Francone, Genetic Programming: An Introduction, San Francisco, CA, Morgan Kaufmann and Heidelberg, 1997.

    Google Scholar 

  23. R. Keller and W. Banzhaf, Genetic Programming Using Genotype-Phenotype Mapping from Linear Genomes into Linear Phenotypes, Proc. of Genetic Programming 1996, pp. 116–122, MIT Press, 1996.

    Google Scholar 

  24. N. Paterson and M. Livesey, Evolving Cache Algorithms in C by GP, Genetic Programming 1997, pp. 262–267, MIT Press, 1997.

    Google Scholar 

  25. A. Ratle and M. Sebag, Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery, Parallel Problem Solving from Nature, 2000.

    Google Scholar 

  26. M. Wong and K. Leung, Applying Logic Grammars to Induce Sub-functions in Genetic Programming, Proc. of 1995 IEEE Conf. on Evolutionary Computation, pp. 737–740, USA:IEEE Press, 1995.

    Google Scholar 

  27. P. Whigham, Grammatically-Based Genetic Programming, Proc. of the Workshop on Genetic Programming: From Theory to Real-World Applications, pp. 33–41, Morgan Kauffmann Publishers, 1995.

    Google Scholar 

  28. H. Hörner, A C++ Class Library for Genetic Programming, Release 1.0 Operating Instructions, Viena University of Economy, 1996.

    Google Scholar 

  29. C. Ryan and M. O'Neill, Grammatical Evolution: Evolving Programs for an Arbitrary Language, LNCS 1391, Proc. of the First European Workshop on Genetic Programming, pp. 83–95, Springer-Verlag, 1998.

    Google Scholar 

  30. Altera Inc., Altera Digital Library Databook 2001, 2001.

    Google Scholar 

  31. D. Montana, R. Popp, S. Iyer and G. Vidaver, EvolvaWare: Genetic Programming for Optimal Design of Hardware-Based Algorithms, Genetic Programming 1998, pp. 869, 1998.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical Engineering Dept., Federal University of Rio de Janeiro, C.P. 68504, CEP 21945-970, Rio de Janeiro, RJ, Brazil

    Sérgio G. Araújo, A. Mesquita & Aloysio C. P. Pedroza

Authors
  1. Sérgio G. Araújo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Mesquita
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aloysio C. P. Pedroza
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. The Department of Electronics, The University of York, YO10 5DD, Heslington, York, United Kingdom

    AAndy M. Tyrrell

  2. Department of Computer and Information Science, The Norwegian University of Science and Technology, Sem Sælands Vei, 7491, Trondheim, Norway

    Pauline C. Haddow

  3. Department of Informatics, University of Oslo, P.O. Box 1080, 0316, Blindern, Oslo, Norway

    Jim Torresen

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Araújo, S.G., Mesquita, A., Pedroza, A.C.P. (2003). Using Genetic Programming and High Level Synthesis to Design Optimized Datapath. In: Tyrrell, A.M., Haddow, P.C., Torresen, J. (eds) Evolvable Systems: From Biology to Hardware. ICES 2003. Lecture Notes in Computer Science, vol 2606. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36553-2_39

Download citation

  • DOI: https://doi.org/10.1007/3-540-36553-2_39

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00730-2

  • Online ISBN: 978-3-540-36553-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation