skip to main content
10.1145/775832.776075acmconferencesArticle/Chapter ViewAbstractPublication PagesdacConference Proceedingsconference-collections
Article

Efficient description of the design space of analog circuits

Published:02 June 2003Publication History

ABSTRACT

In this paper we present a method for determining the feasible set of analog design problems and we propose an efficient method for their verification. The verification method presented relies on the formulation of the analog circuit design problem as a convex optimization problem in both the design variables and the performance specifications. Since the design is convex not only in the design variables but also in the specification parameters, we observe that the feasible sets are convex and points at the boundary can be found by solving a single convex optimization problem. We also show that feasible sets can be very well approximated with a polyhedron and therefore defined by a finite set of points. The implication of the latter is that new verifications do not need to be run for every new instantiation of a synthesized analog cell.

References

  1. IBS Corporation. Industry reports, 2002.Google ScholarGoogle Scholar
  2. G. Moretti. The next wave synthesis tools help with mixed-signal design. Electronic Design Magazine, November 2002.Google ScholarGoogle Scholar
  3. E. S. Ochotta, R. A. Rutenbar, and L. R. Carley. Synthesis of high-performance analog circuits in ASTRX/OBLX. IEEE Transactions on Computer-Aided Design, 15:273--293, March 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. W. Nye, D. C. Riley, A. Sangiovanni-Vincentelli, and A. L. Tits. DELIGHT.SPICE: An optimization-based system for the design of integrated circuits. IEEE Transactions on Computer-Aided Design, 7:501--518, April 1988.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. M. Hershenson, S. Boyd, and T. H. Lee. Optimal design of a CMOS op-amp via geometric programming. IEEE Transactions on Computer-Aided Design, 20:1--21, January 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. W. Daems, G. Gielen, and W. Sansen. An efficient optimization-based technique to generate posynomial performance models for analog. In 39th Design Automation Conference, pages 431--436, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. A. Hassibi and M. Hershenson. Automated optimal design of switched-capacitor filters. In Design, Automation and Test in Europe Conference and Exhibition, page 1111, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. C. Liu and Y. Li. Optimal design of CMOS low noise amplifiers via geometric programming. EE227 Final Project, 2001.Google ScholarGoogle Scholar
  9. M. Hershenson. Design of pipeline analog-to-digital convertes via geometric programming. In Proceedings of the 2002 IEEE/ACM International Conference on Computer Aided Design, November 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. D. Ham and A. Hajimiri. Concepts and methods in optimization of integrated LC VCOs. IEEE Journal of Solid-State Circuits, 36:896--909, June 2001.Google ScholarGoogle ScholarCross RefCross Ref
  11. R. J. Duffin, E. L. Peterson, and C. Zener. Geometric Programming - Theory and Applications. Wiley, 1967.Google ScholarGoogle Scholar
  12. S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. J. W. Chinneck. Discovering the characteristics of mathematical programs via sampling. Technical report, Carleton Univeristy, 2000.Google ScholarGoogle Scholar

Index Terms

  1. Efficient description of the design space of analog circuits

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      DAC '03: Proceedings of the 40th annual Design Automation Conference
      June 2003
      1014 pages
      ISBN:1581136889
      DOI:10.1145/775832

      Copyright © 2003 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 2 June 2003

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • Article

      Acceptance Rates

      DAC '03 Paper Acceptance Rate152of628submissions,24%Overall Acceptance Rate1,770of5,499submissions,32%

      Upcoming Conference

      DAC '24
      61st ACM/IEEE Design Automation Conference
      June 23 - 27, 2024
      San Francisco , CA , USA

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader