skip to main content
10.1109/ICCAD.2004.1382622acmconferencesArticle/Chapter ViewAbstractPublication PagesiccadConference Proceedingsconference-collections
Article

Static statistical timing analysis for latch-based pipeline designs

Authors Info & Claims
Published:07 November 2004Publication History

ABSTRACT

A latch-based timing analyzer is an essential tool for developing high-speed pipeline designs. As process variations increasingly influence the timing characteristics of DSM designs, a timing analyzer capable of handling process-induced timing variations for latch-based pipeline designs becomes in demand. In this work, we present a static statistical timing analyzer, STAP, for latch-based pipeline designs. Our analyzer propagates statistical worst-case delays as well as critical probabilities across the pipeline stages. We present an efficient method to handle correlations due to re-convergent fanouts. We also demonstrate the impact of not including the analysis of reconvergent fanouts in latch-based pipeline designs. Comparing to a Monte-Carlo based timing analyzer, our experiments show that STAP can accurately evaluate the critical probability that a design violates the timing constraints under a given statistical timing model. The runtime comparison further demonstrates the efficiency of our STAP.

References

  1. {1} K. A. Sakallah, T. N. Mudge, and O. A. Olukotun, Check Tc and min Tc: Timing verification and optimal clocking of synchronous digital circuits, ACM/IEEE International Conference on Computer Aided Design, pp. 552-555, November 1990.Google ScholarGoogle Scholar
  2. {2} T. M. Burks, K. A. Sakallah, and T. N. Mudge, Identification of Critical Paths in Circuits with Level-Sensitive Latches, ACM/IEEE International Conference on Computer Aided Design , pp. 137-141, November 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. {3} J. Lee, D. T. Tang, and C. K. Wrong, A Timing Analysis Algorithm for Circuits with Level-Sensitive Latches, ACM/IEEE International Conference on Computer Aided Design , pp. 535-543, November 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. {4} J.-J. Liou, K.-T. Cheng, and D. Mukherjee, Path Selection For Delay Testing of Deep Sub-micron Devices Using Statistical Performance Sensitivity Analysis, IEEE VLSI Test Symposium , pp. 97-104, April 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. {5} J.-J. Liou, A. Krstic, Y.-M. Jiang, and K.-T. Cheng, Path Selection and Pattern Generation for Dynamic Timing Analysis considering power supply noise effects, ACM/IEEE International Conference on Computer Aided Design, pp. 493-496, Nov 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. {6} J.-J. Liou, K.-T. Cheng, S. Kundu, and A. Krstic, Fast Statistical Timing Analysisby by Probabilistic Event Propagation, ACM/IEEE Design Automation Conference, pp. 661- 666, June 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. {7} A. Agarwal, D. Blaauw, V. Zolotov, and S. Vrudhula, Statistical Timing Analysis using Bounds, ACM/IEEE Design, Automation and Test in Europe Conference and Exhibition, pp. 62-67, March 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. {8} A. Devgan, and C. Kashyap, Block-based Static Timing Analysis with Uncertainty, ACM/IEEE International Conference on Computer Aided Design, pp. 607-614, November 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. {9} H. Chang and S. S. Sapatnekar, Statistical Timing Analysis Considering Spatial Correlations Using A Single PERT-like Traversal, ACM/IEEE International Conference on Computer Aided Design, pp. 621-625, November 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. {10} C. Visweswariah, K. Ravindran and K. Kalafala, First-Order Parameterized Block-Based Statistical Timing Analysis, ACM/IEEE workshop on timing issures in the specification and synthesis of digital systems, pp. 17-24, February 2004.Google ScholarGoogle Scholar
  11. {11} C.E. Clark, The Greatest of a Finite Set of Random Variables, Operation Research, vol. 9, pp. 85-91, 1961.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. {12} Eldo v4.4.x User's Manual. 1996.Google ScholarGoogle Scholar

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
    ICCAD '04: Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
    November 2004
    913 pages
    ISBN:0780387023

    Publisher

    IEEE Computer Society

    United States

    Publication History

    • Published: 7 November 2004

    Check for updates

    Qualifiers

    • Article

    Acceptance Rates

    Overall Acceptance Rate457of1,762submissions,26%

    Upcoming Conference

    ICCAD '24
    IEEE/ACM International Conference on Computer-Aided Design
    October 27 - 31, 2024
    New York , NY , USA

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader