First-Order Incremental Block-Based Statistical Timing Analysis

Variability in digital integrated circuits makes timing verification an extremely challenging task. In this paper, a canonical first-order delay model that takes into account both correlated and independent randomness is proposed. A novel linear-time block-based statistical timing algorithm is employed to propagate timing quantities like arrival times and required arrival times through the timing graph in this canonical form. At the end of the statistical timing, the sensitivity of all timing quantities to each of the sources of variation is available. Excessive sensitivities can then be targeted by manual or automatic optimization methods to improve the robustness of the design. This paper also reports the first incremental statistical timer in the literature, which is suitable for use in the inner loop of physical synthesis or other optimization programs. The third novel contribution of this paper is the computation of local and global criticality probabilities. For a very small cost in computer time, the probability of each edge or node of the timing graph being critical is computed. Numerical results are presented on industrial application-specified integrated circuit (ASIC) chips with over two million logic gates, and statistical timing results are compared to exhaustive corner analysis on a chip design whose hardware showed early mode timing violations

[1]  Chandramouli Visweswariah,et al.  Statistical Timing for Parametric Yield Prediction of Digital Integrated Circuits , 2006, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[2]  M. Berkelaar,et al.  Statistical delay calculation, a linear time method , 1997 .

[3]  A. Gattiker,et al.  Timing yield estimation from static timing analysis , 2001, Proceedings of the IEEE 2001. 2nd International Symposium on Quality Electronic Design.

[4]  Chandu Visweswariah,et al.  Death, taxes and failing chips , 2003, Proceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451).

[5]  Sachin S. Sapatnekar,et al.  Statistical Timing Analysis Considering Spatial Correlations using a Single Pert-Like Traversal , 2003, ICCAD 2003.

[6]  C. E. Clark The Greatest of a Finite Set of Random Variables , 1961 .

[7]  M. Cain The Moment-Generating Function of the Minimum of Bivariate Normal Random Variables , 1994 .

[8]  Kurt Keutzer,et al.  A general probabilistic framework for worst case timing analysis , 2002, DAC '02.

[9]  Kwang-Ting Cheng,et al.  Fast statistical timing analysis by probabilistic event propagation , 2001, DAC '01.

[10]  David Blaauw,et al.  Computation and refinement of statistical bounds on circuit delay , 2003, Proceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451).

[11]  Chandramouli Visweswariah,et al.  Statistical Timing for Parametric Yield Prediction of Digital Integrated Circuits , 2003, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[12]  Rajendran Panda,et al.  Statistical timing analysis using bounds and selective enumeration , 2002, TAU '02.

[13]  David Blaauw,et al.  Statistical timing analysis for intra-die process variations with spatial correlations , 2003, ICCAD-2003. International Conference on Computer Aided Design (IEEE Cat. No.03CH37486).

[14]  Louis Scheffer,et al.  Explicit computation of performance as a function of process variation , 2002, TAU '02.

[15]  David Blaauw,et al.  Statistical Timing Analysis for Intra-Die Process Variations with Spatial Correlations , 2003, ICCAD 2003.