Efficient Block-Based Parameterized Timing Analysis Covering All Potentially Critical Paths

In order for the results of timing analysis to be useful, they must provide insight and guidance on how the circuit may be improved so as to fix any reported timing problems. A limitation of many recent variability-aware timing analysis techniques is that, while they report delay distributions, or verify multiple corners, they do not provide the required guidance for re-design. We propose an efficient block-based parameterized timing analysis technique that can accurately capture circuit delay at every point in the parameter space, by reporting all paths that can become critical. Using an efficient pruning algorithm, only those potentially critical paths are carried forward, while all other paths are discarded during propagation. This allows one to examine local robustness to parameters in different regions of the parameter space, not by considering differential sensitivity at a point (which would be useless in this context) but by knowledge of the paths that can become critical at nearby points in parameter space. We give a formal definition of this problem and propose a technique for solving it that improves on the state of the art, both in terms of theoretical computational complexity and in terms of run time on various test circuits.

[1]  Farid N. Najm,et al.  A Linear-Time Approach for Static Timing Analysis Covering All Process Corners , 2006, 2006 IEEE/ACM International Conference on Computer Aided Design.

[2]  Farid N. Najm,et al.  Parameterized timing analysis with general delay models and arbitrary variation sources , 2008, 2008 45th ACM/IEEE Design Automation Conference.

[3]  Sachin S. Sapatnekar,et al.  Statistical timing analysis considering spatial correlations using a single PERT-like traversal , 2003, ICCAD-2003. International Conference on Computer Aided Design (IEEE Cat. No.03CH37486).

[4]  Thomas Ottmann,et al.  Enumerating Extreme Points in Higher Dimensions , 2001, Nord. J. Comput..

[5]  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).

[6]  Sachin S. Sapatnekar,et al.  A framework for block-based timing sensitivity analysis , 2008, 2008 45th ACM/IEEE Design Automation Conference.

[7]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[8]  Natesan Venkateswaran,et al.  First-Order Incremental Block-Based Statistical Timing Analysis , 2006, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[9]  Michael Ian Shamos,et al.  Computational geometry: an introduction , 1985 .