First-order incremental block-based statistical timing analysis
Proceedings of the 41st annual Design Automation Conference
Statistical Timing Analysis Considering Spatial Correlations using a Single Pert-Like Traversal
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Proceedings of the 42nd annual Design Automation Conference
Correlation-aware statistical timing analysis with non-gaussian delay distributions
Proceedings of the 42nd annual Design Automation Conference
Correlation-preserved non-gaussian statistical timing analysis with quadratic timing model
Proceedings of the 42nd annual Design Automation Conference
A general framework for accurate statistical timing analysis considering correlations
Proceedings of the 42nd annual Design Automation Conference
Proceedings of the 43rd annual Design Automation Conference
A linear-time approach for static timing analysis covering all process corners
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
Non-linear statistical static timing analysis for non-Gaussian variation sources
Proceedings of the 44th annual Design Automation Conference
Efficient block-based parameterized timing analysis covering all potentially critical paths
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Leakage reduction, delay compensation using partition-based tunable body-biasing techniques
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Quantifying robustness metrics in parameterized static timing analysis
Proceedings of the 2009 International Conference on Computer-Aided Design
A unified multi-corner multi-mode static timing analysis engine
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
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Many recent techniques for timing analysis under variability, in which delay is an explicit function of underlying parameters, may be described as parameterized timing analysis. The "max" operator, used repeatedly during block-based timing analysis, causes several complications during parameterized timing analysis. We introduce bounds on, and an approximation to, the max operator which allow us to develop an accurate, general, and efficient approach to parameterized timing, which can handle either uncertain or random variations. Applied to random variations, the approach is competitive with existing statistical static timing analysis (SSTA) techniques, in that it allows for nonlinear delay models and arbitrary distributions. Applied to uncertain variations, the method is competitive with existing multi-corner STA techniques, in that it more reliably reproduces overall circuit sensitivity to variations. Crucially, this technique can also be applied to the mixed case where both random and uncertain variations are considered. Our results show that, on average, circuit delay is predicted with less than 2% error for multi-corner analysis, and less than 1% error for SSTA.