Parameter variations and impact on circuits and microarchitecture
Proceedings of the 40th annual Design Automation Conference
First-order incremental block-based statistical timing analysis
Proceedings of the 41st annual Design Automation Conference
Fast statistical timing analysis handling arbitrary delay correlations
Proceedings of the 41st annual Design Automation Conference
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
Asymptotic probability extraction for non-normal distributions of circuit performance
Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
Non-gaussian statistical parameter modeling for SSTA with confidence interval analysis
Proceedings of the 2006 international symposium on Physical design
A framework for statistical timing analysis using non-linear delay and slew models
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
An accurate sparse matrix based framework for statistical static timing analysis
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
Robust Extraction of Spatial Correlation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Accounting for non-linear dependence using function driven component analysis
Proceedings of the 2009 Asia and South Pacific Design Automation Conference
Proceedings of the 46th Annual Design Automation Conference
Non-Gaussian statistical timing analysis using second-order polynomial fitting
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Statistical path selection for at-speed test
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
On confidence in characterization and application of variation models
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Eagle-eye: a near-optimal statistical framework for noise sensor placement
Proceedings of the International Conference on Computer-Aided Design
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In the nanometer manufacturing region, process variation causes significant uncertainty for circuit performance verification. Statistical static timing analysis (SSTA) is thus developed to estimate timing distribution under process variation. However, most of the existing SSTA techniques have difficulty in handling the non-Gaussian variation distribution and non-linear dependency of delay on variation sources. To solve such a problem, in this paper, we first propose a new method to approximate the max operation of two non-Gaussian random variables through second-order polynomial fitting. We then present new non-Gaussian SSTA algorithms under two types of variational delay models: quadratic model and semi-quadratic model (i.e., quadratic model without crossing terms). All atomic operations (such as max and sum) of our algorithms are performed by closed-form formulas, hence they scale well for large designs. Experimental results show that compared to the Monte-Carlo simulation, our approach predicts the mean, standard deviation, and skewness within 1%, 1%, and 5% error, respectively. Our approach is more accurate and also 20x faster than the most recent method for non-Gaussian and nonlinear SSTA.