probabilistic standard cell modeling considering non gaussian parameters and correlations

• DOI: 10.5555/2616606.2616887
• Publication Date: 2014-01-01
• Authors: Andre Lange; Roland Jancke; Joachim Haase; Christoph Sohrmann; Ulf Schlichtmann; Ingolf Lorenz
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

Variability continues to pose challenges to integrated circuit design. With statistical static timing analysis and high-yield estimation methods, solutions to particular problems exist, but they do not allow a common view on performance variability including potentially correlated and non-Gaussian parameter distributions. In this paper, we present a probabilistic approach for variability modeling as an alternative: model parameters are treated as multi-dimensional random variables. Such a fully mul-tivariate statistical description formally accounts for correlations and non-Gaussian random components. Statistical characterization and model application are introduced for standard cells and gate-level digital circuits. Example analyses of circuitry in a 28 nm industrial technology illustrate the capabilities of our modeling approach.