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- W2023595584 abstract "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." @default.
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- W2023595584 date "2014-03-24" @default.
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- W2023595584 title "Probabilistic standard cell modeling considering non-gaussian parameters and correlations" @default.
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- W2023595584 doi "https://doi.org/10.5555/2616606.2616887" @default.
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