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In order to achieve ultra-low power (ULP), ICs are being designed for 0.5 V. At these low voltages, random dopant fluctuations (RDFs) result in a stochastic component of logic delay that can be comparable to the global corner delay. Moreover, the probability density function (PDF) of this stochastic delay can be highly non-Gaussian. In order to predict the statistical impact of RDF-induced local variations on logic timing, it is necessary to incorporate these effects into a timing closure methodology. This paper presents a computationally efficient methodology for stochastic characterization of standard cell libraries at low voltage, where the cell delay is a nonlinear function of the transistor random variables (RVs), and the resulting cell delay has a non-Gaussian PDF. It also presents a computationally efficient methodology for computing any point on the PDF of a timing path (TP) delay, in the case where cell delays are non-Gaussian. The method is called nonlinear operating point analysis of local variation (NLOPALV). The general NLOPALV theory is developed. It is applied to cell library characterization, and the accuracy of the NLOPALV approach is validated by comparison to Monte Carlo simulation. NLOPALV is also applied to timing path analysis on a 28 nm DSP IC. The approach has been implemented using commercial CAD tools, and integrated into a commercial IC design flow. The NLOPALV approach gives timing results that are within 5% accuracy compared to Monte Carlo analysis at 0.5 V. This compares to errors on the order of 50% when the Gaussian approximation is used.

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