Parameterized block-based non-Gaussian statistical gate timing analysis

As technology scales down, timing verification of digital integrated circuits becomes an increasingly challenging task due to the gate and wire variability. Therefore, statistical timing analysis (denoted by sigmaTA) is becoming unavoidable. This paper introduces a new framework for performing statistical gate timing analysis for non-Gaussian sources of variation in block-based sigmaTA. First, an approach is described to approximate a variational RC-pi load by using a canonical first-order model. Next, an accurate variation-aware gate timing analysis based on statistical input transition, statistical gate timing library, and statistical RC-pi load is presented. Finally, to achieve the aforementioned objective, a statistical effective capacitance calculation method is presented. Experimental results show an average error of 6% for gate delay and output transition time with respect to the Monte Carlo simulation with 10⁴ samples while the runtime is nearly two orders of magnitude shorter