Analog Integrated Design Automation

Abstract

Circuit reliability in the presence of statistical process variation is becoming a challenging domain, as transistors sizes get smaller and smaller in the nanoscale era. It is not enough to add safety margins to designs or depend on simple assumptions about “worst case” corners. Circuits that are replicated in millions of instances on large designs such as SRAMs and flip flops face the problem that a rare event in a circuit cell may have a large impact on the system yield. Monte Carlo simulation is an ideal tool for estimation of the yield of such high replication circuit (HRCs) but not a practical one because of the high yield requirements for individual cells. Numerous techniques have been proposed to overcome this disadvantage in Monte Carlo approach. Some approaches are analytical or semi analytical that model the behavior of SRAM cell. Other statistical techniques aim to reduce the number of Monte Carlo simulations. Statistical blockade algorithm aims at detecting rare events in the tail through the classification of tail points and the fitting of GPD distribution to the tail points.\begin_inset Separator latexpar\end_inset