A Design Model for Random Process Variability

Victoria Wang1,  Kanak Agarwal2,  Sani Nassif2,  Kevin Nowka2,  Dejan Markovic1


A new approach to analyze process variation through measured current variation is introduced. The methodology concludes with a simple and convenient posynomial model for random process variability to bridge the gap between existing statistical methods and circuit design. The model contains only design variables: W, L, and operating points Vgs and Vds. Modeling random process variability in this way allows for adaptability to optimization problems, time efficient methods for gathering statistical information in comparison to Monte Carlo, and an alternative equation for hand analysis.