Accurate and Scalable IO Buffer Macromodel Based on Surrogate Modeling

In this paper, a new method is proposed to generate accurate and scalable macromodels for input/output buffers. The method characterizes the physically based model elements with adaptive multivariate surrogate modeling techniques in order to achieve high fidelity and process-voltage-temperature scalability. Both single-ended and differential output buffer circuit examples demonstrate that the proposed modeling method offers good accuracy and flexible scalability to facilitate signal integrity analysis.