Validation of reduced-terminal models in fast SSN analysis

Abstract

Simultaneous switching noise (SSN) continues to play an important role in single-ended signaling systems. Modeling and simulating SSN is quite challenging as it requires a complex system model comprised of numerous signal, power, and ground conductors and planes. An efficient modeling approach based on the special property associated with SSN simulation assumptions was published previously. It assumed a worst case switching noise condition where all SSN aggressors were switching at the same time with same data pattern. Under this assumption, the complexity of the model is drastically reduced by introducing the supernet which is a non-physical net representing all the aggressors' impact. In this paper, we present numerical validation of the previous modeling approach.