Scalable driver I/O macromodels for statistical analysis

Abstract

In this paper, scalable driver I/O macromodels have been proposed for efficient signal integrity and timing analysis of today's high-speed systems. Variations in semiconductor process, temperature, and power supply voltage affect the output voltage and current in driver circuits. The effect of these variations on driver and receiver circuits has been captured using Lagrange's interpolation technique. In this paper, scalable macromodeling approach has been applied to differential driver circuits and single-ended driver and receiver circuits. Scalable driver and receiver circuits consume less CPU memory and simulation time compared to transistor-level driver and receiver circuits. The accuracy of scalable macromodels has been tested on various test cases for differential driver and single-ended driver-receiver circuits and results yielded good accuracy.