Modeling the Effects of Systematic Process Variation on Circuit Performance

As technology scales, understanding semiconductor manufacturing variation becomes essential to effectively design high performance circuits. Knowledge of process variation is important to optimize critical path delay, minimize clock skew, and reduce crosstalk noise. Conventional circuit techniques typically represent the interconnect and device parameter variations as random variables. However, recent studies have shown that strong spatial pattern dependencies exist, especially when considering interconnect variation in chemical mechanical polishing (CMP) processes. Therefore, the total variation can be separated into systematic and random components, where a significant portion of the variation can be modeled based on layout characteristics. Modeling the systematic components of different variation sources and implementing these effects in circuit simulation are key to reduce design uncertainty and maximize circuit performance. This thesis presents a methodology to incorporate systematic pattern dependent interconnec