Robust automated synthesis methodology for integrated spiral inductors with variability

In order to synthesize spiral inductor designs to meet stringent design requirements, fundamental trade-offs in the design space must be analyzed and exploited. In this paper, we develop a robust automated synthesis methodology to efficiently generate spiral inductor designs using multi-objective optimization techniques and surrogate functions to approximate Pareto surfaces in the design space. Using our synthesis methodology, we also demonstrate how to reduce the impact of process variation and other sources of modeling error on spiral inductors. Our results indicate that our synthesis methodology efficiently optimizes inductor designs based on the application´s design requirements with an improvement of up to 51% in key inductor design constraints while reducing the impact of process and model variations.