Development of robust interconnect model based on design of experiments and multiobjective optimization

When designing an integrated circuit, it is important to take into consider ation random variations arising from process variability. Traditional optim ization studies on VLSI interconnect attempt to find the deterministic opti mum of a cost function but do not take into account the effect of these ran dom variations on the objective. We have developed an effective methodology based on TCAD simulation and design of experiments to optimize interconnec t including the effects of process variations. The aim of the study is to s earch for optimum designs that both meet the performance specification and are robust with respect to process variations. A multiobjective optimizatio n technique known as Normal Boundary Intersection is used to find evenly-sp aced tradeoff points on the Pareto curve. Designers can then select designs from the curve without using arbitrary weighting parameters. The proposed methodology was applied to a 0.12 mum CMOS technology; optimization results are discussed and verified using Monte Carlo simulation.