Optimization in Electronic Design Automation

(I) Definition of terms and overview of optimization methods. Unconstrained methods: first and second order gradient-based algorithms, direct algorithms and metaheuristics. Constrained methods: parameter constrains and penalty functions. Definition of analog circuit sensitivity and its role in gradient-based algorithms. Optimization of circuit topology.

(II) Parametric optimization. Measurement definition and cost function formulation. Properties of cost functions. Nominal optimization. Effect of operating parameters and random manufacturing variations. Optimization across corners. Worst case analysis. Yield and yield optimization. A demo run of an optimization tool and result interpretation.

(III) A medium size circuit is run by each student on a personal computer. Parallelization of the optimization process. A large analog optimization case is run on a computer farm and the results are analyzed.

Theoretical knowledge of optimization procedures in EDA. Gaining practical experience with a circuit optimization tool.

Individual consultation, directed seminar work, independent project work.