GASPAD: A General and Efficient mm-Wave Integrated Circuit Synthesis Method Based on Surrogate Model Assisted Evolutionary Algorithm

Abstract

The design and optimization (both sizing and layout) of mm-wave integrated circuits (ICs) have attracted much attention due to the growing demand in industry. However, available manual design and synthesis methods suffer from a high dependence on design experience, being inefficient or not general enough. To address this problem, a new method, called general mm-wave IC synthesis based on Gaussian process model assisted differential evolution (GASPAD), is proposed in this paper. A medium-scale computationally expensive constrained optimization problem must be solved for the targeted mm-wave IC design problem. Besides the basic techniques of using a global optimization algorithm to obtain highly optimized design solutions and using surrogate models to obtain a high efficiency, a surrogate model-aware search mechanism (SMAS) for tackling the several tens of design variables (medium scale) and a method to appropriately integrate constraint handling techniques into SMAS for tackling the multiple (high-) performance specifications are proposed. Experiments on two 60 GHz power amplifiers in a 65 nm CMOS technology and two mathematical benchmark problems are carried out. Comparisons with the state-of-art provide evidence of the important advantages of GASPAD in terms of solution quality and efficiency.