cVTS: A Constrained Voronoi Tree Search Method for High Dimensional Analog Circuit Synthesis
Aidong Zhao, Xianan Wang, Zixiao Lin, Zhaori Bi, Xudong Li, Changhao Yan, Fan Yang, Li Shang, Dian Zhou, Xuan Zeng
Abstract
A constrained Voronoi tree-based domain decomposition method for high-dimensional Bayesian optimization is proposed to solve large scale analog circuit synthesis problems, which can be formulated as high-dimensional heterogeneous black-box optimization. Hierarchical Voronoi tree progressively breaks down the design space into partitions with implicit performance boundaries such that promising regions are efficiently explored. Fast exploitation is ensured in Voronoi nest via local Bayesian optimization with a few observations. A slice-enhanced Gibbs sampling method is proposed to sample acquisition function cMES in irregular polyhedrons with design constraints. Compared with state-of-the-art methods, cVTS achieves significant speed up without loss of accuracy.