An enhanced optimization kernel for analog IC design automation using the shrinking circles technique

Abstract

This paper presents a novel sizing automation tool to improve the efficiency and accuracy of the analog IC design process. A new technique named the “shrinking circles” is proposed to create a balance between the exploration and exploitation capabilities when the optimization algorithm is converging to a possible optimum point. With the help of the shrinking circles concept, an upgraded version of Gravitational Search Algorithm (GSA) named Advanced GSA (AGSA) is proposed to be used as an optimization kernel for our circuit sizing tool. The performance of the proposed AGSA is evaluated over 23 benchmark functions and the results are compared with the standard GSA and Clustered-GSA algorithms. A two-stage op-amp in the 0.35µm CMOS technology is utilized to validate the performance of the proposed sizing tool. The corners analysis is also performed over the obtained solutions to guarantee their robustness against the process and environmental variations. Finally, a statistical study over the final solutions is conducted from the two aspects of quantitative and qualitative analyses.