Trustworthy Genetic Programming-Based Synthesis of Analog Circuit Topologies Using Hierarchical Domain-Specific Building Blocks

• Published in: IEEE transactions on evolutionary computation Vol. 15; no. 4; pp. 557 - 570
• Main Authors: McConaghy, T., Palmers, P., Steyaert, M., Gielen, G. G. E.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2011; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analog; Analog circuits; Applied sciences; Artificial intelligence; Automation; Computer science; control theory; systems; Construction; Design automation; Electronics; evolutionary algorithm (EA); Evolutionary algorithms; Exact sciences and technology; Grammar; integrated circuit (IC); Integrated circuit modeling; Integrated circuits; Integrated circuits by function (including memories and processors); Manufacturing engineering; multiobjective optimization; Searching; Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices; Semiconductor process modeling; Solid modeling; Synthesis; Topology; Analog circuit; Motor car; Evolutionary algorithm; Multiobjective programming; Optimization; Robotics; multiobjective optimization; Confidence; Age; Automation; Operational amplifier; evolutionary algorithm (EA); Topology; Experimental study; Population balance; Search algorithm; design automation; Genetic algorithm; Analog; Integrated circuit; Context free grammar; Circuit synthesis; Hierarchical system; integrated circuit (IC); Molecular biology; Heterostructures
• ISSN: 1089-778X; 1941-0026
• DOI: 10.1109/TEVC.2010.2093581

This paper presents MOJITO, a system that performs structural synthesis of analog circuits, returning designs that are trustworthy by construction. The search space is defined by a set of expert-specified, trusted, hierarchically-organized analog building blocks, which are organized as a parameterized context-free grammar. The search algorithm is a multiobjective evolutionary algorithm that uses an age-layered population structure to balance exploration versus exploitation. It is validated with experiments to search across >;100 000 different one-stage and two-stage opamp topologies, returning human-competitive results. The runtime is orders of magnitude faster than open-ended systems, and unlike the other evolutionary algorithm approaches, the resulting circuits are trustworthy by construction. The approach generalizes to other problem domains which have accumulated structural domain knowledge, such as robotic structures, car assemblies, and modeling biological systems.