Evolution of Transistor Circuits


Analog circuit design is a discipline of electronic design, that demands a lot of knowledge and experience as well as a considerable amount of creativity in solving diverse problems from the designer and there are to date only rudimentary analytical solutions for parameterizing circuit topologies. Motivated by the latter challenges, this thesis focuses on the analog design automation for FPTA architectures by means of evolutionary algorithms (EAs). The advantages of using real hardware for circuit evolution are the significantly faster evaluation of candidate solutions compared to a simulator and the fact that found solutions are guaranteed to work on a real-world substrate. On the software side EAs are particularly well suited for analog circuit synthesis since they do not require prior knowledge of the optimization problem. New genetic operators are developed within this thesis aiming to facilitate the understanding of evolved FPTA circuits and to find solutions that can be transfered to other technologies. A great hope is thereby to possibly discover unusual, new design principles. Furthermore, a multi-objective algorithm is implemented and refined, in order to allow for taking the numerous variables into account, that are required for optimizing the topology and the dimensioning of transistor circuits. The proposed genetic operators and the multiobjective approach are successfully applied to the evolution of logic gates, comparators, oscillators and operational amplifiers. It is achieved to reduce the resource consumption of evolved circuits and in some cases it is possible to generate clear schematics of good solutions. A modular framework for the evolution of circuits on configurable substrates has been developed, which is used to perform the experiments and is further demonstrated to be useful for modeling FPTA architectures and subsequently using them in evolution experiments.