Multi-Objective Optimization Algorithms for Automated Circuit Sizing of Analog/ Mixed-Signal Circuits
Marius Stănescu, Cătălin Vișan, Gabriel Sandu, Horia Cucu, Cristian Diaconu, Andi Buzo, Georg Pelz
Abstract
Manual circuit design involves a time-consuming sizing task that diverts the highly skilled analog designers from creative work to a trial-and-error process. To reduce R&D costs and speed-up the time to market, this process can be automatized using artificial intelligence. In this paper we evaluate the most promising five Evolutionary Algorithms in the context of circuit sizing in a multi-objective optimization scenario. We calibrate their hyperparameters by performing a grid search on synthetic benchmarks and we compare the performance of the algorithms on a real voltage regulator.
Topics & Concepts
SizingComputer scienceContext (archaeology)HyperparameterMixed-signal integrated circuitProcess (computing)Electronic circuitSIGNAL (programming language)Analogue electronicsGridAlgorithmIntegrated circuitEngineeringElectrical engineeringMathematicsOperating systemPaleontologyBiologyProgramming languageGeometryArtVisual artsAdvanced Multi-Objective Optimization AlgorithmsVLSI and FPGA Design TechniquesEvolutionary Algorithms and Applications