F. Durbin, J. Haussy, G. Berthiau, P. Siarry, W.M. Zuberek
{"title":"Integrated circuit performance optimization with simulated annealing algorithm and SPICE-PAC circuit simulator","authors":"F. Durbin, J. Haussy, G. Berthiau, P. Siarry, W.M. Zuberek","doi":"10.1109/EASIC.1990.207978","DOIUrl":null,"url":null,"abstract":"The circuit design problem consists in determining acceptable parameter values (resistors, capacitors, transistor geometries . . .) which allow the circuit to meet various user given operational criteria (DC consumption, AC bandwidth, transient rise times, etc.). This task is equivalent to a multidimensional and/or multi objective optimization problem: n-variables functions have to be minimized in an hyperrectangular domain: equality and/or inequality constraints can be eventually specified. The authors propose an efficient algorithm, based on the repeated application of simulated annealing to a certain number of p-variables sub problems, with p<<n. Objective functions are computed through the modular SPICE-PAC simulator, which is controlled by the optimization algorithm.<<ETX>>","PeriodicalId":205695,"journal":{"name":"[Proceedings] EURO ASIC `90","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] EURO ASIC `90","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EASIC.1990.207978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The circuit design problem consists in determining acceptable parameter values (resistors, capacitors, transistor geometries . . .) which allow the circuit to meet various user given operational criteria (DC consumption, AC bandwidth, transient rise times, etc.). This task is equivalent to a multidimensional and/or multi objective optimization problem: n-variables functions have to be minimized in an hyperrectangular domain: equality and/or inequality constraints can be eventually specified. The authors propose an efficient algorithm, based on the repeated application of simulated annealing to a certain number of p-variables sub problems, with p<>