{"title":"A novel three phase parallel genetic approach to routing for field programmable gate arrays","authors":"A. Muthukaruppan, S. Suresh, V. Kamakoti","doi":"10.1109/FPT.2002.1188705","DOIUrl":null,"url":null,"abstract":"This paper establishes a handshake between the fields of \"parallel genetic algorithms\" and reconfigurable systems, to provide a solution for the routing problem for FPGAs, that attempts to enhance the performance of the circuit implemented by the FPGA. We propose to solve the problem of routing for FPGAs in three phases, out of which the first two utilize the concept of genetic algorithms to transform an initial population of random suggested routings to a population that contains solutions approximating the optimal one.","PeriodicalId":355740,"journal":{"name":"2002 IEEE International Conference on Field-Programmable Technology, 2002. (FPT). Proceedings.","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 IEEE International Conference on Field-Programmable Technology, 2002. (FPT). Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPT.2002.1188705","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper establishes a handshake between the fields of "parallel genetic algorithms" and reconfigurable systems, to provide a solution for the routing problem for FPGAs, that attempts to enhance the performance of the circuit implemented by the FPGA. We propose to solve the problem of routing for FPGAs in three phases, out of which the first two utilize the concept of genetic algorithms to transform an initial population of random suggested routings to a population that contains solutions approximating the optimal one.