{"title":"NRG: global and detailed placement","authors":"M. Sarrafzadeh, Maogang Wang","doi":"10.1109/ICCAD.1997.643590","DOIUrl":null,"url":null,"abstract":"We present a new approach to the placement problem. The proposed approach consists of analyzing the input circuit and deciding on a two-dimensional global grid for that particular input. After determination of the grid size, the placement is carried out in three steps: global placement, detailed placement, and final optimization. We show that the output of the global placement can also serve as a fast and accurate predictor. Current implementation is based on simulated annealing. We have put all algorithms together in a placement package called NRG (pronounced N-er-G). In addition to area minimization, NRG can perform timing-driven placement. Experimental results are strong. We improve TimberWolf's results (version 1.2) by about 5%. Our predictor can estimate the wavelength within 10-20% accuracy offering 2-20x speedup compared with the actual placement algorithm.","PeriodicalId":187521,"journal":{"name":"1997 Proceedings of IEEE International Conference on Computer Aided Design (ICCAD)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"65","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1997 Proceedings of IEEE International Conference on Computer Aided Design (ICCAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAD.1997.643590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 65
Abstract
We present a new approach to the placement problem. The proposed approach consists of analyzing the input circuit and deciding on a two-dimensional global grid for that particular input. After determination of the grid size, the placement is carried out in three steps: global placement, detailed placement, and final optimization. We show that the output of the global placement can also serve as a fast and accurate predictor. Current implementation is based on simulated annealing. We have put all algorithms together in a placement package called NRG (pronounced N-er-G). In addition to area minimization, NRG can perform timing-driven placement. Experimental results are strong. We improve TimberWolf's results (version 1.2) by about 5%. Our predictor can estimate the wavelength within 10-20% accuracy offering 2-20x speedup compared with the actual placement algorithm.