Zhonghua Jiang, N. Xu, Li Gao, Yuchun Ma, Xianlong Hong
{"title":"Hierarchical thermal model using gauss-seidel method in floorplanning","authors":"Zhonghua Jiang, N. Xu, Li Gao, Yuchun Ma, Xianlong Hong","doi":"10.1109/ICASIC.2007.4415819","DOIUrl":null,"url":null,"abstract":"Hierarchical design is employed in the floorplan for scaling to large number modules. The thermal problem has been emerged as one of the key issues for IC design. In this paper, we proposed an efficient hierarchical iterative Gauss-Seidel thermal model to guide the floorplan, which is an efficient algorithm that can reduce the run-time by speeding up the convergence with accurate estimation. Especially, the Gauss-Seidel Iteration is suitable for incremental temperature updating. Compared with inverting Matrix method, the iterative times of incremental Gauss-Seidel thermal model is approximate to 1/5 of the inverting Matrix method. Our method can be 5 times faster than that of the inverting Matrix method.","PeriodicalId":120984,"journal":{"name":"2007 7th International Conference on ASIC","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 7th International Conference on ASIC","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASIC.2007.4415819","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
Hierarchical design is employed in the floorplan for scaling to large number modules. The thermal problem has been emerged as one of the key issues for IC design. In this paper, we proposed an efficient hierarchical iterative Gauss-Seidel thermal model to guide the floorplan, which is an efficient algorithm that can reduce the run-time by speeding up the convergence with accurate estimation. Especially, the Gauss-Seidel Iteration is suitable for incremental temperature updating. Compared with inverting Matrix method, the iterative times of incremental Gauss-Seidel thermal model is approximate to 1/5 of the inverting Matrix method. Our method can be 5 times faster than that of the inverting Matrix method.