{"title":"使用物理网络约束的定时驱动放置","authors":"Bill Halpin, C. Y. Chen, Naresh Sehgal","doi":"10.1145/378239.379065","DOIUrl":null,"url":null,"abstract":"This paper presents a new timing driven placement algorithm that explicitly meets physical net lengths constraints. It is the first recursive bi-section placement (RBP) algorithm that meets precise half perimeter bounding box constraints on critical nets. At each level of the recursive bi-section, we use linear programming to ensure that all net constraints are met. Our method can easily be incorporated with existing RBP methods. We use the net constraint based placer to improve timing results by setting and meeting constraints on timing critical nets. We report significantly better timing results on each of the MCNC benchmarks and achieve an average optimization exploitation of 69% versus previously reported 53%.","PeriodicalId":154316,"journal":{"name":"Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"63","resultStr":"{\"title\":\"Timing driven placement using physical net constraints\",\"authors\":\"Bill Halpin, C. Y. Chen, Naresh Sehgal\",\"doi\":\"10.1145/378239.379065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new timing driven placement algorithm that explicitly meets physical net lengths constraints. It is the first recursive bi-section placement (RBP) algorithm that meets precise half perimeter bounding box constraints on critical nets. At each level of the recursive bi-section, we use linear programming to ensure that all net constraints are met. Our method can easily be incorporated with existing RBP methods. We use the net constraint based placer to improve timing results by setting and meeting constraints on timing critical nets. We report significantly better timing results on each of the MCNC benchmarks and achieve an average optimization exploitation of 69% versus previously reported 53%.\",\"PeriodicalId\":154316,\"journal\":{\"name\":\"Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232)\",\"volume\":\"182 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"63\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/378239.379065\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/378239.379065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Timing driven placement using physical net constraints
This paper presents a new timing driven placement algorithm that explicitly meets physical net lengths constraints. It is the first recursive bi-section placement (RBP) algorithm that meets precise half perimeter bounding box constraints on critical nets. At each level of the recursive bi-section, we use linear programming to ensure that all net constraints are met. Our method can easily be incorporated with existing RBP methods. We use the net constraint based placer to improve timing results by setting and meeting constraints on timing critical nets. We report significantly better timing results on each of the MCNC benchmarks and achieve an average optimization exploitation of 69% versus previously reported 53%.