{"title":"基于遗传算法的相声驱动布局","authors":"Masaya Yoshikawa, H. Terai","doi":"10.1109/CIMSA.2004.1397233","DOIUrl":null,"url":null,"abstract":"Deep-Sub-Micron (DSM) technologies of 0.18 micron and below enable the integration of logical circuits having more than 10 million gates. In such a DSM technology, it's important to consider improving crosstalk noise at initial phase of layout design. In this paper, we proposed a novel crosstalk-driven placement algorithm. The proposed algorithm based on genetic algorithm (GA) has a two-level hierarchical structure. For selection control, new objective functions are introduced for improving crosstalk noise, reducing power consumption, improving interconnection delay and dispersing wire congestion. Studies on floor planning and cell placement have been reported as being applications of GA to the LSI layout problem. However, no studies have ever seen the effect of applying GA in consideration of power, delay and congestion. Results show improvement of 6.7% for crosstalk noise on average.","PeriodicalId":102405,"journal":{"name":"2004 IEEE International Conference onComputational Intelligence for Measurement Systems and Applications, 2004. CIMSA.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Crosstalk-driven placement based on genetic algorithms\",\"authors\":\"Masaya Yoshikawa, H. Terai\",\"doi\":\"10.1109/CIMSA.2004.1397233\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep-Sub-Micron (DSM) technologies of 0.18 micron and below enable the integration of logical circuits having more than 10 million gates. In such a DSM technology, it's important to consider improving crosstalk noise at initial phase of layout design. In this paper, we proposed a novel crosstalk-driven placement algorithm. The proposed algorithm based on genetic algorithm (GA) has a two-level hierarchical structure. For selection control, new objective functions are introduced for improving crosstalk noise, reducing power consumption, improving interconnection delay and dispersing wire congestion. Studies on floor planning and cell placement have been reported as being applications of GA to the LSI layout problem. However, no studies have ever seen the effect of applying GA in consideration of power, delay and congestion. Results show improvement of 6.7% for crosstalk noise on average.\",\"PeriodicalId\":102405,\"journal\":{\"name\":\"2004 IEEE International Conference onComputational Intelligence for Measurement Systems and Applications, 2004. CIMSA.\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 IEEE International Conference onComputational Intelligence for Measurement Systems and Applications, 2004. CIMSA.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIMSA.2004.1397233\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 IEEE International Conference onComputational Intelligence for Measurement Systems and Applications, 2004. CIMSA.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMSA.2004.1397233","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Crosstalk-driven placement based on genetic algorithms
Deep-Sub-Micron (DSM) technologies of 0.18 micron and below enable the integration of logical circuits having more than 10 million gates. In such a DSM technology, it's important to consider improving crosstalk noise at initial phase of layout design. In this paper, we proposed a novel crosstalk-driven placement algorithm. The proposed algorithm based on genetic algorithm (GA) has a two-level hierarchical structure. For selection control, new objective functions are introduced for improving crosstalk noise, reducing power consumption, improving interconnection delay and dispersing wire congestion. Studies on floor planning and cell placement have been reported as being applications of GA to the LSI layout problem. However, no studies have ever seen the effect of applying GA in consideration of power, delay and congestion. Results show improvement of 6.7% for crosstalk noise on average.