基于序列对的交叉操作集成电路设计

M. Yoshikawa, H. Terai
{"title":"基于序列对的交叉操作集成电路设计","authors":"M. Yoshikawa, H. Terai","doi":"10.1109/ISEFS.2006.251171","DOIUrl":null,"url":null,"abstract":"The floorplanning problem, which is an essential design step in VLSI layout design, consists of determining the placement of rectangular modules as densely as possible. Many studies have been carried out on this problem using sequence pairs based on genetic algorithms (GAs). However, the GA-based method generally requires a great amount of computation time. Therefore, we propose the architecture for high speed floorplanning using a sequence pair based on GA. In this paper, the proposed architecture is implemented on LSI, and achieves high speed processing","PeriodicalId":269492,"journal":{"name":"2006 International Symposium on Evolving Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2006-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design of LSI for crossover operation based on sequence pair\",\"authors\":\"M. Yoshikawa, H. Terai\",\"doi\":\"10.1109/ISEFS.2006.251171\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The floorplanning problem, which is an essential design step in VLSI layout design, consists of determining the placement of rectangular modules as densely as possible. Many studies have been carried out on this problem using sequence pairs based on genetic algorithms (GAs). However, the GA-based method generally requires a great amount of computation time. Therefore, we propose the architecture for high speed floorplanning using a sequence pair based on GA. In this paper, the proposed architecture is implemented on LSI, and achieves high speed processing\",\"PeriodicalId\":269492,\"journal\":{\"name\":\"2006 International Symposium on Evolving Fuzzy Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Symposium on Evolving Fuzzy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISEFS.2006.251171\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Symposium on Evolving Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISEFS.2006.251171","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

平面规划问题是VLSI布局设计中必不可少的设计步骤,它包括确定尽可能密集的矩形模块的放置位置。利用基于遗传算法(GAs)的序列对对该问题进行了许多研究。然而,基于遗传算法的方法通常需要大量的计算时间。因此,我们提出了一种基于遗传算法的序列对高速平面规划体系结构。本文将该架构实现在大规模集成电路上,实现了高速处理
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Design of LSI for crossover operation based on sequence pair
The floorplanning problem, which is an essential design step in VLSI layout design, consists of determining the placement of rectangular modules as densely as possible. Many studies have been carried out on this problem using sequence pairs based on genetic algorithms (GAs). However, the GA-based method generally requires a great amount of computation time. Therefore, we propose the architecture for high speed floorplanning using a sequence pair based on GA. In this paper, the proposed architecture is implemented on LSI, and achieves high speed processing
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Comparison of Search Ability between Genetic Fuzzy Rule Selection and Fuzzy Genetics-Based Machine Learning Recognition of Different Operating States in Complex Systems by Use of Growing Neural Models Spatial Interpolation of Traffic Data by Genetic Fuzzy System Pruning for interpretability of large spanned eTS Learning Methods for Intelligent Evolving Systems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1