基于聚类的K-way谱划分线性排序算法

Proceedings of the ASP-DAC '99 Asia and South Pacific Design Automation Conference 1999 (Cat. No.99EX198) Pub Date : 1999-01-18 DOI:10.1109/ASPDAC.1999.759714

Shiuann-Shiuh Lin, Wen-Hsin Chen, Wen-Wei Lin, TingTing Hwang

{"title":"基于聚类的K-way谱划分线性排序算法","authors":"Shiuann-Shiuh Lin, Wen-Hsin Chen, Wen-Wei Lin, TingTing Hwang","doi":"10.1109/ASPDAC.1999.759714","DOIUrl":null,"url":null,"abstract":"The spectral method can lead to a high quality of multi-way partition due to its ability to capture global netlist information. For spectral partition, n netlist modules are mapped to n points in d-dimensional space, and then a linear ordering of these n modules is constructed to be used as a basis for partitioning. In this paper, we propose two clustering based linear ordering algorithms taking into consideration the objective function presented.","PeriodicalId":201352,"journal":{"name":"Proceedings of the ASP-DAC '99 Asia and South Pacific Design Automation Conference 1999 (Cat. No.99EX198)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A clustering based linear ordering algorithm for K-way spectral partitioning\",\"authors\":\"Shiuann-Shiuh Lin, Wen-Hsin Chen, Wen-Wei Lin, TingTing Hwang\",\"doi\":\"10.1109/ASPDAC.1999.759714\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The spectral method can lead to a high quality of multi-way partition due to its ability to capture global netlist information. For spectral partition, n netlist modules are mapped to n points in d-dimensional space, and then a linear ordering of these n modules is constructed to be used as a basis for partitioning. In this paper, we propose two clustering based linear ordering algorithms taking into consideration the objective function presented.\",\"PeriodicalId\":201352,\"journal\":{\"name\":\"Proceedings of the ASP-DAC '99 Asia and South Pacific Design Automation Conference 1999 (Cat. No.99EX198)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-01-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ASP-DAC '99 Asia and South Pacific Design Automation Conference 1999 (Cat. No.99EX198)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASPDAC.1999.759714\",\"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 ASP-DAC '99 Asia and South Pacific Design Automation Conference 1999 (Cat. No.99EX198)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASPDAC.1999.759714","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

谱法由于能够捕获全局网表信息，可以实现高质量的多路分割。对于谱划分，将n个网表模块映射到d维空间中的n个点，然后构造这n个模块的线性排序作为划分的基础。本文在考虑目标函数的基础上，提出了两种基于聚类的线性排序算法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A clustering based linear ordering algorithm for K-way spectral partitioning

The spectral method can lead to a high quality of multi-way partition due to its ability to capture global netlist information. For spectral partition, n netlist modules are mapped to n points in d-dimensional space, and then a linear ordering of these n modules is constructed to be used as a basis for partitioning. In this paper, we propose two clustering based linear ordering algorithms taking into consideration the objective function presented.

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

Proceedings of the ASP-DAC '99 Asia and South Pacific Design Automation Conference 1999 (Cat. No.99EX198)

自引率

0.00%

发文量