{"title":"Multi-point model reductions of VLSI interconnects using the rational Arnoldi method with adaptive orders (RAMAO)","authors":"Herng-Jer Lee, C. Chu, W. Feng","doi":"10.1109/APCCAS.2004.1413052","DOIUrl":null,"url":null,"abstract":"This work proposes the rational Arnoldi method with adaptive orders for high-speed VLSI interconnect reductions. It is based on an extension of the classical multi-point Pade approximation by using the rational Arnoldi iteration approach. Given a set of expansion points, the transfer function error at each expansion point is derived first. In each iteration of the proposed algorithm, the expansion frequency corresponding to the maximum output moment error is chosen. The corresponding reduced-order model yields the greatest output moment improvement.","PeriodicalId":426683,"journal":{"name":"The 2004 IEEE Asia-Pacific Conference on Circuits and Systems, 2004. Proceedings.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2004 IEEE Asia-Pacific Conference on Circuits and Systems, 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCCAS.2004.1413052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This work proposes the rational Arnoldi method with adaptive orders for high-speed VLSI interconnect reductions. It is based on an extension of the classical multi-point Pade approximation by using the rational Arnoldi iteration approach. Given a set of expansion points, the transfer function error at each expansion point is derived first. In each iteration of the proposed algorithm, the expansion frequency corresponding to the maximum output moment error is chosen. The corresponding reduced-order model yields the greatest output moment improvement.