A. Magnani, M. de Magistris, A. Maffucci, A. Todri-Sanial
{"title":"A node clustering reduction scheme for power grids electrothermal analysis","authors":"A. Magnani, M. de Magistris, A. Maffucci, A. Todri-Sanial","doi":"10.1109/SAPIW.2015.7237399","DOIUrl":null,"url":null,"abstract":"This paper presents a new technique to lower the computational cost of the electrothermal (ET) analysis of a large on-chip power distribution network. It is based on a node reduction strategy following a preliminary efficient steady-state solution of the ET problem. After a proper classification of nodes according to temperature and voltage drop ranges, a reduced network is then produced by means of clustering and topological network transformations, and is available for any static/dynamic analysis. Due to the achievable reduction ratios, it possible to lower by order of magnitudes the computational cost at very good accuracies. A case-study is provided where a power grid of 4 millions of nodes is reduced by a factor of 180 (electrical network) and 500 (thermal network).","PeriodicalId":231437,"journal":{"name":"2015 IEEE 19th Workshop on Signal and Power Integrity (SPI)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 19th Workshop on Signal and Power Integrity (SPI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAPIW.2015.7237399","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper presents a new technique to lower the computational cost of the electrothermal (ET) analysis of a large on-chip power distribution network. It is based on a node reduction strategy following a preliminary efficient steady-state solution of the ET problem. After a proper classification of nodes according to temperature and voltage drop ranges, a reduced network is then produced by means of clustering and topological network transformations, and is available for any static/dynamic analysis. Due to the achievable reduction ratios, it possible to lower by order of magnitudes the computational cost at very good accuracies. A case-study is provided where a power grid of 4 millions of nodes is reduced by a factor of 180 (electrical network) and 500 (thermal network).