{"title":"基于单节点SOR法的电力/地面网络统计分析","authors":"Zuying Luo, S. Tan","doi":"10.1109/ISQED.2008.62","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an efficient statistical analysis method for analyzing on-chip power grids. The new method, called SN-SOR (and its faster version, PSN- SOR), is based on a novel localized relaxed iterative approach and it can perform variational analysis on one node at a time. PSN-SOR further speeds up the analysis by using a refined conditioner, where the initial solution of SN-SOR is used as the pre-conditioner for the later iterations. Experimental results show that PSN-SOR is about two orders of magnitude(186X) faster than Monte- Carlo method with slight errors less than 5.685% on maximum and is about one order magnitude (41X) faster than general global successive over relaxation (SOR) method. PSN-SOR is more accurate and efficient than the recently proposed random walk method for localized statistical analysis.","PeriodicalId":243121,"journal":{"name":"9th International Symposium on Quality Electronic Design (isqed 2008)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Statistic Analysis of Power/Ground Networks Using Single-Node SOR Method\",\"authors\":\"Zuying Luo, S. Tan\",\"doi\":\"10.1109/ISQED.2008.62\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose an efficient statistical analysis method for analyzing on-chip power grids. The new method, called SN-SOR (and its faster version, PSN- SOR), is based on a novel localized relaxed iterative approach and it can perform variational analysis on one node at a time. PSN-SOR further speeds up the analysis by using a refined conditioner, where the initial solution of SN-SOR is used as the pre-conditioner for the later iterations. Experimental results show that PSN-SOR is about two orders of magnitude(186X) faster than Monte- Carlo method with slight errors less than 5.685% on maximum and is about one order magnitude (41X) faster than general global successive over relaxation (SOR) method. PSN-SOR is more accurate and efficient than the recently proposed random walk method for localized statistical analysis.\",\"PeriodicalId\":243121,\"journal\":{\"name\":\"9th International Symposium on Quality Electronic Design (isqed 2008)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"9th International Symposium on Quality Electronic Design (isqed 2008)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISQED.2008.62\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"9th International Symposium on Quality Electronic Design (isqed 2008)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISQED.2008.62","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistic Analysis of Power/Ground Networks Using Single-Node SOR Method
In this paper, we propose an efficient statistical analysis method for analyzing on-chip power grids. The new method, called SN-SOR (and its faster version, PSN- SOR), is based on a novel localized relaxed iterative approach and it can perform variational analysis on one node at a time. PSN-SOR further speeds up the analysis by using a refined conditioner, where the initial solution of SN-SOR is used as the pre-conditioner for the later iterations. Experimental results show that PSN-SOR is about two orders of magnitude(186X) faster than Monte- Carlo method with slight errors less than 5.685% on maximum and is about one order magnitude (41X) faster than general global successive over relaxation (SOR) method. PSN-SOR is more accurate and efficient than the recently proposed random walk method for localized statistical analysis.