{"title":"一种新的多终端RC网络稀疏保持模型降阶算法","authors":"Xin Chen, Lin Pan, Yangxin Xiang","doi":"10.1109/ASICON52560.2021.9620477","DOIUrl":null,"url":null,"abstract":"VLSI post-layout parasitic analysis demands more in fast simulation methods of huge and multi-terminal networks. Model order reduction (MOR) can settle for it by smaller model with approximating response at terminals, but destruction of system sparsity can slow down simulation speed a lot. To preserve sparsity, we introduce incomplete LU decomposition and pre-processing procedure into projection-based reduction methods. Experimental results show that the circuit simulation speed improves about 3X-11X with RMS error lower than 2e-3.","PeriodicalId":233584,"journal":{"name":"2021 IEEE 14th International Conference on ASIC (ASICON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Sparsity Preserving Model Order Reduction Algorithm for Multi-terminal RC Networks\",\"authors\":\"Xin Chen, Lin Pan, Yangxin Xiang\",\"doi\":\"10.1109/ASICON52560.2021.9620477\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"VLSI post-layout parasitic analysis demands more in fast simulation methods of huge and multi-terminal networks. Model order reduction (MOR) can settle for it by smaller model with approximating response at terminals, but destruction of system sparsity can slow down simulation speed a lot. To preserve sparsity, we introduce incomplete LU decomposition and pre-processing procedure into projection-based reduction methods. Experimental results show that the circuit simulation speed improves about 3X-11X with RMS error lower than 2e-3.\",\"PeriodicalId\":233584,\"journal\":{\"name\":\"2021 IEEE 14th International Conference on ASIC (ASICON)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 14th International Conference on ASIC (ASICON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASICON52560.2021.9620477\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 14th International Conference on ASIC (ASICON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASICON52560.2021.9620477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Sparsity Preserving Model Order Reduction Algorithm for Multi-terminal RC Networks
VLSI post-layout parasitic analysis demands more in fast simulation methods of huge and multi-terminal networks. Model order reduction (MOR) can settle for it by smaller model with approximating response at terminals, but destruction of system sparsity can slow down simulation speed a lot. To preserve sparsity, we introduce incomplete LU decomposition and pre-processing procedure into projection-based reduction methods. Experimental results show that the circuit simulation speed improves about 3X-11X with RMS error lower than 2e-3.