{"title":"一种用于电力和地网分析的压缩bicstab算法","authors":"Haohang Su, Yimen Zhang, Yuming Zhang, Jincai Man","doi":"10.1109/ICASIC.2007.4415858","DOIUrl":null,"url":null,"abstract":"An effective method is proposed based on compressed BiCGStab approaches to perform static and transient simulations for large-scale power and ground network circuits and a good result is obtained. Extensive experimental results on large-scale power and ground network show that presented method is over two orders faster than HSPICE in transient simulations. Furthermore, our algorithm reduces over 95% of memory usage than HSPICE and 75% of memory usage than ICCG while the accuracy is not compromised.","PeriodicalId":120984,"journal":{"name":"2007 7th International Conference on ASIC","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A compressed BiCGStab algorithm for power and ground network analysis\",\"authors\":\"Haohang Su, Yimen Zhang, Yuming Zhang, Jincai Man\",\"doi\":\"10.1109/ICASIC.2007.4415858\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An effective method is proposed based on compressed BiCGStab approaches to perform static and transient simulations for large-scale power and ground network circuits and a good result is obtained. Extensive experimental results on large-scale power and ground network show that presented method is over two orders faster than HSPICE in transient simulations. Furthermore, our algorithm reduces over 95% of memory usage than HSPICE and 75% of memory usage than ICCG while the accuracy is not compromised.\",\"PeriodicalId\":120984,\"journal\":{\"name\":\"2007 7th International Conference on ASIC\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 7th International Conference on ASIC\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASIC.2007.4415858\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 7th International Conference on ASIC","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASIC.2007.4415858","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A compressed BiCGStab algorithm for power and ground network analysis
An effective method is proposed based on compressed BiCGStab approaches to perform static and transient simulations for large-scale power and ground network circuits and a good result is obtained. Extensive experimental results on large-scale power and ground network show that presented method is over two orders faster than HSPICE in transient simulations. Furthermore, our algorithm reduces over 95% of memory usage than HSPICE and 75% of memory usage than ICCG while the accuracy is not compromised.
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