{"title":"Symbolic analysis of large analog circuits with determinant decision diagrams","authors":"C. Shi, S. Tan","doi":"10.1109/ICCAD.1997.643562","DOIUrl":null,"url":null,"abstract":"Symbolic analog-circuit analysis has many applications, and is especially useful for analog synthesis and testability analysis. We present a new approach to exact and canonical symbolic analysis by exploiting the sparsity and sharing of product terms. It consists of representing the symbolic determinant of a circuit matrix by a graph-called determinant decision diagram (DDD)-and performing symbolic analysis by graph manipulations. We showed that DDD construction and DDD-based symbolic analysis can be performed in time complexity proportional to the number of DDD vertices. We described a vertex ordering heuristic, and showed that the number of DDD vertices can be quite small-usually orders-of-magnitude less than the number of product terms. The algorithm has been implemented. An order-of-magnitude improvement in both CPU time and memory usage over existing symbolic analyzers ISAAC and Maple-V has been observed for large analog circuits.","PeriodicalId":187521,"journal":{"name":"1997 Proceedings of IEEE International Conference on Computer Aided Design (ICCAD)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1997 Proceedings of IEEE International Conference on Computer Aided Design (ICCAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAD.1997.643562","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 33
Abstract
Symbolic analog-circuit analysis has many applications, and is especially useful for analog synthesis and testability analysis. We present a new approach to exact and canonical symbolic analysis by exploiting the sparsity and sharing of product terms. It consists of representing the symbolic determinant of a circuit matrix by a graph-called determinant decision diagram (DDD)-and performing symbolic analysis by graph manipulations. We showed that DDD construction and DDD-based symbolic analysis can be performed in time complexity proportional to the number of DDD vertices. We described a vertex ordering heuristic, and showed that the number of DDD vertices can be quite small-usually orders-of-magnitude less than the number of product terms. The algorithm has been implemented. An order-of-magnitude improvement in both CPU time and memory usage over existing symbolic analyzers ISAAC and Maple-V has been observed for large analog circuits.