{"title":"带辅助变量的数据路径的符号遍历","authors":"G. Cabodi, P. Camurati, S. Quer","doi":"10.1109/GLSV.1994.289989","DOIUrl":null,"url":null,"abstract":"Symbolic state space traversal techniques are best on control-dominated circuits, not on data paths. This paper extends their applicability to regular structures commonly found in data paths by using auxiliary variables to decompose and to manipulate Boolean functions in decomposed form. Experimental results demonstrate the gain both in terms of binary decision diagram (BDD) size and CPU time.<<ETX>>","PeriodicalId":330584,"journal":{"name":"Proceedings of 4th Great Lakes Symposium on VLSI","volume":"201 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Symbolic traversals of data paths with auxiliary variables\",\"authors\":\"G. Cabodi, P. Camurati, S. Quer\",\"doi\":\"10.1109/GLSV.1994.289989\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Symbolic state space traversal techniques are best on control-dominated circuits, not on data paths. This paper extends their applicability to regular structures commonly found in data paths by using auxiliary variables to decompose and to manipulate Boolean functions in decomposed form. Experimental results demonstrate the gain both in terms of binary decision diagram (BDD) size and CPU time.<<ETX>>\",\"PeriodicalId\":330584,\"journal\":{\"name\":\"Proceedings of 4th Great Lakes Symposium on VLSI\",\"volume\":\"201 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 4th Great Lakes Symposium on VLSI\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GLSV.1994.289989\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 4th Great Lakes Symposium on VLSI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLSV.1994.289989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Symbolic traversals of data paths with auxiliary variables
Symbolic state space traversal techniques are best on control-dominated circuits, not on data paths. This paper extends their applicability to regular structures commonly found in data paths by using auxiliary variables to decompose and to manipulate Boolean functions in decomposed form. Experimental results demonstrate the gain both in terms of binary decision diagram (BDD) size and CPU time.<>