{"title":"可预测性:定义、分析和优化","authors":"Ankur Srivastava, M. Sarrafzadeh","doi":"10.1145/774572.774589","DOIUrl":null,"url":null,"abstract":"Predictability is the quantified from of accuracy. We propose a predictability driven design methodology. The novelty lies in defining and using the idea of predictability. In order to illustrate the basic concepts we focus on the low power binding problem. The binding problem for low power was solved in [3], [5], but in the presence of in-accuracies, their claims of optimality are imprecise. Our experiments show that these inaccuracies could be as high as 33%. Our methodology could improve this unpredictability to as low as 11% with minimal power penalty (7% on average).","PeriodicalId":142229,"journal":{"name":"International Workshop on Logic & Synthesis","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Predictability: definition, ananlysis and optimization\",\"authors\":\"Ankur Srivastava, M. Sarrafzadeh\",\"doi\":\"10.1145/774572.774589\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Predictability is the quantified from of accuracy. We propose a predictability driven design methodology. The novelty lies in defining and using the idea of predictability. In order to illustrate the basic concepts we focus on the low power binding problem. The binding problem for low power was solved in [3], [5], but in the presence of in-accuracies, their claims of optimality are imprecise. Our experiments show that these inaccuracies could be as high as 33%. Our methodology could improve this unpredictability to as low as 11% with minimal power penalty (7% on average).\",\"PeriodicalId\":142229,\"journal\":{\"name\":\"International Workshop on Logic & Synthesis\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Logic & Synthesis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/774572.774589\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Logic & Synthesis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/774572.774589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predictability: definition, ananlysis and optimization
Predictability is the quantified from of accuracy. We propose a predictability driven design methodology. The novelty lies in defining and using the idea of predictability. In order to illustrate the basic concepts we focus on the low power binding problem. The binding problem for low power was solved in [3], [5], but in the presence of in-accuracies, their claims of optimality are imprecise. Our experiments show that these inaccuracies could be as high as 33%. Our methodology could improve this unpredictability to as low as 11% with minimal power penalty (7% on average).