Leonard Lee, Li-C. Wang, Praveen Parvathala, T. M. Mak
{"title":"On silicon-based speed path identification","authors":"Leonard Lee, Li-C. Wang, Praveen Parvathala, T. M. Mak","doi":"10.1109/VTS.2005.61","DOIUrl":null,"url":null,"abstract":"Speed path identification is an indispensable step for pushing the design timing wall and for developing the final speed binning strategy in production test. For complex high-performance designs, pre-silicon timing tools have so far not been able to deliver satisfactory results in predicting the actual speed limiting paths on the silicon. The actual speed paths are mostly uncovered through test and silicon debug, where tremendous manual effort is involved. This paper presents a novel approach as the first step for automating the speed path identification process. Our approach is silicon-based, meaning that timing information is extracted through testing of silicon sample chips. We call this step silicon learning. Based on silicon learning, we present an iterative flow for speed path identification. Experimental results are presented to explain the new methodologies and to demonstrate the effectiveness of our techniques.","PeriodicalId":268324,"journal":{"name":"23rd IEEE VLSI Test Symposium (VTS'05)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"23rd IEEE VLSI Test Symposium (VTS'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VTS.2005.61","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 40
Abstract
Speed path identification is an indispensable step for pushing the design timing wall and for developing the final speed binning strategy in production test. For complex high-performance designs, pre-silicon timing tools have so far not been able to deliver satisfactory results in predicting the actual speed limiting paths on the silicon. The actual speed paths are mostly uncovered through test and silicon debug, where tremendous manual effort is involved. This paper presents a novel approach as the first step for automating the speed path identification process. Our approach is silicon-based, meaning that timing information is extracted through testing of silicon sample chips. We call this step silicon learning. Based on silicon learning, we present an iterative flow for speed path identification. Experimental results are presented to explain the new methodologies and to demonstrate the effectiveness of our techniques.