M. Abu-Rahma, K. Chowdhury, Joseph Wang, Zhiqin Chen, S. Yoon, M. Anis
{"title":"A methodology for statistical estimation of read access yield in SRAMs","authors":"M. Abu-Rahma, K. Chowdhury, Joseph Wang, Zhiqin Chen, S. Yoon, M. Anis","doi":"10.1145/1391469.1391522","DOIUrl":null,"url":null,"abstract":"The increase of process variations in advanced CMOS technologies is considered one of the biggest challenges for SRAM designers. This is aggravated by the strong demand for lower cost and power consumption, higher performance and density which complicates SRAM design process. In this paper, we present a methodology for statistical simulation of SRAM read access yield, which is tightly related to SRAM performance and power consumption. The proposed flow enables early SRAM yield predication and performance/power optimization in the design time, which is important for SRAM in nanometer technologies. The methodology is verified using measured silicon yield data from a 1 Mb memory fabricated in an industrial 45 nm technology.","PeriodicalId":412696,"journal":{"name":"2008 45th ACM/IEEE Design Automation Conference","volume":"189 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 45th ACM/IEEE Design Automation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1391469.1391522","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32
Abstract
The increase of process variations in advanced CMOS technologies is considered one of the biggest challenges for SRAM designers. This is aggravated by the strong demand for lower cost and power consumption, higher performance and density which complicates SRAM design process. In this paper, we present a methodology for statistical simulation of SRAM read access yield, which is tightly related to SRAM performance and power consumption. The proposed flow enables early SRAM yield predication and performance/power optimization in the design time, which is important for SRAM in nanometer technologies. The methodology is verified using measured silicon yield data from a 1 Mb memory fabricated in an industrial 45 nm technology.