{"title":"基于空间、时间和参数制程可变性模型的65nm SOI CMOS电池宽带引擎性能和良率基准","authors":"Choongyeun Cho, D.D. Kim, Jonghae Kim","doi":"10.1109/ASSCC.2008.4708719","DOIUrl":null,"url":null,"abstract":"This paper introduces a process variability model to determine the performance and yield of the cell broadband engine (CBE) in 65 nm SOI CMOS. The model incorporates spatial (die-to-die), temporal (manufacturing process drift), and parametric dimensions, and provides microprocessor performance tracking and comprehensive view on the process variability with embedded ring oscillator measurement at the wafer level. It extracts CBE performance regularity within die for the circuit design and models, and reveals the semiconductor manufacturing signatures in wafers and lots for process technology. The model reduces performance estimation testing requirements by surpassing conventional methodspsila accuracy by 28%.","PeriodicalId":143173,"journal":{"name":"2008 IEEE Asian Solid-State Circuits Conference","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Cell Broadband Engine performance and yield benchmark in 65nm SOI CMOS with spatial, temporal and parametric process variability model\",\"authors\":\"Choongyeun Cho, D.D. Kim, Jonghae Kim\",\"doi\":\"10.1109/ASSCC.2008.4708719\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a process variability model to determine the performance and yield of the cell broadband engine (CBE) in 65 nm SOI CMOS. The model incorporates spatial (die-to-die), temporal (manufacturing process drift), and parametric dimensions, and provides microprocessor performance tracking and comprehensive view on the process variability with embedded ring oscillator measurement at the wafer level. It extracts CBE performance regularity within die for the circuit design and models, and reveals the semiconductor manufacturing signatures in wafers and lots for process technology. The model reduces performance estimation testing requirements by surpassing conventional methodspsila accuracy by 28%.\",\"PeriodicalId\":143173,\"journal\":{\"name\":\"2008 IEEE Asian Solid-State Circuits Conference\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE Asian Solid-State Circuits Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASSCC.2008.4708719\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Asian Solid-State Circuits Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASSCC.2008.4708719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
本文介绍了一种工艺变化模型,用于确定65nm SOI CMOS小区宽带引擎(CBE)的性能和良率。该模型结合了空间(模对模),时间(制造过程漂移)和参数维度,并提供微处理器性能跟踪和在晶圆级上使用嵌入式环形振荡器测量的过程可变性的全面视图。为电路设计和模型提取芯片内部CBE性能规律,为工艺技术揭示晶圆和批次中的半导体制造特征。该模型降低了性能评估测试的要求,比传统方法的准确率提高了28%。
Cell Broadband Engine performance and yield benchmark in 65nm SOI CMOS with spatial, temporal and parametric process variability model
This paper introduces a process variability model to determine the performance and yield of the cell broadband engine (CBE) in 65 nm SOI CMOS. The model incorporates spatial (die-to-die), temporal (manufacturing process drift), and parametric dimensions, and provides microprocessor performance tracking and comprehensive view on the process variability with embedded ring oscillator measurement at the wafer level. It extracts CBE performance regularity within die for the circuit design and models, and reveals the semiconductor manufacturing signatures in wafers and lots for process technology. The model reduces performance estimation testing requirements by surpassing conventional methodspsila accuracy by 28%.