SHF: Medium: Collaborative Research: System Level Self Correction Using On-Chip Micro Sensor Network and Autonomous Feedback Control

SHF：中：协作研究：使用片上微传感器网络和自主反馈控制的系统级自我校正

• 批准号: 0964514
• 负责人: Swarup Bhunia
• 金额: $ 30万
• 依托单位: Case Western Reserve University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0964514&HistoricalAwards=false
• 关键词: SHF; Medium; Collaborative; Research; System

With technology scaling and increasing integration density in the nanometer technology regime, design considerations for yield and reliability have become critical. The objective of this collaborative research is to explore low-overhead formal design methodology with distributed micro-scale sensor network and systematic feedback control to achieve auto-curing of digital, analog and mixed-signal electronic systems under large process and temporal variations. Such auto-curing approaches will play a key role in preventing yield loss for nanoscale designs, while ensuring reliability of operation and low power dissipation. The research investigates self-curing concepts/techniques for logic circuits, digital signal processing (DSP) units, embedded memory and analog components using appropriate variation sensing and compensation techniques to achieve high yield with optimal power/die-area overhead. It also explores system-level self-curing approaches using global parameter sensor and global controller to determine optimal compensation of mixed-signal cores under power constraint. To realize the curing methodologies in an automatic synthesis environment, the research will aim at developing appropriate Computer-Aided Design tools and a library of self-correcting mixed-signal cores. If successful, it will help the semiconductor industry deliver complex nanoelectronic systems with high reliability, low power and high yield. The proposed research will integrate education and training through course development, summer research program for undergraduates, and senior project design.

随着纳米技术规模的扩大和集成密度的增加，良率和可靠性的设计考虑变得至关重要。本合作研究的目的是探索采用分布式微尺度传感器网络和系统反馈控制的低开销形式化设计方法，以实现数字、模拟和混合信号电子系统在大过程和时间变化下的自动固化。这种自动固化方法将在防止纳米级设计的良率损失，同时确保运行可靠性和低功耗方面发挥关键作用。该研究研究了逻辑电路、数字信号处理（DSP）单元、嵌入式存储器和模拟元件的自固化概念/技术，使用适当的变化传感和补偿技术，以实现最佳功率/模面积开销的高产量。本文还探讨了系统级自固化方法，利用全局参数传感器和全局控制器来确定功率约束下混合信号核心的最佳补偿。为了在自动合成环境中实现固化方法，研究将致力于开发适当的计算机辅助设计工具和自校正混合信号核心库。如果成功，它将有助于半导体行业提供高可靠性、低功耗和高产量的复杂纳米电子系统。建议的研究将通过课程开发、本科生暑期研究计划和高级项目设计来整合教育和培训。