II-EN: Infrastructure Acquisition for Statistical Power, Leakage, and Timing Modeling Towards Realization of Robust Complex Nanoelectronic Circuits

该奖项是根据2009年《美国复苏和再投资法案》(Public Law 111-5)资助的。在考虑工艺变化的同时，对功耗、泄漏和时序进行准确的建模，对于纳米级CMOS集成电路的可制造设计至关重要。因此，迫切需要统计模型，以允许设计工程师快速进行体系结构或系统级别的设计空间探索，而无需求助于从系统到物理级别的完整设计迭代。该项目方法的主旨是从最低(晶体管)到最高(系统)级别的数据传输的进展，同时利用来自实际硅的最小数据。该项目利用以下基础设施：(1)专用设备：混合信号分析仪、探测站和任意波形发生器，用于样本数据采集、探测和分析，用于模型验证。(2)计算资源：一个高端的4处理器服务器，具有16-GB本地存储器和4-TB RAID5存储，可供两名教员和10名学生用于纳米级数据采集，控制、分析和存储。(3)研究和开发人员开发模型和库，验证方法，并维护基础设施。该项目的教育影响有三个方面：对北大课程的影响，对将使用该基础设施的其他研究人员的课程的影响，以及对达拉斯-沃斯堡大都市周围的社区学院的影响。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Accurate modeling of power, leakage, and timing while accounting for process variations, is crucial for the manufacturable design of nanoscale CMOS integrated circuits. Thus, there is a pressing need for statistical models that allow design engineers to make fast architectural or system level design space exploration without resorting to a complete design iteration, from system to physical level. The thrust of the project's methodology is the progression of data transfer from lowest (transistor) to highest (system) level while utilizing minimal data from actual silicon. This allows for fast concurrent design for manufacturing of new systems with a clear delineation of the needed data at every level.To conduct research on nanoscale CMOS modeling that can be used for realization of robust circuits, and to make the deliverables available to the VLSI and educational communities, the project utilizes the following infrastructure: (1) Specialized equipment: mixed-signal analyzer, probing station and arbitrary waveform generator for sample data collection, probing and analysis for model validation.(2) Computing resources: a high-end, 4 processor server with 16-GB local memory and 4-TB RAID5 storage to be used by two faculty members and 10 students for nanoscale data acquisition, control, analysis, and storage.(3) Research and development personnel to develop the models and libraries, to validate the methodology, and to maintain the infrastructure.The educational impact of the project is 3-fold: impact on curricula at UNT, impact on curricula of other researchers who will use this infrastructure, and impact on the community colleges around the Dallas-Fort Worth metroplex.