II-NEW: Infrastructure Acquisition for Research and Education in Statistical Design

集成系统（微处理器、soc、asic、存储器、MEMS等）的设计和分析越来越困难，因为在制造过程和操作环境中都存在极端的变化。因此，在设计过程中简单地进行最坏情况分析已不再可行。相反，由这些变化产生的设计分布必须有效而准确地建模。使这种需求更加复杂的是集成规模的不断扩大。随着更大的片上存储器，越来越多的不同计算和通信模块的使用，以及越来越多的异质性，这些系统必须得到很好的表征和“统计”设计，达到甚至超过“六西格玛”。卡耐基梅隆大学的硅系统实现中心（CSSI）专注于统计设计和分析的各个方面，从系统级架构到模拟/数字电路，再到半导体制造中发现的复杂性的物理和建模。利用从NSF计算研究基础设施（CRI）项目获得的共享计算基础设施，CSSI正在开发各种统计设计和分析方法，从而能够继续使用缩放cmos技术。CSSI教师在集成系统设计和制造的各个领域领导了70多个不同的研究项目，并指导了20多个不同的研究生/高级课程，涵盖这些领域。通过支持NSF CRI计划获得的计算机基础设施，开发和验证统计设计新方法的能力，以及培养下一代集成系统研究人员和实践者的能力正在显著增强。

Design and analysis of integrated systems (microprocessors, SoCs, ASICs, memories, MEMS, etc.) is increasingly difficult due to the extreme variations that exist both in the fabrication process and the operating environment. As a result, it is no longer viable to simply perform worst-case analysis during design. Instead, the distribution of designs resulting from these variations must be efficiently and accurately modeled. Compounding this need is the increasing scale of integration. With larger on-chip memories, growing use of diverse computing and communication blocks, and increasing heterogeneity, it is imperative that these systems be well characterized and "statistically" designed up to and even beyond "six sigma". The Center for Silicon System Implementation (CSSI) at Carnegie Mellon is focused on all aspects of statistical design and analysis that spans from system-level architectures to analog/digital circuits, to the physics and modeling of the complexities found in semiconductor manufacturing. Using the shared compute infrastructure acquired with support from the NSF Computing Research Infrastructure (CRI) program, CSSI is developing various statistical design and analysis methodologies that enable continued use of scaled-CMOS technology. CSSI faculty lead over 70 different research projects in various areas related to integrated system design and manufacturing, and instruct over 20 different graduate/senior-level courses that cover these same areas. The ability to develop and validate new methodologies for statistical design, and train the next-generation of integrated systems researchers and practitioners is being significantly enhanced by the computer infrastructure acquired through support of the NSF CRI program.