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.
