SHF: Small: Re-thinking Polynomial Programming: Efficient Design and Optimization of Resilient Analog/RF Integrated Systems by Convexification

该项目涉及一种新的设计和优化框架，以提高先进的模拟和射频(RF)集成系统的性能，应用范围广泛，从消费电子到医疗仪器，对半导体行业和国民经济具有潜在影响。此外，鉴于其跨学科覆盖范围，该项目为大学生和工业工程师提供了培训机会，包括课程开发、学生咨询、外联活动和讲习班组织。它可以改善教育基础设施，培养相关领域的高素质研究人员和从业人员。这些教育活动与拟议的研究任务相结合，促进了新的设计和优化技术向技术界的转移，并可能导致影响美国半导体行业的更广泛的影响。不断发展的技术规模、大规模的工艺变化、新标准的快速引入和越来越多的自主应用，使得开发具有弹性的模拟和射频(RF)集成系统变得必要，该系统能够适应与工艺、环境和标准相关的所有变量。然而，弹性模拟/射频系统的设计和优化一直被认为是一个巨大的挑战，因为它们的性能函数不规则，设计空间离散，系统复杂性高。该项目利用一种新的优化框架来高效地设计和实现弹性模拟/射频系统。该框架以最新的结果优化理论为基础，期望找到既高效(即计算成本低)又稳健(例如保证全局最优)的最优设计。该项目将应用这项技术来优化弹性模拟/射频系统，该系统由可调模拟/射频电路、片上传感器和片上控制器组成。因此，建议的框架为模拟/射频设计提供了一种新的基础设施，从而实现了根本性的改进。

This project deals with a novel design and optimization framework to improve performance of advanced analog and radio frequency (RF) integrated systems over a broad range of applications, from consumer electronics to medical instruments with potential impact on the semiconductor industry and national economy. In addition, given its interdisciplinary coverage, the project offers opportunities for training to both university students and industrial engineers, including curriculum development, student advising, outreach activities and workshop organization. It could improve the education infrastructure and generate high-quality researchers and practitioners in related fields. These education activities integrated with the proposed research tasks facilitate the transfer of the new design and optimization techniques to the technical community, and will potentially lead to a broader impact affecting the US semiconductor industry.Aggressive technology scaling, large-scale process variation, rapid introduction of new standards and increased number of autonomous applications have made it necessary to develop resilient analog and radio frequency (RF) integrated systems that can adapt to all variabilities related to process, environment and standard. However, the design and optimization of resilient analog/RF systems has been considered as a grand challenge due to their irregular performance functions, discrete design spaces and high system complexities. This project exploits a novel optimization framework to efficiently design and implement resilient analog/RF systems. The framework is based on recent results optimization theory, and is expected to find the optimal design both efficiently (i.e., with low computational cost) and robustly (e.g., with guaranteed global optimum). The project would apply this technique to optimize resilient analog/RF systems that are composed of tunable analog/RF circuits, on-chip sensors and on-chip controllers. Hence, the proposed framework offers a novel infrastructure for analog/RF design enabling radical improvements.