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

SHF：小：重新思考多项式编程：通过凸化实现弹性模拟/射频集成系统的高效设计和优化

• 批准号: 1604150
• 负责人: Xin Li
• 金额: $ 35万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-15 至 2017-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1604150&HistoricalAwards=false
• 关键词: SHF; Small; Re; thinking; Polynomial

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.

该项目涉及一种新颖的设计和优化框架，以提高先进模拟和射频（RF）集成系统在广泛应用中的性能，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，鉴于其跨学科的覆盖面，该项目为大学生和工业工程师提供了培训机会，包括课程编制、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，培养相关领域的高质量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，并将潜在地导致影响美国半导体行业的更广泛的影响。激进的技术规模化，大规模的工艺变化新标准的快速引入和自主应用数量的增加使得有必要开发弹性模拟和射频（RF）能够适应与过程、环境和标准相关的所有可变性的集成系统。然而，弹性模拟/RF系统的设计和优化一直被认为是一个巨大的挑战，由于其不规则的性能函数，离散的设计空间和高系统复杂性。该项目利用一种新的优化框架来有效地设计和实现弹性模拟/RF系统。该框架是基于最新的结果优化理论，并预计找到最佳设计既有效（即，具有低计算成本）和鲁棒性（例如，保证全局最优）。该项目将应用该技术来优化弹性模拟/RF系统，该系统由可调模拟/RF电路、片上传感器和片上控制器组成。因此，所提出的框架提供了一种新的基础设施，模拟/RF设计，使根本的改进。