Collaborative Research: FuSe: A Reconfigurable Ferrolectronics Platform for Collective Computing (FALCON)

合作研究：FuSe：用于集体计算的可重构铁电子平台（FALCON）

• 批准号: 2328961
• 负责人: Nikhil Shukla
• 金额: $ 69.78万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2328961&HistoricalAwards=false
• 关键词: Collaborative; Research; FuSe; Reconfigurable; Ferrolectronics

Digital computing has been the bedrock of the modern information revolution. However, improvements in energy efficiency and reductions in compute costs for digital hardware have decelerated. The impact of this slowdown is felt most acutely when solving computationally challenging problems, such as those in combinatorial optimization (CO), where the computational resources (energy, time, memory) required scale exponentially with problem size. Moreover, such problems find extensive real-world application in fields ranging from artificial intelligence, to autonomous driving, to airline scheduling, to power distribution, creating a practical need to develop new alternative approaches to solving such problems efficiently. Analog dynamical systems such as coupled oscillators offer a promising physics-based approach for solving such hard problems since they exhibit collective properties that are unavailable in digital systems. However, current coupled oscillator platforms address a very limited set of CO problems, exhibit little reconfigurability, and lack the hardware-algorithm ecosystem that made digital computing so successful. Therefore, the goal of this research is to develop a new analog coupled oscillator platform, FALCON, that overcomes these challenges using a cross-cutting effort that spans the development of new oscillator-based computational models to the design of new ferroelectric materials, devices, and circuits for implementing them. The research will enable fundamental advances in analog computing that will subsequently translate to performance improvements for practical applications. Furthermore, to broaden the impact of this work, the team will create an open-source repository of computational models, coupling architectures, and design schemes that will be developed through the course of this project. The team will also focus on workforce development through various activities, such as organizing an industry day, developing new courses, and creating research opportunities for students underrepresented in STEM fields.The coupled oscillator-based FALCON platform developed in this project will offer tailored coupling cores with differentiated phase synchronization dynamics that are specifically engineered such that specific classes of CO problems can be directly mapped and solved in hardware. The proposed paradigm marks a radical departure from the ‘one-size-fits-all’ approach used until now, wherein the oscillator synchronization dynamics could only be mapped to a single computational model (e.g., Ising model) that may not always be computationally efficient for the CO problem to be solved. This approach can result in significant pre-processing overhead and entail additional hardware requirements (oscillator nodes) that far exceed the size of the original problem. Moreover, the additional pre-processing and hardware needs can reduce, if not eliminate, any performance advantage of the analog approach, as well as limit its scalability. In contrast, the FALCON coupling cores will offer multiple types of synchronization dynamics, with each core facilitating the mapping of a large number of CO problems directly onto the hardware with minimal overhead. The FALCON platform will be developed through across-the-stack innovation in ferroelectric materials, devices, and mixed-signal circuits, in close conjunction with the advancement of the theoretical foundations of coupled oscillator-based computing.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

数字计算一直是现代信息革命的基石。然而，数字硬件能源效率的提高和计算成本的降低已经放缓。在解决具有计算挑战性的问题时，例如组合优化 (CO) 中的问题，需要的计算资源（能量、时间、内存）随着问题规模呈指数级增长，这种放缓的影响最为明显。此外，此类问题在人工智能、自动驾驶、航班调度、配电等领域有着广泛的实际应用，因此迫切需要开发新的替代方法来有效解决此类问题。耦合振荡器等模拟动力系统为解决此类难题提供了一种有前景的基于物理的方法，因为它们表现出数字系统所不具备的集体特性。然而，当前的耦合振荡器平台解决的 CO 问题非常有限，几乎没有可重构性，并且缺乏使数字计算如此成功的硬件算法生态系统。因此，本研究的目标是开发一种新的模拟耦合振荡器平台 FALCON，通过跨领域的努力克服这些挑战，这些努力涵盖了基于振荡器的新计算模型的开发以及用于实现这些模型的新铁电材料、器件和电路的设计。该研究将使模拟计算取得根本性进步，随后将转化为实际应用的性能改进。此外，为了扩大这项工作的影响，该团队将创建一个计算模型、耦合架构和设计方案的开源存储库，这些存储库将在该项目的过程中开发。该团队还将通过各种活动重点关注劳动力发展，例如组织行业日、开发新课程以及为 STEM 领域代表性不足的学生创造研究机会。该项目中开发的基于耦合振荡器的 FALCON 平台将提供具有差异化相位同步动力学的定制耦合核心，这些核心经过专门设计，可以直接在硬件中映射和解决特定类别的 CO 问题。所提出的范例标志着与迄今为止使用的“一刀切”方法的彻底背离，其中振荡器同步动力学只能映射到单个计算模型（例如伊辛模型），该模型对于要解决的 CO 问题可能并不总是具有计算效率。这种方法可能会导致大量的预处理开销，并且需要额外的硬件要求（振荡器节点），远远超出原始问题的规模。此外，额外的预处理和硬件需求可能会减少（如果不是消除的话）模拟方法的任何性能优势，并限制其可扩展性。相比之下，FALCON 耦合核心将提供多种类型的同步动态，每个核心都有助于以最小的开销将大量 CO 问题直接映射到硬件上。 FALCON 平台将通过铁电材料、器件和混合信号电路的跨堆栈创新来开发，并与基于耦合振荡器的计算的理论基础的进步密切结合。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。