FET: SHF: Small: Collaborative: Advanced Circuits, Architectures and Design Automation Technologies for Energy-efficient Single Flux Quantum Logic

FET：SHF：小型：协作：用于节能单通量量子逻辑的先进电路、架构和设计自动化技术

• 批准号: 2008514
• 负责人: Yanzhi Wang
• 金额: $ 20万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2008514&HistoricalAwards=false
• 关键词: FET; SHF; Small; Collaborative; Advanced

The critical dependence of the world economy on energy-efficient operations in computing are now almost universally recognized. To this end, advances in “beyond-CMOS” device technologies and corresponding logic families are now seen as a key step towards achieving the next major leap in high-performance computing. The challenges and opportunities described in this research provide directions for developing many aspects of a very promising “beyond-CMOS” technology, which can result in extremely high-performance, yet energy-efficient, computing systems, and thereby ensure sustainability of the information-technology ecosystem. SuperConductive Electronics (SCE) based on the Josephson junction (JJ) Single Flux Quantum (SFQ) logic cells have evolved into a within-reach “beyond-CMOS” technology, with switching speeds in the hundreds of GHz and energy dissipation of 10^-19 or less Joules per transition. The project will enhance business and societal opportunities by producing ultra-high performance and energy-efficient electronics for a wide range of computing fabrics, and in the process will also contribute to enhancing the technological capabilities of the US by providing education and research opportunities to undergraduate, graduate, and underrepresented students by including them in the planned research.This research aims to achieve major strides in the development of advanced circuits, architectures and design-automation technologies in support of large-scale superconductive SFQ digital electronics to meet the needs of future energy-efficient, high-performance exa-scale computing systems. Research on design automation will enable large-scale SCE systems integration. Targeting both DC-powered energy-efficient Rapid SFQ and AC-powered Adiabatic Quantum-Flux-Parametron circuit families, this research aims to solve four key problems associated with the design automation and optimization of SFQ logic circuits, namely: minimization of SFQ circuit retiming to the number of buffers for operating frequency improvement and/or clock-phase consistency; path-balancing technology mapping for sequential SFQ circuits with loops; timing-driven global placement using unique features of SFQ logic families and a powerful mathematical optimization tool; and circuit partitioning to enable effective current recycling.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.

现在，世界经济对计算中节能运营的批判性依赖性现在几乎被普遍认可。为此，“超越流程”设备技术和相应的逻辑系列的进步被视为实现高性能计算的下一个重大飞跃的关键一步。这项研究中描述的挑战和机遇为开发非常有希望的“超越流行”技术的许多方面提供了方向，这可能会导致极高的绩效，能效率高的计算系统，从而确保信息技术生态系统的可持续性。超导电子（SCE）基于约瑟夫森连接（JJ）单通量量子（SFQ）逻辑细胞已演变为范围内的“超越流体”技术，数百个GHz的切换速度和能量耗散的10^-19或更少的joules jouleles每次过渡。该项目将通过为广泛的计算织物生产超高的性能和节能电子设备来增强业务和社交机会，在此过程中，还将有助于通过在计划研究中包括在计划研究中包括在内的研究目标，以实现架构的研究，从而提高了美国的技术能力，以提供教育和研究机会，以使他们在计划中累积，并促进他们的技术能力。支持大规模超导SFQ数字电子设备的技术，以满足未来能效，高性能EXA级计算系统的需求。设计自动化的研究将使大规模SCE系统集成。这项研究旨在靶向DC驱动的能源快速SFQ和AC功率的绝热量子量频率 - Parametron电路家族，旨在解决与SFQ逻辑电路的设计自动化和优化相关的四个关键问题，即：最小化SFQ电路以使SFQ电路对操作频率提高和时钟的频率提高和时钟的次数最小化；循环的连续SFQ电路的路径平衡技术映射；定时驱动的全局位置使用SFQ逻辑家族的独特功能和功能强大的数学优化工具；该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的审查标准来评估值得支持的。

项目成果

Towards AQFP-Capable Physical Design Automation

迈向支持 AQFP 的物理设计自动化

• 发表时间: 2021
• 期刊: and Test in Europe (DATE
• 作者: Hongjia Li, Mengshu Sun

TAAS: a timing-aware analytical strategy for AQFP-capable placement automation

TAAS：用于支持 AQFP 的贴装自动化的时序感知分析策略

• DOI: 10.1145/3489517.3530487
• 发表时间: 2022
• 期刊: Design Automation Conference (DAC
• 作者: Dong, Peiyan;Xie, Yanyue;Li, Hongjia;Sun, Mengshu;Chen, Olivia;Yoshikawa, Nobuyuki;Wang, Yanzhi
• 通讯作者: Wang, Yanzhi