IRES Track I: U.S.-Japan International Research Experience for Students on Superconducting Electronics

IRES Track I:美国-日本超导电子学学生国际研究经验

基本信息

  • 批准号:
    1854213
  • 负责人:
  • 金额:
    $ 29.93万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-03-15 至 2025-02-28
  • 项目状态:
    未结题

项目摘要

The objective of this IRES project is to provide U.S. students with international research experience in superconducting electronics and circuits as future computing paradigms in Yokohama National University (YNU), Japan, which has one of the world's strongest research center in superconducting electronics and circuits. The project will select five (5) graduate students and two (2) undergraduate students nation-wide each year and support them to visit YNU over a period of eight (8) weeks. The project will enable U.S. students to conduct high-quality research on next-generation superconducting electronics, in collaboration with their faculty mentors in YNU. Such experiences expose U.S. students to the international research community at a critical early stage in their careers. Through participating in this program, U.S. students will gain extensive experience on the research of superconducting electronics, on the culture in Japan, and on performing and collaborating in an international environment in general. The experience will also be shared to the broader community through the personal social media, Web 2.0 based forum, carefully integrated activities such as research for undergraduate students, minorities and underrepresented groups, as well as outreach events for local schools. It will be beneficial for the STEM and underrepresented student education as well as the advancing of superconducting and semiconductor industry in U.S.Being widely-known for low energy dissipation and ultra-fast switching speed, Josephson Junction-based superconductor logic families have been proposed and implemented to process analog and digital signals. It has been perceived to be important candidate to replace state-of-the-art CMOS due to the superior potential in operation speed and energy efficiency. The project contains well-planned recruitment, preparation, mentoring and post-trip activities. The proposed research address fundamental problems in the circuit design, electronic design automation, and applications in superconducting electronics that need to be addressed urgently. The first project deals with the integration of AQFP technology with the efficient implementation of deep learning systems, where the latter is a core research topic in hardware and AI. The second project deals with efficient design of AQFP and RSFQ superconducting circuits and will greatly enhance the performance, efficiency and reliability. The third project aims to develop a design automation toolflow of superconducting electronics, which is currently lacking and will significantly reduce the development time of superconducting circuits. It is anticipated that with the close interaction with YNU, the breakthroughs made from these projects can have a significant impact on future superconducting electronics development and supercomputing systems, as well as the technology in the U.S. in corresponding areas.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.
这个IRES项目的目标是为美国学生提供超导电子和电路的国际研究经验,作为日本横滨国立大学(YNU)的未来计算范例,该大学拥有世界上最强大的超导电子和电路研究中心之一。该项目将选择五(5)研究生和两(2)本科生全国范围内,每年支持他们访问YNU超过八(8)周。该项目将使美国学生能够与YNU的教师导师合作,对下一代超导电子进行高质量的研究。这些经历使美国学生在职业生涯的关键早期阶段接触到国际研究界。通过参加该计划,美国学生将获得超导电子研究,日本文化以及在国际环境中表演和合作的广泛经验。这些经验也将通过个人社交媒体、基于Web 2.0的论坛、精心整合的活动(如针对本科生、少数民族和代表性不足的群体的研究)以及针对当地学校的外联活动分享给更广泛的社区。这将有利于STEM和未被充分代表的学生教育以及美国超导和半导体产业的发展。以低能耗和超快开关速度而闻名的基于约瑟夫森结的超导逻辑系列已经被提出并实现用于处理模拟和数字信号。由于其在操作速度和能量效率方面的上级潜力,它已被认为是取代最先进的CMOS的重要候选者。该项目包括精心规划的征聘、准备、辅导和旅行后活动。所提出的研究解决了电路设计,电子设计自动化和超导电子学应用中迫切需要解决的基本问题。第一个项目涉及AQFP技术与深度学习系统的有效实现的集成,后者是硬件和人工智能的核心研究课题。第二个项目涉及AQFP和RSFQ超导电路的有效设计,将大大提高性能,效率和可靠性。第三个项目旨在开发超导电子学的设计自动化工具流程,这是目前缺乏的,将大大减少超导电路的开发时间。预计通过与YNU的密切合作,这些项目所取得的突破将对未来的超导电子发展和超级计算系统以及美国相应领域的技术产生重大影响。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Towards AQFP-Capable Physical Design Automation
迈向支持 AQFP 的物理设计自动化
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Hongjia Li, Mengshu Sun
  • 通讯作者:
    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:
  • 影响因子:
    0
  • 作者:
    Dong, Peiyan;Xie, Yanyue;Li, Hongjia;Sun, Mengshu;Chen, Olivia;Yoshikawa, Nobuyuki;Wang, Yanzhi
  • 通讯作者:
    Wang, Yanzhi
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Yanzhi Wang其他文献

Design and Evaluation of Deep Learning Accelerators Using Superconductor Logic Families
使用超导逻辑系列的深度学习加速器的设计和评估
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Qiuyun Xu;Yanzhi Wang;Naoki Takeuchi;Nobuyuki Yoshikawa
  • 通讯作者:
    Nobuyuki Yoshikawa
Dynamics and control of spin entanglement
自旋纠缠的动力学与控制
  • DOI:
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Qiuyun Xu;Yanzhi Wang;Naoki Takeuchi;Nobuyuki Yoshikawa;井澤佳那子,羽藤英二,菊池雅彦,石神孝裕,川名義輝,杉本保男;寺地徳之,フィオリ アレクサンドレ,桐谷範彦,谷本 智,ゲラール エチェン,小出康夫;小林研介;Zenji Horita;S. Tarucha
  • 通讯作者:
    S. Tarucha
Resource allocation optimization in a data center with energy storage devices
具有储能设备的数据中心的资源分配优化
Ultra-broad bandwidth low-dispersion mirror with smooth dispersion and high laser damage resistance.
超宽带宽低色散镜,色散平滑,抗激光损伤能力强。
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    3.6
  • 作者:
    Yuhui Zhang;Yanzhi Wang;Yu Chen;Ye Lu;Xinliang Wang;Fanyu Kong;Zhihao Wang;Chang Chen;Yi Xu;Yuxin Leng;Hongbo He;J. Shao
  • 通讯作者:
    J. Shao
Share Repurchases as a Potential Tool to Mislead Investors
股票回购是误导投资者的潜在工具

Yanzhi Wang的其他文献

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{{ truncateString('Yanzhi Wang', 18)}}的其他基金

Collaborative Research: CSR: Small: Expediting Continual Online Learning on Edge Platforms through Software-Hardware Co-designs
协作研究:企业社会责任:小型:通过软硬件协同设计加快边缘平台上的持续在线学习
  • 批准号:
    2312158
  • 财政年份:
    2023
  • 资助金额:
    $ 29.93万
  • 项目类别:
    Standard Grant
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
  • 财政年份:
    2020
  • 资助金额:
    $ 29.93万
  • 项目类别:
    Standard Grant
SPX: Collaborative Research: FASTLEAP: FPGA based compact Deep Learning Platform
SPX:协作研究:FASTLEAP:基于 FPGA 的紧凑型深度学习平台
  • 批准号:
    1919117
  • 财政年份:
    2019
  • 资助金额:
    $ 29.93万
  • 项目类别:
    Standard Grant
CNS Core: Small: Collaborative: Content-Based Viewport Prediction Framework for Live Virtual Reality Streaming
CNS 核心:小型:协作:用于直播虚拟现实流的基于内容的视口预测框架
  • 批准号:
    1909172
  • 财政年份:
    2019
  • 资助金额:
    $ 29.93万
  • 项目类别:
    Standard Grant

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