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.
该 IRES 项目的目标是为美国学生提供超导电子学和电路方面的国际研究经验,作为日本横滨国立大学 (YNU) 的未来计算范式,该大学拥有世界上最强大的超导电子学和电路研究中心之一。该项目每年将在全国范围内选拔五 (5) 名研究生和两 (2) 名本科生,并支持他们在八 (8) 周内访问云南大学。该项目将使美国学生能够与云南大学的导师合作,对下一代超导电子学进行高质量的研究。这些经历让美国学生在职业生涯的关键早期阶段接触国际研究界。通过参与该项目,美国学生将获得超导电子学研究、日本文化以及在国际环境中的表演和合作方面的丰富经验。这些经验还将通过个人社交媒体、基于 Web 2.0 的论坛、精心整合的活动(例如针对本科生、少数族裔和代表性不足群体的研究)以及针对当地学校的外展活动,与更广泛的社区分享。这将有利于STEM和代表性不足的学生教育以及美国超导和半导体行业的发展。基于约瑟夫森结的超导逻辑系列以低能耗和超快开关速度而闻名,已被提出并实现处理模拟和数字信号。由于其在运行速度和能源效率方面的卓越潜力,它被认为是取代最先进 CMOS 的重要候选者。该项目包含精心策划的招募、准备、指导和旅行后活动。拟议的研究解决了电路设计、电子设计自动化以及超导电子学应用中急需解决的基本问题。第一个项目涉及 AQFP 技术与深度学习系统的高效实施的集成,其中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超导电路的高效设计,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,这是目前所缺乏的,并将显着缩短超导电路的开发时间。预计通过与云南大学的密切互动,这些项目取得的突破将对未来超导电子学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。该奖项体现了NSF的法定使命和使命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,该项目被认为值得支持。

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)
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:
    2022-07
  • 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
Towards AQFP-Capable Physical Design Automation
迈向支持 AQFP 的物理设计自动化
  • DOI:
  • 发表时间:
    2021-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Hongjia Li; Mengshu Sun
  • 通讯作者:
    Mengshu Sun
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Yanzhi Wang其他文献

Battery-supercapacitor hybrid system for high-rate pulsed load applications
适用于高速率脉冲负载应用的电池-超级电容器混合系统
  • DOI:
    10.1109/date.2011.5763295
  • 发表时间:
    2011-03-14
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Donghwa Shin;Younghyun Kim;J. Seo;N. Chang;Yanzhi Wang;M. Pedram
  • 通讯作者:
    M. Pedram
Reduced-Complexity Deep Neural Networks Design Using Multi-Level Compression
使用多级压缩降低复杂度的深度神经网络设计
Design of SFQ convolutional computation processor for convolutional neural network
卷积神经网络SFQ卷积计算处理器的设计
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Fei Ke;Ao Ren;Yanzhi Wang;Olivia Chen;Yuki Yamanashi;Nobuyuki Yoshikawa
  • 通讯作者:
    Nobuyuki Yoshikawa
Design Automation Methodology and Tools for Superconductive Electronics
超导电子设计自动化方法和工具
The Oscar Goes to…: High-tech Firms’ Acquisitions in Response to Rivals’ Technology Breakthroughs
奥斯卡奖颁给了……:高科技公司——应对竞争对手的收购——技术突破
  • DOI:
    10.2139/ssrn.2815148
  • 发表时间:
    2020-09-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    I. Chen;Po;Micah S. Officer;Yanzhi Wang
  • 通讯作者:
    Yanzhi Wang

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
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
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

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    $ 29.93万
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