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II-New: RICARDO: Research Infrastructure for Circuit and Architecture Design with Emerging Technologies

II-New: RICARDO: Research Infrastructure for Circuit and Architecture Design with Emerging Technologies
II-新:RICARDO:利用新兴技术进行电路和架构设计的研究基础设施
批准号:
1730309
负责人:
Yuan Xie
金额:
$50.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2020-08-31

项目摘要

项目成果

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中文摘要
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英文摘要
Aggressive technology scaling into the deep sub-micron (DSM) regime has been accompanied by a dramatic increase in transistor densities with shrinking transistor feature size that approaches the physical limits, resulting in major economic and technical challenges that are expected to hinder the continued scaling of traditional Complimentary Metal-Oxide Semiconductor (CMOS) technology. This has resulted in the trends of searching for alternative emerging technologies that can continue the performance/power improvement for computing systems. As the underlying emerging technologies continue to evolve, it has become imperative for computer engineers to translate the potential of such emerging devices into circuits and architecture designs. Such new circuits and architecture designs will face multiple challenges ranging from the modeling/abstraction and simulation of such emerging technologies, to the complexity due to the sheer volume of nanodevices that will have to be integrated for complex functionality.The proposing team is exploring multiple emerging technologies (including three-dimensional integration, emerging non-volatile memory, and nanophotonics) with a comprehensive coverage of innovative work in the modeling, design analysis, simulation, verification, testing, and evaluation of circuits and architectures constructed out of emerging technologies, to overcome all the CMOS scaling limits. Efficient design and use of future system architectures using emerging technologies will be vital to the future of computing. The acquired equipment and the chip prototyping will be used to train graduate students and undergraduate students including those from under-represented groups advised by the PIs (women and minority students) to gain expertise in the area of computer architecture, Very Large-Scale Integration (VLSI), and device fabrication. Teaching material and lab modules will be developed for several courses and made available on the web for wider dissemination. Ongoing collaborations with industry partners and national labs in current NSF-funded research will be used for transfer of technology.
期刊论文(25)
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会议论文
DOI: 10.1109/isca45697.2020.00073
发表时间: 2020-05
期刊: 2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture (ISCA)
影响因子: --
作者: [Weitao Li;Pengfei Xu;Yang Zhao;Haitong Li;Yuan Xie;Yingyan Lin]
通讯作者: Weitao Li;Pengfei Xu;Yang Zhao;Haitong Li;Yuan Xie;Yingyan Lin
DOI: 10.1145/3352460.3358290
发表时间: 2019-10
期刊: Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture
影响因子: --
作者: [Pengfei Zuo;Yu Hua;Yuan Xie]
通讯作者: Pengfei Zuo;Yu Hua;Yuan Xie
DOI: 10.1109/tvlsi.2018.2865133
发表时间: 2018-11-01
期刊: IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
影响因子: 2.8
作者: [Xie, Mimi, Li, Shuangchen, Xie, Yuan]
通讯作者: Xie, Yuan
DOI: 10.1109/dac18072.2020.9218644
发表时间: 2020-07
期刊: 2020 57th ACM/IEEE Design Automation Conference (DAC)
影响因子: --
作者: [Maohua Zhu;Yuan Xie]
通讯作者: Maohua Zhu;Yuan Xie
23
    SHF:SMALL:Collaborative Research: Exploring Nonvolatility of Emerging Memory Technologies for Architecture Design
    SPX: Collaborative Research: Ula! - An Integrated Deep Neural Network (DNN) Acceleration Framework with Enhanced Unsupervised Learning Capability
    XPS: FULL: DSD: Collaborative Research: Parallelizing and Accelerating Metagenomic Applications
    SHF: Medium: ASKS - Architecture Support for darK Silicon
    海外基金