Collaborative Research: SHF: Small: Tangram: Scaling into the Exascale Era with Reconfigurable Aggregated "Virtual Chips"

合作研究:SHF:小型:七巧板:通过可重构聚合“虚拟芯片”扩展到百亿亿次时代

基本信息

  • 批准号:
    2008477
  • 负责人:
  • 金额:
    $ 21.34万
  • 依托单位:
  • 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:
    2020-07-15 至 2022-10-31
  • 项目状态:
    已结题

项目摘要

The design of general-purpose processors is reaching a performance bottleneck due to the limitations in technology scaling. Chiplet-based systems offer a promising solution by integrating small dies (chiplets) inside one package. Chiplets also enable heterogeneous integration of discrete chip architectures, such as CPUs, GPUs, DSPs, and FPGAs. However, the design of high-performance chiplet-based systems faces serious challenges: inter-chiplet communication is a critical bottleneck; resource needs to be efficiently shared among the chiplets to improve the performance-cost ratio; power and thermal management need to be optimized for better in-package integration. Consequently, such designs need to take a more holistic approach, and investigations are needed on the cross-cutting issues across the processing nodes, storage and interconnection fabric. This research proposes to build "virtual chips" from heterogeneous aggregated chiplets, so that the system can not only reap the performance benefit of a monolithic super chip but also break the scalability bottleneck. A major outcome of the project will be a set of optimization methods that enable the design of a reconfigurable architecture, leveraging a hybrid wireless interconnection to seamlessly connect the computing and memory components. To this end, the research goals include: (1) design of reconfigurable architectures to break the chiplet boundaries for efficient resource sharing; (2) development of models to quantify interactions between the applications and hardware resources for fast design-space exploration; (3) design of a hybrid wireless interconnection network to seamlessly bridge the physical gaps between chiplets and enable reconfigurable architectures through the flexibility of wireless networks; and (4) design of novel wireless antennas to improve energy and thermal efficiency.The proposed research bridges the gap between multiple layers of the design stack: hardware architectures, networks and devices. Due to its cross-cutting nature, the proposed research has the potential to transform the design of high-performance, energy-efficient and cost-effective systems that are able to meet the demand of emerging applications with growing bandwidth and performance needs. The educational contributions of this research include integrating research with teaching and training, design of tutorials and workshops focusing on the training of future engineers, and interaction with industry to accelerate technology transfer. Through the outreach activities as part of the proposed project, more undergraduate and minority students will be attracted to this field of engineering.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.
由于技术扩展的局限性,通用处理器的设计正在达到性能瓶颈。基于Chiplet的系统通过将小模具(chiplets)集成到一个包装中,提供了有希望的解决方案。 Chiplet还可以实现离散芯片架构(例如CPU,GPU,DSP和FPGA)的异质整合。但是,高性能基于chiplet的系统的设计面临严重的挑战:芯片间交流是关键的瓶颈;资源需要在芯片中有效共享,以提高性能成本比率;需要优化功率和热管理,以获得更好的包装整合。因此,此类设计需要采取更全面的方法,并且需要对处理节点,存储和互连织物的横切问题进行研究。这项研究提议从异质的聚集芯片中构建“虚拟芯片”,以便该系统不仅可以从单片超级芯片中获得性能益处,而且可以破坏可扩展性瓶颈。该项目的主要结果将是一组优化方法,可以设计可重构体系结构,利用混合无线互连以无缝连接计算和内存组件。为此,研究目标包括:(1)设计可重构体系结构以打破chiplet边界以进行有效的资源共享; (2)开发模型,以量化应用程序和硬件资源之间的相互作用,以进行快速设计空间探索; (3)设计混合无线互连网络,以通过无线网络的灵活性无缝地弥合chiplets之间的物理间隙,并启用可重新配置的架构; (4)新型无线天线的设计以提高能量和热效率。拟议的研究弥合了设计堆栈多层之间的缝隙:硬件体系结构,网络和设备。由于其跨裁切性质,拟议的研究有可能改变高性能,节能和成本效益的系统的设计,这些系统能够满足随着带宽和性能需求增长的新兴应用的需求。 这项研究的教育贡献包括将研究与教学和培训,教程和研讨会的设计集成,重点是培训未来的工程师,以及与行业的互动以加速技术转移。通过推出活动作为拟议项目的一部分,将吸引更多的本科生和少数民族学生进入这一工程领域。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和更广泛影响的评估审查标准通过评估来获得支持的。

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)
Energy-efficient task-resource co-allocation and heterogeneous multi-core NoC design in dark silicon era
暗硅时代节能任务资源协同分配与异构多核NoC设计
  • DOI:
    10.1016/j.micpro.2021.104055
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    2.6
  • 作者:
    Reza, Md Farhadur;Zhao, Dan;Bayoumi, Magdy
  • 通讯作者:
    Bayoumi, Magdy
ThingNet: A Lightweight Real-time Mirai IoT Variants Hunter through CPU Power Fingerprinting
ThingNet:通过 CPU 功率指纹识别的轻量级实时 Mirai IoT 变体猎人
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Hongyi Wu其他文献

Structural characterization of a dimerization interface in the CD28 transmembrane domain.
CD28 跨膜域二聚化界面的结构表征。
  • DOI:
    10.1016/j.str.2022.03.004
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    5.7
  • 作者:
    Hongyi Wu;Ruiyu Cao;M. Wen;Hongjuan Xue;B. Ouyang
  • 通讯作者:
    B. Ouyang
Minimum-cost gateway deployment in cellular Wi-Fi networks
在蜂窝 Wi-Fi 网络中部署成本最低的网关
Simulation studies of a Fair and Effective Queueing algorithm for WiMAX resource allocation
WiMAX资源分配公平有效排队算法的仿真研究
Size Controlled Metal Oxide Nanoparticles:Synthesis, Characterization, and Application to Catalysis
尺寸控制的金属氧化物纳米颗粒:合成、表征及其催化应用
  • DOI:
  • 发表时间:
    2009
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Hongyi Wu
  • 通讯作者:
    Hongyi Wu
Thrombin induced platelet-fibrin clot strength measured by thrombelastography is a novel marker of platelet activation in acute myocardial infarction.
通过血栓弹力图测量的凝血酶诱导的血小板纤维蛋白凝块强度是急性心肌梗塞中血小板活化的新标志物。

Hongyi Wu的其他文献

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{{ truncateString('Hongyi Wu', 18)}}的其他基金

Collaborative Research: CyberTraining: Implementation: Medium: T3-CIDERS: A Train-the-Trainer Approach to Fostering CI- and Data-Enabled Research in Cybersecurity
协作研究:网络培训:实施:中:T3-CIDERS:一种培训师培训方法,促进网络安全中的 CI 和数据支持研究
  • 批准号:
    2320999
  • 财政年份:
    2023
  • 资助金额:
    $ 21.34万
  • 项目类别:
    Standard Grant
IUCRC Planning Grant Old Dominion University: Center for Wireless Innovation towards Secure, Pervasive, Efficient and Resilient Next G Networks (WISPER)
IUCRC 规划拨款 Old Dominion 大学:实现安全、普遍、高效和有弹性的下一代网络 (WISPER) 的无线创新中心
  • 批准号:
    2209673
  • 财政年份:
    2022
  • 资助金额:
    $ 21.34万
  • 项目类别:
    Standard Grant
Collaborative Research: CCRI: New: Medium: A Development and Experimental Environment for Privacy-preserving and Secure (DEEPSECURE) Machine Learning
合作研究:CCRI:新:媒介:隐私保护和安全(DEEPSECURE)机器学习的开发和实验环境
  • 批准号:
    2245250
  • 财政年份:
    2022
  • 资助金额:
    $ 21.34万
  • 项目类别:
    Standard Grant
IUCRC Planning Grant Old Dominion University: Center for Wireless Innovation towards Secure, Pervasive, Efficient and Resilient Next G Networks (WISPER)
IUCRC 规划拨款 Old Dominion 大学:实现安全、普遍、高效和有弹性的下一代网络 (WISPER) 的无线创新中心
  • 批准号:
    2244902
  • 财政年份:
    2022
  • 资助金额:
    $ 21.34万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Small: Tangram: Scaling into the Exascale Era with Reconfigurable Aggregated "Virtual Chips"
合作研究:SHF:小型:七巧板:通过可重构聚合“虚拟芯片”扩展到百亿亿次时代
  • 批准号:
    2245129
  • 财政年份:
    2022
  • 资助金额:
    $ 21.34万
  • 项目类别:
    Standard Grant
Collaborative Research: CCRI: New: Medium: A Development and Experimental Environment for Privacy-preserving and Secure (DEEPSECURE) Machine Learning
合作研究:CCRI:新:媒介:隐私保护和安全(DEEPSECURE)机器学习的开发和实验环境
  • 批准号:
    2120279
  • 财政年份:
    2021
  • 资助金额:
    $ 21.34万
  • 项目类别:
    Standard Grant
NSF INCLUDES Planning Grant: Building Cybersecurity Inclusive Pathways towards Higher Education and Research (CIPHER)
NSF 包括规划拨款:构建通向高等教育和研究的网络安全包容性途径 (CIPHER)
  • 批准号:
    2012941
  • 财政年份:
    2020
  • 资助金额:
    $ 21.34万
  • 项目类别:
    Standard Grant
CyberTraining:CIC: DeapSECURE: A Data-Enabled Advanced Training Program for Cyber Security Research and Education
Cyber​​Training:CIC:DeapSECURE:用于网络安全研究和教育的数据支持高级培训计划
  • 批准号:
    1829771
  • 财政年份:
    2018
  • 资助金额:
    $ 21.34万
  • 项目类别:
    Standard Grant
Planning Grant: Engineering Research Center for Safe and Secure Artificial Intelligence Solutions (SAIS)
规划资助:安全可靠的人工智能解决方案工程研究中心(SAIS)
  • 批准号:
    1840458
  • 财政年份:
    2018
  • 资助金额:
    $ 21.34万
  • 项目类别:
    Standard Grant
MRI Acquisition: A Reconfigurable Computing Infrastructure Enabling Interdisciplinary and Collaborative Research in Hampton Roads
MRI 采集:可重新配置的计算基础设施,支持汉普顿路的跨学科和协作研究
  • 批准号:
    1828593
  • 财政年份:
    2018
  • 资助金额:
    $ 21.34万
  • 项目类别:
    Standard Grant

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协作研究:SHF:小型:LEGAS:大规模学习演化图
  • 批准号:
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    2024
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    $ 21.34万
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    2024
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