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Collaborative Research: Feedback-Driven Resiliency for Near-Threshold Systems

Collaborative Research: Feedback-Driven Resiliency for Near-Threshold Systems
协作研究:反馈驱动的近阈值系统弹性
批准号:
1255937
负责人:
Chris Kim
金额:
$9.6万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-04-01 至 2017-03-31

项目摘要

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中文摘要
翻译
近阈值电压(NTV)操作已经成为一种很有前途的策略,通过降低电源电压来提高能源效率,同时利用并行性来补偿频率损失。与“Turbo模式”相结合的NTV处理器还可以提供峰值性能,从而使它们适合各种动态工作负载行为。尽管前景光明,但由于许多问题,这些系统的应用在很大程度上仍然难以捉摸。该研究首次涉及VLSI电路、计算机体系结构和软件系统,解决了NTV/Turbo模式系统在器件老化和可变性背景下的可靠性挑战。研究人员将集成分布式系统监控和控制,以实现片上NTV/ turbo模式核心的节能故障恢复能力。这项工作将为反馈导向的优化系统奠定基础,该系统通过平衡性能、可靠性和能耗来调整硬件的执行以满足应用需求。我们社会的生产力和进步与世界计算基础设施的可预测和可持续运行密切相关。不幸的是,由于不断增加的计算机能耗,这种趋势开始动摇。积极的能源削减与不稳定的计算机系统性能和寿命紧密相连。这项研究将揭示克服近阈值电压系统问题所必需的观察结果,这对进一步的高级计算有很大的希望。利用硬件和软件两层的方法,研究人员将研究和开发新的技术来克服能源问题。这种跨层次的整体和共同努力是确保我们的社会在先进计算的基础上取得长期成功的关键。
英文摘要
Near-threshold voltage (NTV) operation has emerged as a promising strategy to improve energy-efficiency by reducing the supply voltage while exploiting parallelism to compensate for frequency loss. NTV processors combined with "Turbo mode" can also offer peak performance, thereby making them suitable for a range of dynamic workload behaviors. Despite the promise, applications of these systems have remained largely elusive due to many issues. This research, involving VLSI circuits, computer architecture, and software systems, for the first time, addresses the reliability challenges of NTV/Turbo mode systems in the context of device aging and variability. Researchers will integrate distributed system monitors and controls to enable power-efficient fault resiliency for on-chip NTV/Turbo-mode cores. The work will lay the foundations for a feedback-directed optimization system that tunes the hardware's execution to meet application requirements by balancing performance, reliability and energy consumption.Our society's productivity and advancements are intimately tied to the predictable and sustainable operation of the world's computing infrastructure. Unfortunately, this trend is beginning to falter due to increasing computer energy consumption. Aggressive energy reductions are tightly coupled with destabilizing computer system performance and longevity. The research will uncover observations that are necessary to overcome the problem in near-threshold voltage systems that hold great promise for further advanced computing. Using an approach spanning both the hardware and software layers, researchers will investigate and develop novel techniques to overcome the energy problem. Such a holistic and joint effort across the layers is the key for ensuring our society's long-term success based on advanced computing.
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ASCENT: TUNA: TUnable randomness for NAtural computing
  • 批准号:
    2230963
  • 项目类别:
    Standard Grant
  • 资助金额:
    $150.0万
  • 财政年份:
    2022
  • 负责人:
    Chris Kim
  • 依托单位:
Collaborative Research: Innovating Quantum-Inspired Learning for Undergraduates in Research and Engineering
SHF: Medium: Time Based Deep Neural Networks: An Integrated Hardware-Software Approach
  • 批准号:
    1763761
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $90.0万
  • 财政年份:
    2018
  • 负责人:
    Chris Kim
  • 依托单位:
A Sub-2V Printed Flexible Organic RFID System Design for Long Range Communication
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)