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

基本信息

  • 批准号:
    1255892
  • 负责人:
  • 金额:
    $ 9.6万
  • 依托单位:
  • 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
  • 起止时间:
    2013-04-01 至 2017-03-31
  • 项目状态:
    已结题

项目摘要

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.
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。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Vijay Janapa Reddi其他文献

Bendable non-silicon RISC-V microprocessor
可弯曲的非硅 RISC-V 微处理器
  • DOI:
    10.1038/s41586-024-07976-y
  • 发表时间:
    2024-09-25
  • 期刊:
  • 影响因子:
    48.500
  • 作者:
    Emre Ozer;Jedrzej Kufel;Shvetank Prakash;Alireza Raisiardali;Olof Kindgren;Ronald Wong;Nelson Ng;Damien Jausseran;Feras Alkhalil;David Kong;Gage Hills;Richard Price;Vijay Janapa Reddi
  • 通讯作者:
    Vijay Janapa Reddi
Web search using mobile cores
使用移动核心的网络搜索
  • DOI:
    10.1145/1816038.1816002
  • 发表时间:
    2010
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Vijay Janapa Reddi;Benjamin C. Lee;Trishul M. Chilimbi;Kushagra Vaid
  • 通讯作者:
    Kushagra Vaid
Predictive Guardbanding: Program-driven Timing Margin Reduction for GPUs
预测性保护带:程序驱动的 GPU 时序裕度减少
The neurobench framework for benchmarking neuromorphic computing algorithms and systems
用于神经形态计算算法和系统基准测试的神经基准框架
  • DOI:
    10.1038/s41467-025-56739-4
  • 发表时间:
    2025-02-11
  • 期刊:
  • 影响因子:
    15.700
  • 作者:
    Jason Yik;Korneel Van den Berghe;Douwe den Blanken;Younes Bouhadjar;Maxime Fabre;Paul Hueber;Weijie Ke;Mina A. Khoei;Denis Kleyko;Noah Pacik-Nelson;Alessandro Pierro;Philipp Stratmann;Pao-Sheng Vincent Sun;Guangzhi Tang;Shenqi Wang;Biyan Zhou;Soikat Hasan Ahmed;George Vathakkattil Joseph;Benedetto Leto;Aurora Micheli;Anurag Kumar Mishra;Gregor Lenz;Tao Sun;Zergham Ahmed;Mahmoud Akl;Brian Anderson;Andreas G. Andreou;Chiara Bartolozzi;Arindam Basu;Petrut Bogdan;Sander Bohte;Sonia Buckley;Gert Cauwenberghs;Elisabetta Chicca;Federico Corradi;Guido de Croon;Andreea Danielescu;Anurag Daram;Mike Davies;Yigit Demirag;Jason Eshraghian;Tobias Fischer;Jeremy Forest;Vittorio Fra;Steve Furber;P. Michael Furlong;William Gilpin;Aditya Gilra;Hector A. Gonzalez;Giacomo Indiveri;Siddharth Joshi;Vedant Karia;Lyes Khacef;James C. Knight;Laura Kriener;Rajkumar Kubendran;Dhireesha Kudithipudi;Shih-Chii Liu;Yao-Hong Liu;Haoyuan Ma;Rajit Manohar;Josep Maria Margarit-Taulé;Christian Mayr;Konstantinos Michmizos;Dylan R. Muir;Emre Neftci;Thomas Nowotny;Fabrizio Ottati;Ayca Ozcelikkale;Priyadarshini Panda;Jongkil Park;Melika Payvand;Christian Pehle;Mihai A. Petrovici;Christoph Posch;Alpha Renner;Yulia Sandamirskaya;Clemens J. S. Schaefer;André van Schaik;Johannes Schemmel;Samuel Schmidgall;Catherine Schuman;Jae-sun Seo;Sadique Sheik;Sumit Bam Shrestha;Manolis Sifalakis;Amos Sironi;Kenneth Stewart;Matthew Stewart;Terrence C. Stewart;Jonathan Timcheck;Nergis Tömen;Gianvito Urgese;Marian Verhelst;Craig M. Vineyard;Bernhard Vogginger;Amirreza Yousefzadeh;Fatima Tuz Zohora;Charlotte Frenkel;Vijay Janapa Reddi
  • 通讯作者:
    Vijay Janapa Reddi

Vijay Janapa Reddi的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Vijay Janapa Reddi', 18)}}的其他基金

Collaborative Research: Conference: DESC: Type III: Eco Edge - Advancing Sustainable Machine Learning at the Edge
协作研究:会议:DESC:类型 III:生态边缘 - 推进边缘的可持续机器学习
  • 批准号:
    2342497
  • 财政年份:
    2024
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
Collaborative Research: DESC: Type 2: Delphi: Life-time aware design frameworks for sustainable edge devices
合作研究:DESC:类型 2:Delphi:可持续边缘设备的生命周期感知设计框架
  • 批准号:
    2324862
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
SHF: Small: High-Performance, Energy-Efficient Mobile Web Computing
SHF:小型:高性能、高能效的移动网络计算
  • 批准号:
    1619283
  • 财政年份:
    2016
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
SHF: Small: Collaborative Research: Resilient Computing Systems Using Deep Learning Techniques
SHF:小型:协作研究:使用深度学习技术的弹性计算系统
  • 批准号:
    1528045
  • 财政年份:
    2015
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
SHF: Small: Cross-Layer Solutions for Sustainable and Reliable Computing Systems
SHF:小型:可持续、可靠计算系统的跨层解决方案
  • 批准号:
    1218474
  • 财政年份:
    2012
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
Cell Research
  • 批准号:
    31224802
  • 批准年份:
    2012
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research
  • 批准号:
    31024804
  • 批准年份:
    2010
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research (细胞研究)
  • 批准号:
    30824808
  • 批准年份:
    2008
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
  • 批准号:
    10774081
  • 批准年份:
    2007
  • 资助金额:
    45.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research [FW-HTF-RL]: Enhancing the Future of Teacher Practice via AI-enabled Formative Feedback for Job-Embedded Learning
协作研究 [FW-HTF-RL]:通过人工智能支持的工作嵌入学习形成性反馈增强教师实践的未来
  • 批准号:
    2326170
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
Collaborative Research: Examining Cloud-Radiation Feedback at Convective Scales in Tropical Cyclones
合作研究:检查热带气旋对流尺度的云辐射反馈
  • 批准号:
    2331121
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Continuing Grant
IntBIO: Collaborative Research: Feedback between physiological performance and social foraging in multi-species social network of wintering birds
IntBIO:合作研究:越冬鸟类多物种社交网络中生理表现和社交觅食之间的反馈
  • 批准号:
    2316374
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
Collaborative Research: Studying Carbon Injection and the Silicate Weathering Feedback over the Paleocene Eocene Thermal Maximum Using Ca Isotopes and Modeling
合作研究:利用 Ca 同位素和模拟研究古新世始新世热最大值期间的碳注入和硅酸盐风化反馈
  • 批准号:
    2233961
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
Collaborative Research [FW-HTF-RL]: Enhancing the Future of Teacher Practice via AI-enabled Formative Feedback for Job-Embedded Learning
协作研究 [FW-HTF-RL]:通过人工智能支持的工作嵌入学习形成性反馈增强教师实践的未来
  • 批准号:
    2326169
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
Collaborative Research: Discriminating Between Galactic Feedback Models with Next Generation Observations
合作研究:区分银河反馈模型与下一代观测
  • 批准号:
    2346977
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
Collaborative Research: DMREF: Synthetic machines from feedback-controlled active matter
合作研究:DMREF:反馈控制活性物质的合成机器
  • 批准号:
    2324195
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
IntBIO: Collaborative Research: Feedback between physiological performance and social foraging in multi-species social network of wintering birds
IntBIO:合作研究:越冬鸟类多物种社交网络中生理表现和社交觅食之间的反馈
  • 批准号:
    2316373
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
Collaborative Research: Studying Carbon Injection and the Silicate Weathering Feedback over the Paleocene Eocene Thermal Maximum Using Ca Isotopes and Modeling
合作研究:利用 Ca 同位素和模拟研究古新世始新世热最大值期间的碳注入和硅酸盐风化反馈
  • 批准号:
    2233962
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
Collaborative Research: Cloud-Radiative Feedback as the Coupling Mechanism of the Madden-Julian Oscillation and Quasi-Biennial Oscillation
合作研究:云辐射反馈作为马登-朱利安振荡和准两年振荡的耦合机制
  • 批准号:
    2303505
  • 财政年份:
    2023
  • 资助金额:
    $ 9.6万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了