SHF: Medium: Automatic Control Driven Resource Management in Chip Multiprocessors

SHF:中:芯片多处理器中自动控制驱动的资源管理

基本信息

  • 批准号:
    0963839
  • 负责人:
  • 金额:
    $ 89.97万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2010
  • 资助国家:
    美国
  • 起止时间:
    2010-06-01 至 2015-05-31
  • 项目状态:
    已结题

项目摘要

Future computer architectures will execute critical applications ranging from climate modeling to bioinformatics to simulations of new materials. Emerging chip multiprocessors are novel architectures that provide high performance and low power consumption. When multiple applications share the same chip multiprocessor, proper management of architectural resources becomes a critical problem. This research targets inter-application management of different types of resources found in a chip multiprocessor using robust and resilient techniques drawn from formal feedback control theory. It enables applications to satisfy their performance requirements and, at the same time, maximizes the utilization of hardware resources. This research helps to make the transition from conventional architectures to chip multiprocessors smoother, and as a result, maximizes the number of critical applications that can take advantage of these emerging architectures. The transfer of the technology being developed to IBM and HP Labs allows serious testing of the proposed strategies in large-scale architectures built from chip multiprocessors. The results from this project not only present an accurate assessment of feedback control theory in a new domain, but also get integrated into two important software infrastructures, Singularity and Xen, both used extensively by large research communities. This research also accommodates two efforts in broadening participation, CISE Visit in Engineering Weekends (VIEW) and NASA-Aerospace Education Services Project (NASA-AESP) at the Center for Science and the Schools (CSATS).
未来的计算机架构将执行从气候建模到生物信息学到新材料模拟的关键应用。新兴的片上多处理器是一种新型的高性能、低功耗体系结构。当多个应用程序共享同一片上多处理器时,架构资源的合理管理成为一个关键问题。本研究的目标是在一个芯片多处理器中发现的不同类型的资源,使用强大的和弹性的技术,从正式的反馈控制理论的应用程序间管理。它使应用程序能够满足其性能要求,同时最大限度地利用硬件资源。这项研究有助于从传统架构过渡到芯片多处理器更顺利,因此,最大限度地提高了关键应用程序的数量,可以利用这些新兴的架构。将正在开发的技术转移到IBM和HP实验室,可以在由芯片多处理器构建的大规模架构中对所提出的策略进行认真的测试。该项目的结果不仅在新领域中对反馈控制理论进行了准确的评估,而且还集成到两个重要的软件基础设施中,Singularity和Xen,这两个软件基础设施都被大型研究社区广泛使用。这项研究还提供了两个努力,扩大参与,CISE访问工程周末(VIEW)和美国宇航局航空航天教育服务项目(NASA-AESP)在科学和学校中心(CSATS)。

项目成果

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Mahmut Kandemir其他文献

Particle simulation on the Cell BE architecture
A case for core-assisted bottleneck acceleration in GPUs
GPU 中核心辅助瓶颈加速的案例
  • DOI:
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Nandita Vijaykumar;Gennady Pekhimenko;Adwait Jog;A. Bhowmick;Rachata Ausavarungnirun;Chita R. Das;Mahmut Kandemir;T. Mowry;O. Mutlu
  • 通讯作者:
    O. Mutlu
Optimizing Leakage Energy Consumption in Cache Bitlines
  • DOI:
    10.1007/s10617-005-5345-4
  • 发表时间:
    2004-03-01
  • 期刊:
  • 影响因子:
    0.900
  • 作者:
    Soontae Kim;Narayanan Vijaykrishnan;Mahmut Kandemir;Mary Jane Irwin
  • 通讯作者:
    Mary Jane Irwin
Time-constrained optimization of multi-AUV cooperative mine detection
多AUV协同探雷的时间约束优化
  • DOI:
    10.1109/oceans.2008.5151971
  • 发表时间:
    2008
  • 期刊:
  • 影响因子:
    0
  • 作者:
    R. Prins;Mahmut Kandemir
  • 通讯作者:
    Mahmut Kandemir
An I/O-Conscious Tiling Strategy for Disk-Resident Data Sets
  • DOI:
    10.1023/a:1014156327748
  • 发表时间:
    2002-01-01
  • 期刊:
  • 影响因子:
    2.700
  • 作者:
    Mahmut Kandemir;Alok Choudhary;J. Ramanujam
  • 通讯作者:
    J. Ramanujam

Mahmut Kandemir的其他文献

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{{ truncateString('Mahmut Kandemir', 18)}}的其他基金

Collaborative Research: CNS Core: Small: Resource-efficient, Strongly Consistent Replication for the Cloud
合作研究:CNS 核心:小型:资源高效、强一致性的云复制
  • 批准号:
    2149389
  • 财政年份:
    2022
  • 资助金额:
    $ 89.97万
  • 项目类别:
    Standard Grant
PPoSS: Planning: Cross-Layer Design for Cost-Effective HPC in the Cloud
PPoSS:规划:云中经济高效 HPC 的跨层设计
  • 批准号:
    2028929
  • 财政年份:
    2020
  • 资助金额:
    $ 89.97万
  • 项目类别:
    Standard Grant
SaTC: CORE: Small: Automatic Software Patching against Microarchitectual Attacks
SaTC:核心:小型:针对微架构攻击的自动软件修补
  • 批准号:
    1956032
  • 财政年份:
    2020
  • 资助金额:
    $ 89.97万
  • 项目类别:
    Standard Grant
SHF: Small: Characterizing and Optimizing 3D NAND Flash
SHF:小型:表征和优化 3D NAND 闪存
  • 批准号:
    1908793
  • 财政年份:
    2019
  • 资助金额:
    $ 89.97万
  • 项目类别:
    Standard Grant
Frameworks: Re-Engineering Galaxy for Performance, Scalability and Energy Efficiency
框架:重新设计 Galaxy 以提高性能、可扩展性和能源效率
  • 批准号:
    1931531
  • 财政年份:
    2019
  • 资助金额:
    $ 89.97万
  • 项目类别:
    Standard Grant
XPS: FULL: A Fresh Look at Near Data Computing: Coordinated Data and Computation Government
XPS:完整:近数据计算的新视角:协调数据和计算政府
  • 批准号:
    1629129
  • 财政年份:
    2016
  • 资助金额:
    $ 89.97万
  • 项目类别:
    Standard Grant
CSR: Medium: Collaborative Research: Enabling GPUs as First-Class Computing Engines
CSR:媒介:协作研究:使 GPU 成为一流的计算引擎
  • 批准号:
    1409095
  • 财政年份:
    2014
  • 资助金额:
    $ 89.97万
  • 项目类别:
    Continuing Grant
XPS: FULL:CCA: Extracting Scalable Parallelism by Relaxing the Contracts across the System Stack
XPS:FULL:CCA:通过放松整个系统堆栈的契约来提取可扩展的并行性
  • 批准号:
    1439021
  • 财政年份:
    2014
  • 资助金额:
    $ 89.97万
  • 项目类别:
    Standard Grant
SHF: Medium: Breaking the Physical Divide between Computation and NAND-Flash Storage
SHF:媒介:打破计算和 NAND 闪存存储之间的物理鸿沟
  • 批准号:
    1302557
  • 财政年份:
    2013
  • 资助金额:
    $ 89.97万
  • 项目类别:
    Continuing Grant
Collaborative Research: Adaptive Techniques for Achieving End-to-End QoS in the I/O Stack on Petascale Multiprocessors
协作研究:在千万级多处理器上的 I/O 堆栈中实现端到端 QoS 的自适应技术
  • 批准号:
    0937949
  • 财政年份:
    2009
  • 资助金额:
    $ 89.97万
  • 项目类别:
    Standard Grant

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LEAPS-MPS: A Systematic and Automatic Spectral Analysis of Physical Conditions of Circumgalactic Medium using Genetic Algorithms;
LEAPS-MPS:使用遗传算法对环绕银河系介质的物理条件进行系统自动光谱分析;
  • 批准号:
    2213494
  • 财政年份:
    2022
  • 资助金额:
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Collaborative Research: SHF: Medium: Collaborative Automatic Parallelization
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  • 批准号:
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Collaborative Research: SHF: Medium: Collaborative Automatic Parallelization
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  • 批准号:
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    2021
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    $ 89.97万
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    Continuing Grant
CHS: Medium: Critical Factors for Automatic Speech Recognition in Supporting Small Group Communication Between People who are Deaf or Hard of Hearing and Hearing Colleagues
CHS:中:自动语音识别支持聋哑人或听力障碍人士与听力正常同事之间小组交流的关键因素
  • 批准号:
    1954284
  • 财政年份:
    2020
  • 资助金额:
    $ 89.97万
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SaTC: CORE: Medium: Collaborative: Understanding and Discovering Illicit Online Business Through Automatic Analysis of Online Text Traces
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    1850725
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NeTS:媒介:协作研究:自动网络修复
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    2018
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    $ 89.97万
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  • 批准号:
    1801365
  • 财政年份:
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    $ 89.97万
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