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Collaborative Research: II-NEW: Marcher - A Heterogeneous High Performance Computing Infrastructure for Research and Education in Green Computing

Collaborative Research: II-NEW: Marcher - A Heterogeneous High Performance Computing Infrastructure for Research and Education in Green Computing
协作研究:II-新:Marcher - 用于绿色计算研究和教育的异构高性能计算基础设施
批准号:
1305382
负责人:
Rong Ge
金额:
$30.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-01 至 2015-08-31

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中文摘要
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英文摘要
Excessive energy consumption is a major constraint when designing and deploying the next generation of supercomputers. Minimizing energy consumption of high performance computing requires novel energy-conscious technologies at multiple layers from architecture, system support, and applications. One obstacle that hinders the exploration of these new technologies is the lack of tools and systems that can provide accurate, fine-grained, and real-time power and energy measurement for technology evaluation and verification. This project bridges the gap by building Marcher, a heterogeneous high performance computing infrastructure equipped with cutting-edge power-efficient accelerators including Intel Many Integrated Cores and Nvidia Graphics Processing Units, power-aware memory systems, hybrid storage with hard disk drives and solid state disks, and high performance interconnects. The Marcher system supports the development of two complementary component-level power measurement tools for major computer components: (i) pluggable Power Data Acquisition Card (PODAC) for direct and decomposed power measurement and (ii) Software Power Meter (SoftMeter) that indirectly estimates the power consumption of systems where direct measurement is not feasible or too costly. Upon completion of this project, both PODAC and SoftMeter will be made available to a broader community and researchers to establish their own power-aware systems. Marcher will be open to external research groups and provide users with comprehensive and detailed performance and power profiles to aid the research in energy efficient software design and system development.
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CAREER: Optimization Landscape for Non-convex Functions - Towards Provable Algorithms for Neural Networks
  • 批准号:
    1845171
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2019
  • 负责人:
    Rong Ge
  • 依托单位:
CCF: EAGER: DeepGreen: Modeling and Boosting Accelerated Computing on Liquid Immersion Cooled HPC Systems
  • 批准号:
    1942182
  • 项目类别:
    Standard Grant
  • 资助金额:
    $26.98万
  • 财政年份:
    2019
  • 负责人:
    Rong Ge
  • 依托单位:
AF: Large: Collaborative Research: Nonconvex Methods and Models for Learning: Towards Algorithms with Provable and Interpretable Guarantees
  • 批准号:
    1704656
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2017
  • 负责人:
    Rong Ge
  • 依托单位:
CAREER: Cross-Layer Power-Bounded High Performance Computing on Emerging and Future Heterogeneous Computer Clusters
  • 批准号:
    1453775
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $45.35万
  • 财政年份:
    2015
  • 负责人:
    Rong Ge
  • 依托单位:
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)