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

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:
2008911
负责人:
Hui Zhao
金额:
$17.26万
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
项目状态:
已结题
起止时间:
2020-07-15 至 2024-06-30

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中文摘要
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英文摘要
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.
期刊论文(4)
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科研奖励(0)
会议论文
Improving GPU Throughput through Parallel Execution Using Tensor Cores and CUDA Cores
使用 Tensor 核心和 CUDA 核心通过并行执行提高 GPU 吞吐量
DOI: 10.1109/isvlsi54635.2022.00051
发表时间: 2022
期刊: 2022 IEEE Computer Society Annual Symposium on VLSI (ISVLSI
影响因子: --
作者: [Ho, Khoa, Zhao, Hui, Jog, Adwait, Mohanty, Saraju]
通讯作者: Mohanty, Saraju
Task Scheduling Strategy for Heterogeneous Multicore Systems
异构多核系统的任务调度策略
DOI: 10.1109/mce.2021.3073654
发表时间: 2022
期刊: IEEE Consumer Electronics Magazine
影响因子: 4.5
作者: [Fang, Juan, Zhang, Jiaxing, Lu, Shuaibing, Zhao, Hui, Zhang, Di, Cui, Yuwen]
通讯作者: Cui, Yuwen
DOI: 10.1109/ispass57527.2023.00026
发表时间: 2023-04
期刊: 2023 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
影响因子: --
作者: [Zhuren Liu;Shouzhe Zhang;Justin Garrigus;Hui Zhao]
通讯作者: Zhuren Liu;Shouzhe Zhang;Justin Garrigus;Hui Zhao
Predicting GPU Performance and System Parameter Configuration Using Machine Learning
使用机器学习预测 GPU 性能和系统参数配置
DOI: 10.1109/isvlsi54635.2022.00056
发表时间: 2022
期刊: 2022 IEEE Computer Society Annual Symposium on VLSI (ISVLSI
影响因子: --
作者: [Liu, Zhuren, Exley, Trevor, Meek, Austin, Yang, Rachel, Zhao, Hui, Albert, Mark V.]
通讯作者: Albert, Mark V.
Collaborative Research: Self-regulated non-equilibrium assembly of chiral colloidal clusters via electrokinetic interactions
  • 批准号:
    2314340
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $25.75万
  • 财政年份:
    2023
  • 负责人:
    Hui Zhao
  • 依托单位:
Collaborative Research: Concentration Polarization Induced Electrokinetic Flows around dielectric Surfaces
  • 批准号:
    2127852
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.56万
  • 财政年份:
    2021
  • 负责人:
    Hui Zhao
  • 依托单位:
REU Site: Interdisciplinary Research Experience on Accelerated Deep Learning through A Hardware-Software Collaborative Approach
  • 批准号:
    2051062
  • 项目类别:
    Standard Grant
  • 资助金额:
    $39.87万
  • 财政年份:
    2021
  • 负责人:
    Hui Zhao
  • 依托单位:
CAREER: Reinventing Network-on-Chips of GPU-Accelerated Systems
  • 批准号:
    2046186
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $51.9万
  • 财政年份:
    2021
  • 负责人:
    Hui Zhao
  • 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)