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Programmable Nanophotonics for Deep Learning and Neuromorphic Computing

Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
批准号:
RGPIN-2018-05249
负责人:
Shastri, Bhavin
金额:
$2.4万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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英文摘要
SYNOPSIS. The birth of computers shaped 20th century society and science. After decades of exponential improvement, the performance of von Neumann architectures in speed, efficiency, and generality, has begun to run into fundamental limits, as the shrinking of transistors reaches its physical limits. As a result, the gap between current computing capabilities and computing needs is widening. This insufficiency is apparent in problems involving complex systems, big data, or real-time requirements. Forays into unconventional (non-von Neumann) computing have only been partially successful due to the limitations in bandwidth and energy consumption posed by metal interconnects.******VISION orm state-of-the-art microelectronic processors in energy efficiency and computational speeds by seven- and four orders-of-magnitude, respectively. Scientific objectives include: 1) devices thrustenergy efficient (attoJoule/operation) photonic neurons with graphene-based electro-optic modulators; 2) architectures thrustscalable and programmable silicon photonic neural network architectures; and 3) applications thrustphotonic processors for generalized neuromorphic computing tasks including deep learning and nonlinear optimization for model predictive control. This program focuses on these computing tasks as they are notoriously difficult to solve.******IMPACT. An experimentally-driven investigation of neuromorphic nanophotonics will serve as the first feasibility proof of using integrated photonics for scalable information processing. The proposed program has the potential to shape the emerging field of generalized compute engines beyond von-Neumann architectures and help redefine their physical limitations. The resulting technology has the potential to transform social, scientific, and technological sectors including self-navigating vehicles, bio-informatics, security, and big data. This research will contribute to the culture of innovation excellence across the scientific community and Canada. The multi-disciplinary nature of the program promises to foster collaborative ties across Canadian academic institutions and the private sector. The program's educational impact rests on uniquely positioning students for a readied workforce in academia or industry to drive tomorrow's advancements in photonics, applied physics, and engineering for 21st century challenges.
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Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
  • 批准号:
    RGPIN-2018-05249
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2022
  • 负责人:
    Shastri, Bhavin
  • 依托单位:
Cryogenic system for the exploration of low-temperature neuromorphic photonic systems
  • 批准号:
    RTI-2022-00457
  • 项目类别:
    Research Tools and Instruments
  • 资助金额:
    $10.93万
  • 财政年份:
    2021
  • 负责人:
    Shastri, Bhavin
  • 依托单位:
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
  • 批准号:
    RGPIN-2018-05249
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2021
  • 负责人:
    Shastri, Bhavin
  • 依托单位:
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
  • 批准号:
    RGPIN-2018-05249
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2020
  • 负责人:
    Shastri, Bhavin
  • 依托单位:
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