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Accelerating Neural Computation

Accelerating Neural Computation
加速神经计算
批准号:
RGPIN-2016-05700
负责人:
Dimopoulos, Nikitas
金额:
$1.6万
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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中文摘要
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英文摘要
Computing systems that have found the inspiration of their function in Biology or model the functioning of actual biological systems have been introduced for many years and have seen their development accelerating recently as advances in technology have allowed the deployment of high performance computing systems.***In this research program, we will focus on developing methods of accelerating the computations needed in neural networks. Neural networks can be viewed as (i) Artificial Neural Networks that have found applications in classification, modeling and learning, and (ii) spiking neuromorphic systems that closer resemble the structure and functioning of the central nervous system.***Our long term objective is to devise a system that can accurately emulate a part of the brain in real or near-real time. Such a system can be used in biological research to test hypotheses especially as related to diseases, and to better understand the influence of the structure on function. Such a goal is novel, as most of the current neuromorphic systems research is focusing on developing complex systems that scale, often using simplified neural models and interconnects that do not accurately represent biology. Our approach is computationally challenging, but its complexity is tractable. An additional goal is the development of systems enhancing the performance of generalizing ANN. ***It is expected that the successful completion of this research will lead to advanced study, and contribute to the understanding of complex neural systems. ***In the field of artificial neural networks, having an efficient computational environment will allow the modeling complex systems and classifiers and it will contribute to big data analytics. ***In the field of neuromorphic systems, having the ability to accurately simulate brain structures in real or near-real time, will allow researchers to experiment and understand the functioning of these brain structures. Such systems have the potential of becoming virtual laboratories to experiment on such brain structures, prod their functionality, explore how learning occurs and understand how some degenerating diseases manifest themselves.
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Accelerating Neural Computation
  • 批准号:
    RGPIN-2016-05700
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2021
  • 负责人:
    Dimopoulos, Nikitas
  • 依托单位:
Accelerating Neural Computation
  • 批准号:
    RGPIN-2016-05700
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2020
  • 负责人:
    Dimopoulos, Nikitas
  • 依托单位:
Accelerating Neural Computation
  • 批准号:
    RGPIN-2016-05700
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2018
  • 负责人:
    Dimopoulos, Nikitas
  • 依托单位:
ANN for detection and prediction of membrane fouling in water-treatment plants******
  • 批准号:
    536518-2018
  • 项目类别:
    Engage Grants Program
  • 资助金额:
    $1.82万
  • 财政年份:
    2018
  • 负责人:
    Dimopoulos, Nikitas
  • 依托单位:
国内基金
海外基金
Neural Process模型的多样化高保真技术研究