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CAREER: Scalable Computer Architectures of Hierarchical Noeoctex Models and K-12 Education Enhancement

CAREER: Scalable Computer Architectures of Hierarchical Noeoctex Models and K-12 Education Enhancement
职业:分层 Noeoctex 模型的可扩展计算机架构和 K-12 教育增强
批准号:
0644231
负责人:
Tarek Taha
金额:
$40.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-03-15 至 2010-09-30

项目摘要

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中文摘要
翻译
本CAREER提案的研究目标是开发计算机硬件架构,以加速基于分层新皮层模型的认知应用。这些新的认知模型在描述大脑新皮层的功能方面显示出了巨大的希望。认知应用包括感知、自然语言理解和认知反射,在国家安全、医学、交通、工业和科学等许多领域都很重要。大规模的应用也将使神经生物学家能够评估新皮层的新模型。在这项工作中,将为大规模FPGA系统和嵌入式处理应用开发受生物学启发的架构。一旦开发出这些模型,将研究一个模型来预测认知模型在其他架构上的性能。这项研究工作将通过FPGA集群实现大规模认知应用的实时实现,并通过专门的架构实现嵌入式应用的实时实现。该提案的教育目标旨在使从K-12到大学水平的学生受益。在大学层面,将开发一个建筑可视化工具,以加强建筑概念的学习。此外,从这项工作中发展出来的研究思路将通过课堂项目引入课程。在K-12阶段,将为小学生制定一套关于计算机技术的课程计划和学习工具。将通过一系列讲习班培训小学教师如何使用这些工具和课程计划。这项工作将与克莱姆森大学(Clemson University)的“Call Me Mister”项目合作实施(该项目旨在增加南卡罗来纳州少数民族学校教师的数量)。
英文摘要
The research objective of this CAREER proposal is to develop computer hardware architectures that would accelerate cognitive applications based on hierarchical neocortex models. These new class of cognitive models have shown significant promise in describing the functioning of the neocortex. Cognitive applications include perception, natural language comprehension, and cognitive reflection and are important in a large variety of domains such as national security, medicine, transportation, industry, and science. Large scale implementations will also enable neurobiologists to evaluate new models of the neocortex. In this work, biologically inspired architectures will be developed for large scale FPGA systems and embedded processing applications. Once these are developed, a model to predict the performance of the cognitive models on other architectures will be investigated. The research work will enable real-time implementations of cognitive applications at the large scale through FPGA clusters and at the embedded scale through a specialized architecture.The educational objectives of this proposal are aimed at benefiting students from the K-12 to the university level. At the university level, an architecture visualization tool to enhance learning of architecture concepts will be developed. In addition, the research ideas developed form this work will be introduced into the curriculum through classroom projects. At the K-12 level, a set of lesson plans and learning tools about computer technology will be developed for elementary school students. Elementary school teachers will be trained in the use of the tools and lesson plans through a series of workshops. This work will be implemented in collaboration with the "Call Me Mister" program at Clemson University (this program is aimed at increasing the number of minority school teachers in South Carolina).
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会议论文
SHF:Small:Neuromorphic Architectures for On-line Learning
  • 批准号:
    1718633
  • 项目类别:
    Standard Grant
  • 资助金额:
    $44.0万
  • 财政年份:
    2017
  • 负责人:
    Tarek Taha
  • 依托单位:
Collaborative Research: High Performance Cellular Simultaneous Recurrent Network based Pattern Recognition
  • 批准号:
    1309708
  • 项目类别:
    Standard Grant
  • 资助金额:
    $14.66万
  • 财政年份:
    2013
  • 负责人:
    Tarek Taha
  • 依托单位:
CAREER: Scalable Computer Architectures of Hierarchical Noeoctex Models and K-12 Education Enhancement
  • 批准号:
    1053149
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $27.25万
  • 财政年份:
    2009
  • 负责人:
    Tarek Taha
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis