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Fast and Scalable Model Order Reduction Technique for Accelerating the Simulation of Next-Generation VLSI Designs

Fast and Scalable Model Order Reduction Technique for Accelerating the Simulation of Next-Generation VLSI Designs
用于加速下一代 VLSI 设计仿真的快速且可扩展的模型降阶技术
批准号:
518621-2018
负责人:
Bekmambetova, Fadime
金额:
$1.53万
依托单位:
依托单位国家:
加拿大
项目类别:
Postgraduate Scholarships - Doctoral
财政年份:
2020
资助国家:
加拿大
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31

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中文摘要
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英文摘要
Model order reduction, Circuit simulation, Interconnect modeling
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Fast and Scalable Model Order Reduction Technique for Accelerating the Simulation of Next-Generation VLSI Designs
  • 批准号:
    518621-2018
  • 项目类别:
    Postgraduate Scholarships - Doctoral
  • 资助金额:
    $1.53万
  • 财政年份:
    2019
  • 负责人:
    Bekmambetova, Fadime
  • 依托单位:
Fast and Scalable Model Order Reduction Technique for Accelerating the Simulation of Next-Generation VLSI Designs
  • 批准号:
    518621-2018
  • 项目类别:
    Postgraduate Scholarships - Doctoral
  • 资助金额:
    $1.53万
  • 财政年份:
    2018
  • 负责人:
    Bekmambetova, Fadime
  • 依托单位:
Innovative Model Order Reduction Techniques for the Design of Next-Generation Integrated Circuits
  • 批准号:
    515093-2017
  • 项目类别:
    Alexander Graham Bell Canada Graduate Scholarships - Master's
  • 资助金额:
    $1.27万
  • 财政年份:
    2017
  • 负责人:
    Bekmambetova, Fadime
  • 依托单位:
A New Accelerated FDTD Method for EM Problems Involving Human Models
  • 批准号:
    497135-2016
  • 项目类别:
    University Undergraduate Student Research Awards
  • 资助金额:
    $0.33万
  • 财政年份:
    2016
  • 负责人:
    Bekmambetova, Fadime
  • 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