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SHF: Small: Collaborative Research: A Novel Method for the Performance Analysis of VLSI Circuits with Severe Parameter Value Variations due to Nano-scale Process

SHF: Small: Collaborative Research: A Novel Method for the Performance Analysis of VLSI Circuits with Severe Parameter Value Variations due to Nano-scale Process
SHF:小型:协作研究:一种用于纳米级工艺导致参数值变化严重的 VLSI 电路性能分析的新方法
批准号:
1115556
负责人:
Dian Zhou
金额:
$17.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-07-01 至 2015-06-30

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中文摘要
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英文摘要
The advance of VLSI technology has reached to 32nm feature size and below. For such a nano-scale process, lithography no longer produces the ideal shape/dimension of circuit components in a silicon wafer, and the corresponding electrical parameters may vary as large as 1/3 or more. A major concern in VLSI design is how to evaluate the circuits/systems performance made in such nano-scale process. In the other words, we want to know how much the performance specs will change due to variation in circuit parameters from their nominal values caused by the process uncertainties. The current research on performance robustness analysis is developed mainly along the line of the Monte-Carlo sampling method, or stochastic and statistical analysis methods. They all require a high level of computation complexity to achieve the required accuracy and one would like to avoid the evaluation of large number of samples to validate the performance range of a VLSI circuit/system. In this research the PIs propose a novel method for VLSI circuit performance robustness analysis which does not require evaluation of large numbers of samples. Instead, it computes only a few critical polynomials in frequency domain, or critical systems in time domain. It is a fundamentally new way to analyze VLSI circuit performance robustness. The consequent leap of computation efficiency would make nano-scale VLSI circuit design and its performance robustness analysis practically possible. The objectives of this project are: (i) to develop a solid theoretical basis for the performance robustness analysis of VLSI circuits in both frequency and time domains; (ii) to develop an efficient, novel method for computing VLSI circuit performance variation bounds and distribution (due to the process variation) without using the Monte-Carlo method.The broad impact of this project will be its potentially transformative effect on the robust analysis methods for VLSI circuits. This research will be integrated into the graduate education of the Ph.D. students at the two universities involved, and disseminated by publications in journals and presentations at conferences, a workshop and collaboration with industry, and will hopefully contribute to broad thinking across multiple disciplines.
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Collaborative Research: Numerical Computations of Parasitic Parameters with Spectral Stochastic Collocation Methods for Nano-VLSI Technologies
  • 批准号:
    0727751
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.0万
  • 财政年份:
    2007
  • 负责人:
    Dian Zhou
  • 依托单位:
Wavelet Based Nonlinear Companding Method for Analog Circuit Behavioral Modeling
  • 批准号:
    0306298
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $0.0万
  • 财政年份:
    2003
  • 负责人:
    Dian Zhou
  • 依托单位:
Efficient and Performance Guaranteed Methods for Order Reduction and Analysis of VLSI Interconnect Circuits
  • 批准号:
    0098275
  • 项目类别:
    Standard Grant
  • 资助金额:
    $39.42万
  • 财政年份:
    2001
  • 负责人:
    Dian Zhou
  • 依托单位:
NSF Young Investigator: Performance-Driven VLSI Designs
  • 批准号:
    9996429
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $7.43万
  • 财政年份:
    1999
  • 负责人:
    Dian Zhou
  • 依托单位:
国内基金
海外基金
昼夜节律性small RNA在血斑形成时间推断中的法医学应用研究
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
  • 依托单位:
tRNA-derived small RNA上调YBX1/CCL5通路参与硼替佐米诱导慢性疼痛的机制研究
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2022
  • 负责人:
    张祥忠
  • 依托单位:
Small RNA调控I-F型CRISPR-Cas适应性免疫性的应答及分子机制
Small RNAs调控解淀粉芽胞杆菌FZB42生防功能的机制研究
  • 批准号:
    31972324
  • 项目类别:
    面上项目
  • 资助金额:
    58.0万元
  • 批准年份:
    2019
  • 负责人:
    高学文
  • 依托单位: