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Toward innovative, robust, energy-efficient and probabilistic circuit and system architectures based on nanoscale devices

Toward innovative, robust, energy-efficient and probabilistic circuit and system architectures based on nanoscale devices
迈向基于纳米级器件的创新、稳健、节能和概率电路和系统架构
批准号:
386722-2010
负责人:
Han, Jie
金额:
$1.68万
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:
2014
资助国家:
加拿大
项目状态:
已结题
起止时间:
2014-01-01 至 2015-12-31

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中文摘要
翻译
在过去的几十年里,计算机变得越来越便宜,同时功能也越来越强大。这是由于电子设备的不断缩小,使得越来越多的零部件可以以相对较低的成本封装到一块芯片中。然而,这种增长趋势并不是永无止境的,预计很快就会碰壁。在目前硅技术已经达到纳米(十亿分之一米)的制度下,硅和其他纳米级(或纳米技术)设备都开始出现可靠性差、误码率高和功耗高等问题。纳米设备的这些新特征挑战了关于计算机是如何制造的传统思维。
英文摘要
In the past decades, computers have been getting cheaper and at the same time more powerful. This is due to the continuous shrinking of electronic devices, so that more and more components can be packed into a single chip with a relatively low cost. However, this scaling trend is not endless and is predicted to be soon hitting a brick wall. In the nanometer (one billionth of a meter) regime, where the current silicon technology has reached, both silicon and other nanometer-scale (or nanotechnology) devices start to have problems such as poor reliabilities, high error rates and high power consumption. These new characteristics of nanoscale devices challenge the traditional thinking about how computers are made.
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Approximate and Stochastic Computing Systems
  • 批准号:
    RGPIN-2020-06572
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2022
  • 负责人:
    Han, Jie
  • 依托单位:
Efficient computing systems for deep learning and combinatorial optimization
  • 批准号:
    552712-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $4.66万
  • 财政年份:
    2021
  • 负责人:
    Han, Jie
  • 依托单位:
Approximate and Stochastic Computing Systems
  • 批准号:
    RGPIN-2020-06572
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2021
  • 负责人:
    Han, Jie
  • 依托单位:
Low-power and high-performance circuit modules for digital signal processing, wireless communications and deep learning
  • 批准号:
    561173-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $3.64万
  • 财政年份:
    2021
  • 负责人:
    Han, Jie
  • 依托单位:
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