BRIGE: Minimum-Energy Bio-Inspired Analogic Computing Devices with Stochastic Switching Transistors under Ultra-Low VDD
BRIGE:超低 VDD 下具有随机开关晶体管的最低能耗仿生模拟计算设备
基本信息
- 批准号:1342225
- 负责人:
- 金额:$ 14.84万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-09-15 至 2016-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
ECCS-1342225Lin, MingjieUniversity of Central FloridaBRIGE: Minimum-Energy Bio-Inspired AnaLogic Computing Devices with Stochastic Switching Transistors under Ultra-Low VDDABSTRACTIntellectual Merit: This BRIGE project aims at achieving robust ultra-low power computation by exploiting the stochastic switching behavior observed within a CMOS digital circuit that is driven by an ultra-low supply voltage approaching the digital switching limit. This objective is motivated by two observations. First, probabilistic inference and stochastic learning are fundamental in sensor data processing. Second, emerging devices will exhibit sophisticated physical property that may natively compute probabilistic algorithms. This proposed effort will first model and analyze the stochastic switching behavior in minimum-energy CMOS transistors under ultra-low VDD (¡Ö 50mV) both analytically and experimentally. Subsequently, it will develop a field-theoretic methodology to optimize a large-scale logic circuit built with such stochastic switching devices in order to improve its robustness. Finally, it will exploit the stochastic switching behavior natively to design and implement AnaLogic circuits (between analog and logic circuits) that emulate a robust self-motion algorithm inspired by fly eye based on optical flow extraction.Broader Impacts: Leveraging the physics of field-effect devices to perform computational tasks, this proposed research could potentially inspire a totally unconventional design paradigm for emerging nanoscale device technology with severe device variability and switching uncertainty. Furthermore, the proposed field-theoretic approach offers a rich mathematical structure, therefore can broaden the current digital circuit design theory. Finally, the proposed methodology can enable more accurate understanding of existing logic circuit design methods, especially on their limitations when directly applied to future device technologies driven by ultra-low VDD. Besides disseminating its research findings through new curricula and hardware-based stochastic logic circuit emulations, this project will approach the challenge of broadening the engineering participation from underrepresented minority groups in both bottom-up (public STEM education) and top-down (PhD students recruiting) directions. The PI will create mentoring and outreach programs specifically designed to attract female, African-American, Latino, and first-generation college students to join his group, thus preparing a new diverse work force for the computing industry. Additionally, the Orlando Science Center will be used as the main platform to stimulate public interests in STEM education of computing. The success of this educational effort, through innovative exhibits and engaging mini-lectures, will be judged by the PhD enrollment of computer engineering from underrepresented groups at UCF and the size of public audience to its collaborative exhibit efforts with the Orlando Science Center.
ECCS-1342225Lin,明杰中佛罗里达大学BRIGE:超低 VDD 下具有随机开关晶体管的最低能量仿生模拟计算设备摘要智力优点:该 BRIGE 项目旨在通过利用在一个随机开关中观察到的行为来实现强大的超低功耗计算。由接近数字开关的超低电源电压驱动的 CMOS 数字电路这一目标是由两个观察推动的。首先,概率推理和随机学习是传感器数据处理的基础,其次,新兴设备将表现出可以本地计算概率算法的复杂物理特性。通过分析和实验研究最小能量 CMOS 晶体管在超低 VDD (± 50mV) 下的开关行为,随后将开发一种场论方法来优化使用该器件构建的大规模逻辑电路。最后,它将利用本机的随机开关行为来设计和实现模拟逻辑电路(模拟电路和逻辑电路之间),该电路模拟受基于光流的蝇眼启发的鲁棒自运动算法。更广泛的影响:利用场效应器件的物理原理来执行计算任务,这项拟议的研究可能会激发一种完全非传统的设计范式,用于新兴的纳米级器件技术,该技术具有严重的器件可变性和开关不确定性。场论方法提供了丰富的数学结构,因此可以拓宽当前的数字电路设计理论,最后,所提出的方法可以使人们更准确地理解现有的逻辑电路设计方法,特别是直接应用于未来器件技术驱动时的局限性。除了通过新课程和基于硬件的随机逻辑电路仿真传播其研究成果外,该项目还将应对扩大代表性不足的少数群体在自下而上(公共 STEM 教育)和自上而下的工程参与的挑战。向下(博士生招募)方向。 PI 将创建专门旨在吸引女性、非裔美国人、拉丁裔和第一代大学生加入他的团队的指导和外展计划,从而为计算机行业准备一支新的多元化劳动力队伍。此外,奥兰多科学中心将作为激发公众对计算机 STEM 教育兴趣的主要平台。通过创新的展览和引人入胜的迷你讲座,这一教育工作的成功将取决于计算机工程博士的入学情况。 UCF 代表性不足的群体及其规模公众观众对其与奥兰多科学中心的合作展览工作。
项目成果
期刊论文数量(0)
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专利数量(0)
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Mingjie Lin其他文献
Stochastic-Based Deep Convolutional Networks with Reconfigurable Logic Fabric
具有可重构逻辑结构的基于随机的深度卷积网络
- DOI:
10.1109/tmscs.2016.2601326 - 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
Mohammed Alawad;Mingjie Lin - 通讯作者:
Mingjie Lin
Stochastically computing discrete Fourier transform with reconfigurable digital fabric
使用可重构数字结构随机计算离散傅里叶变换
- DOI:
10.1109/reconfig.2014.7032558 - 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Yu Bai;Mingjie Lin - 通讯作者:
Mingjie Lin
Stochastic-Based Spin-Programmable Gate Array with Emerging MTJ Device Technology
采用新兴 MTJ 器件技术的基于随机的自旋可编程门阵列
- DOI:
10.3390/jlpea6030015 - 发表时间:
2016 - 期刊:
- 影响因子:2.1
- 作者:
Y. Bai;Mingjie Lin - 通讯作者:
Mingjie Lin
Performance Benefits of Monolithically Stacked 3-D FPGA
单片堆叠 3D FPGA 的性能优势
- DOI:
10.1145/1117201.1117219 - 发表时间:
2006 - 期刊:
- 影响因子:2.9
- 作者:
Mingjie Lin;A. El Gamal;Yi;S. Wong - 通讯作者:
S. Wong
Boosting Memory Performance of Many-Core FPGA Device through Dynamic Precedence Graph
通过动态优先级图提升众核 FPGA 器件的内存性能
- DOI:
10.1109/fccm.2013.39 - 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
Yunru Bai;Abigail Fuentes;Mike Riera;Mohammed Alawad;Mingjie Lin - 通讯作者:
Mingjie Lin
Mingjie Lin的其他文献
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{{ truncateString('Mingjie Lin', 18)}}的其他基金
SHF: Small: Graph-X: Exploiting Hidden Parallelism of Irregular and Non-Stencil Computation in High-Level Synthesis
SHF:小:Graph-X:在高级综合中利用不规则和非模板计算的隐藏并行性
- 批准号:
1908177 - 财政年份:2019
- 资助金额:
$ 14.84万 - 项目类别:
Standard Grant
CAREER: iMPACT: Metaphysical and Probabilistic-Based Computing Transformation with Emerging Spin-Transfer Torque Device Technology
职业:iMPACT:利用新兴的自旋转移扭矩器件技术进行形而上学和基于概率的计算转型
- 批准号:
1553056 - 财政年份:2016
- 资助金额:
$ 14.84万 - 项目类别:
Continuing Grant
SHF: Small: Bio-Inspired Logic Design with Graph and Field Theory
SHF:小:利用图和场论进行仿生逻辑设计
- 批准号:
1319884 - 财政年份:2013
- 资助金额:
$ 14.84万 - 项目类别:
Standard Grant
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