CCF: Medium: Collaborative Research: SHF: Cascode: Supporting and Leveraging Voltage Stacking in Future Microprocessors
CCF:中:协作研究:SHF:共源共栅:支持和利用未来微处理器中的电压堆叠
基本信息
- 批准号:1514433
- 负责人:
- 金额:$ 61.5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-06-15 至 2019-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Power dissipation is increasingly becoming the central issue in almost all computing and communication systems from mobile devices to warehouse-scale systems. This project investigates a technology that can shave off at least a few percent of chip energy of all chips by targeting one particular aspect of power consumption that has not received as much attention as others: power delivery. In addition to the team of investigators, the project will involve graduate and undergraduate students, include members of underrepresented groups and will thus help enlarge the nation?s workforce in information technologies.Today's chips operate at low voltages (about 1V) to reduce power consumption. However, delivering the power at low voltage is problematic. For instance, it results in more delivery loss (in the real world, electricity is transported at voltages thousands of times higher than that of the usage voltage). This project will be investigating a solution called the Cascode power delivery system, which stacks multiple planes of circuit to naturally increase the effective usage (and therefore delivery) voltage. This design is not only likely to bypass some fundamental problems with other means of increasing power delivery voltage (such as using on-chip voltage converters), but also to creates new architectural opportunities such as improved communication circuits with higher voltages and better capabilities to compensate variations in the fabrication process.
从移动设备到仓库规模的系统,几乎所有的计算和通信系统的功耗都日益成为中心问题。这个项目研究了一种技术,它可以通过针对功耗的一个特定方面来削减至少百分之几的芯片能量,而这个方面并没有像其他方面那样受到那么多的关注:电力输送。除了调查小组,该项目还将涉及研究生和本科生,包括代表性不足的群体的成员,从而有助于扩大国家?美国在信息技术方面的劳动力。今天的芯片工作在低电压(约1V),以减少功耗。然而,在低电压下传输电力是有问题的。例如,它会导致更多的传输损耗(在现实世界中,电力在比使用电压高数千倍的电压下传输)。该项目将研究一种名为Cascode的电力输送系统的解决方案,该系统将多个电路平面堆叠起来,以自然地增加有效使用(从而增加输送)电压。这种设计不仅有可能绕过其他增加电力输送电压的方法(如使用片上电压转换器)的一些基本问题,而且还创造了新的架构机会,如改进的通信电路具有更高的电压和更好的能力,以补偿制造过程中的变化。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Michael Huang其他文献
An Evaluation of Falls, Syncope, and Dizziness by Prolonged Ambulatory Cardiographic Monitoring in a Geriatric Institutional Setting
在老年机构环境中通过长时间动态心电图监测评估跌倒、晕厥和头晕
- DOI:
10.1111/j.1532-5415.1982.tb03697.x - 发表时间:
1982 - 期刊:
- 影响因子:6.3
- 作者:
M. Gordon;Michael Huang;C. Gryfe - 通讯作者:
C. Gryfe
Ising-CF: A Pathbreaking Collaborative Filtering Method Through Efficient Ising Machine Learning
Ising-CF:通过高效 Ising 机器学习实现的开创性协同过滤方法
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Zhuo Liu;Yunan Yang;Zhenyu Pan;Anshujit Sharma;Amit Hasan;Caiwen Ding;Ang Li;Michael Huang;Tong Geng - 通讯作者:
Tong Geng
1550-nm wavelength-tunable HCG VCSELs
1550 nm 波长可调谐 HCG VCSEL
- DOI:
10.1117/12.2041821 - 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
C. Chase;Y. Rao;Michael Huang;C. Chang - 通讯作者:
C. Chang
Reduction in New Onset Diabetes After Transplant (NODAT) with Erythropoietin-Stimulating Agents, a Case Control Study
- DOI:
10.1016/j.jcjd.2013.08.133 - 发表时间:
2013-10-01 - 期刊:
- 影响因子:
- 作者:
Tess Montada-Atin;Diana Choi;Minna Woo;Ravi Retnakaran;Michael Huang;Ramesh Prasad;Jeffrey S. Zaltzman - 通讯作者:
Jeffrey S. Zaltzman
Performing Machine Learning Based Outlier Detection for Automotive Grade Products
对汽车级产品执行基于机器学习的异常值检测
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Y. L. Yang;P. Tsao;C. W. Lin;Ross Lee;Olivia Ni;T. T. Chen;Y. Ting;C. Lai;Jason Yeh;Arnold Yang;Wayne Huang;Peng Chen;Charly Tsai;Ryan Yang;Y. S. Huang;B. Hsu;M. Z. Lee;T. H. Lee;Michael Huang;Coming Chen;L. Chu;H. Kao;N. S. Tsai;Hsinchu Taiwan MediaTek Inc. - 通讯作者:
Hsinchu Taiwan MediaTek Inc.
Michael Huang的其他文献
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{{ truncateString('Michael Huang', 18)}}的其他基金
FET: Small: Increasing Robustness, Efficacy, and Capability of CMOS-Compatible Electronic Ising Machines
FET:小型:提高 CMOS 兼容电子发射机的鲁棒性、效率和能力
- 批准号:
2233378 - 财政年份:2023
- 资助金额:
$ 61.5万 - 项目类别:
Standard Grant
ASCENT: Using Optical Frequency Comb for Ultrafast Nature-Based Computing for Machine Learning Algorithms
ASCENT:使用光学频率梳进行机器学习算法的超快基于自然的计算
- 批准号:
2231036 - 财政年份:2022
- 资助金额:
$ 61.5万 - 项目类别:
Standard Grant
XPS: EXPL: CCA: Optical Data Containers
XPS:EXPL:CCA:光学数据容器
- 批准号:
1533842 - 财政年份:2015
- 资助金额:
$ 61.5万 - 项目类别:
Standard Grant
Software Susceptibility-Driven Non-Uniform Memory Error Protection
软件敏感性驱动的非一致内存错误保护
- 批准号:
1255729 - 财政年份:2013
- 资助金额:
$ 61.5万 - 项目类别:
Continuing Grant
CSR: Small: System Support for SSD-Backed Recoverable Network Applications
CSR:小型:对 SSD 支持的可恢复网络应用程序的系统支持
- 批准号:
1217372 - 财政年份:2012
- 资助金额:
$ 61.5万 - 项目类别:
Standard Grant
CSR: Small: Towards a Co-Designed Latency-Centric On-Chip Communication Substrate
CSR:小:迈向共同设计的以延迟为中心的片上通信基板
- 批准号:
1217662 - 财政年份:2012
- 资助金额:
$ 61.5万 - 项目类别:
Standard Grant
CAREER: Understanding and Exploring Performance-Correctness Explicitly Decoupled Architecture
职业:理解和探索性能正确性显式解耦架构
- 批准号:
0747324 - 财政年份:2008
- 资助金额:
$ 61.5万 - 项目类别:
Continuing Grant
Collaborative Research: SMA: Accurate Temperature Measurement Infrastructure and Methodology for Power, Variability, and Reliability Analysis
合作研究:SMA:用于功率、可变性和可靠性分析的精确温度测量基础设施和方法
- 批准号:
0719790 - 财政年份:2007
- 资助金额:
$ 61.5万 - 项目类别:
Continuing Grant
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