Collaborative Research: FuSe: A Reconfigurable Ferrolectronics Platform for Collective Computing (FALCON)
合作研究:FuSe:用于集体计算的可重构铁电子平台(FALCON)
基本信息
- 批准号:2328962
- 负责人:
- 金额:$ 129万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-10-01 至 2026-09-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Digital computing has been the bedrock of the modern information revolution. However, improvements in energy efficiency and reductions in compute costs for digital hardware have decelerated. The impact of this slowdown is felt most acutely when solving computationally challenging problems, such as those in combinatorial optimization (CO), where the computational resources (energy, time, memory) required scale exponentially with problem size. Moreover, such problems find extensive real-world application in fields ranging from artificial intelligence, to autonomous driving, to airline scheduling, to power distribution, creating a practical need to develop new alternative approaches to solving such problems efficiently. Analog dynamical systems such as coupled oscillators offer a promising physics-based approach for solving such hard problems since they exhibit collective properties that are unavailable in digital systems. However, current coupled oscillator platforms address a very limited set of CO problems, exhibit little reconfigurability, and lack the hardware-algorithm ecosystem that made digital computing so successful. Therefore, the goal of this research is to develop a new analog coupled oscillator platform, FALCON, that overcomes these challenges using a cross-cutting effort that spans the development of new oscillator-based computational models to the design of new ferroelectric materials, devices, and circuits for implementing them. The research will enable fundamental advances in analog computing that will subsequently translate to performance improvements for practical applications. Furthermore, to broaden the impact of this work, the team will create an open-source repository of computational models, coupling architectures, and design schemes that will be developed through the course of this project. The team will also focus on workforce development through various activities, such as organizing an industry day, developing new courses, and creating research opportunities for students underrepresented in STEM fields.The coupled oscillator-based FALCON platform developed in this project will offer tailored coupling cores with differentiated phase synchronization dynamics that are specifically engineered such that specific classes of CO problems can be directly mapped and solved in hardware. The proposed paradigm marks a radical departure from the ‘one-size-fits-all’ approach used until now, wherein the oscillator synchronization dynamics could only be mapped to a single computational model (e.g., Ising model) that may not always be computationally efficient for the CO problem to be solved. This approach can result in significant pre-processing overhead and entail additional hardware requirements (oscillator nodes) that far exceed the size of the original problem. Moreover, the additional pre-processing and hardware needs can reduce, if not eliminate, any performance advantage of the analog approach, as well as limit its scalability. In contrast, the FALCON coupling cores will offer multiple types of synchronization dynamics, with each core facilitating the mapping of a large number of CO problems directly onto the hardware with minimal overhead. The FALCON platform will be developed through across-the-stack innovation in ferroelectric materials, devices, and mixed-signal circuits, in close conjunction with the advancement of the theoretical foundations of coupled oscillator-based computing.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
数字计算是现代信息革命的基石。然而,数字硬件的能效提高和计算成本降低的速度已经放缓。这种减速的影响在解决计算上具有挑战性的问题时最为明显,例如组合优化(CO)中的问题,其中所需的计算资源(能量,时间,内存)随问题大小呈指数级增长。此外,这些问题在从人工智能到自动驾驶,到航空公司调度,到配电的领域中找到了广泛的现实应用,从而产生了开发新的替代方法来有效解决这些问题的实际需求。模拟动态系统,如耦合振荡器提供了一个很有前途的基于物理的方法来解决这些困难的问题,因为他们表现出集体的性质,是不可用的数字系统。然而,当前的耦合振荡器平台解决了非常有限的一组CO问题,表现出很少的可重构性,并且缺乏使数字计算如此成功的硬件算法生态系统。因此,本研究的目标是开发一种新的模拟耦合振荡器平台,ESCCON,它克服了这些挑战,使用跨领域的努力,跨越了新的基于振荡器的计算模型的开发,以设计新的铁电材料,器件和电路来实现它们。这项研究将使模拟计算取得根本性进展,随后将转化为实际应用的性能改进。此外,为了扩大这项工作的影响,该团队将创建一个开源的计算模型,耦合架构和设计方案的存储库,这些都将在本项目的过程中开发。该团队还将通过各种活动,如组织工业日,开发新课程,并为在STEM领域代表性不足的学生创造研究机会。耦合振荡器-在该项目中开发的基于TMS 320 C 0 N的平台将提供具有差异化相位同步动态的定制耦合核心,这些耦合核心经过专门设计,可以直接映射特定类别的CO问题,在硬件中解决。所提出的范例标志着与迄今为止使用的“一刀切”方法的根本背离,其中振荡器同步动力学只能映射到单个计算模型(例如,Ising模型),其对于待解决的CO问题可能并不总是计算高效的。这种方法可能会导致显着的预处理开销,并需要额外的硬件要求(振荡器节点),远远超过原来的问题的大小。此外,额外的预处理和硬件需求可能会减少(如果不是消除)模拟方法的任何性能优势,并限制其可扩展性。相比之下,CPCON耦合核心将提供多种类型的同步动态,每个核心都有助于以最小的开销将大量CO问题直接映射到硬件上。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。
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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Saibal Mukhopadhyay其他文献
MACHINE LEARNING TO IDENTIFY HIGH-RISK PATIENTS AFTER STEMI IN LOW/MIDDLE INCOME COUNTRIES
- DOI:
10.1016/s0735-1097(21)01506-0 - 发表时间:
2021-05-11 - 期刊:
- 影响因子:
- 作者:
Mohit Dayal Gupta;Manu Kumar Shetty;Girish MP;Sameer Arora;Arman Qamar;Muthiah Vaduganathan;Michael Hendrickson;Puneet Gupta;Ankit Bansal;Vardhmaan Jain;Vishal Batra;Saibal Mukhopadhyay;Jamal Yusuf;Sanjay Tyagi;Ranjitha Prasad;Anubha Gupta;Bhushan Shah;Prattay Sarkar;Deepak Bhatt - 通讯作者:
Deepak Bhatt
STATIN ELIGIBILITY PER CHOLESTEROL GUIDELINES PRIOR TO STEMI IN PATIENTS IN INDIA - THE NORTH INDIA ST-ELEVATION MYOCARDIAL INFARCTION REGISTRY (NORIN-STEMI)
- DOI:
10.1016/s0735-1097(21)02815-1 - 发表时间:
2021-05-11 - 期刊:
- 影响因子:
- 作者:
Sameer Arora;Arman Qamar;Puneet Gupta;Michael Hendrickson;Avinainder Singh;Muthiah Vaduganathan;Ambarish Pandey;Ankit Bansal;Vishal Batra;Saibal Mukhopadhyay;Bhawna Mahajan;MP Girish;Jamal Yusuf;Prashant Kaul;Deepak Bhatt;Mohit Gupta - 通讯作者:
Mohit Gupta
A Generic Data-Driven Nonparametric Framework for Variability Analysis of Integrated Circuits in Nanometer Technologies
用于纳米技术集成电路可变性分析的通用数据驱动非参数框架
- DOI:
10.1109/tcad.2009.2017429 - 发表时间:
2009 - 期刊:
- 影响因子:2.9
- 作者:
Saibal Mukhopadhyay - 通讯作者:
Saibal Mukhopadhyay
Topological Representations of Heterogeneous Learning Dynamics of Recurrent Spiking Neural Networks
循环尖峰神经网络异构学习动态的拓扑表示
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Biswadeep Chakraborty;Saibal Mukhopadhyay - 通讯作者:
Saibal Mukhopadhyay
Double Kissing Mini-Culotte Stenting in Unprotected Distal Left Main Bifurcation Under Optical Coherence Tomography Guidance: Immediate and Short-Term Outcomes
- DOI:
10.1016/j.amjcard.2024.08.010 - 发表时间:
2024-10-15 - 期刊:
- 影响因子:
- 作者:
Saibal Mukhopadhyay;Jamal Yusuf;Ankit Bansal;Rupesh Agrawal;Vimal Mehta;Mohit D. Gupta;Girish M.P.;Arima Nigam;Safal Safal;Vishal Batra;Sanjeev Kathuria;Ankur Gautam;Subrat Kumar Muduli;Sumod Kurian - 通讯作者:
Sumod Kurian
Saibal Mukhopadhyay的其他文献
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{{ truncateString('Saibal Mukhopadhyay', 18)}}的其他基金
E2CDA: Type I: Collaborative Research: Energy-Efficient Artificial Intelligence with Binary RRAM and Analog Epitaxial Synaptic Arrays
E2CDA:I 型:协作研究:采用二进制 RRAM 和模拟外延突触阵列的节能人工智能
- 批准号:
1740197 - 财政年份:2017
- 资助金额:
$ 129万 - 项目类别:
Continuing Grant
CSR: Small: Exploiting 3D Integration for Power Management in Embedded Processors
CSR:小型:利用 3D 集成进行嵌入式处理器中的电源管理
- 批准号:
1218745 - 财政年份:2012
- 资助金额:
$ 129万 - 项目类别:
Standard Grant
CAREER: 3D Heterogeneous Integration for Power Reduction in Embedded Systems: Application to Wireless Image Sensing and Transport
职业:用于降低嵌入式系统功耗的 3D 异构集成:在无线图像传感和传输中的应用
- 批准号:
1054429 - 财政年份:2011
- 资助金额:
$ 129万 - 项目类别:
Continuing Grant
COLLABORATIVE RESEARCH: RECONFIGURABLE COMPUTING USING 2D NANOSCALE MEMORY ARRAY FOR MULTIMEDIA SIGNAL PROCESSING
协作研究:使用 2D 纳米级存储阵列进行可重构计算进行多媒体信号处理
- 批准号:
1002090 - 财政年份:2010
- 资助金额:
$ 129万 - 项目类别:
Standard Grant
SHF: Small: A Generic Micro-Architecture for Accuracy-Aware Ultra Low Power Multimedia Processing
SHF:小型:用于精度感知超低功耗多媒体处理的通用微架构
- 批准号:
0916083 - 财政年份:2009
- 资助金额:
$ 129万 - 项目类别:
Standard Grant
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- 批准号:10774081
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- 项目类别:面上项目
相似海外基金
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Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
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- 批准号:
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