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:
    2328961
  • 负责人:
  • 金额:
    $ 69.78万
  • 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

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.
数字计算已经成为现代信息革命的基石。然而,能源效率的提高和数字硬件计算成本的降低已经放缓。在解决具有计算挑战性的问题时,这种速度放缓的影响最为明显,例如在组合优化(CO)中,所需的计算资源(能量、时间、内存)随着问题规模呈指数级增长。此外,这些问题在人工智能、自动驾驶、航班调度、配电等领域都有广泛的实际应用,因此需要开发新的替代方法来有效地解决这些问题。耦合振荡器等模拟动力系统为解决此类难题提供了一种很有前途的基于物理的方法,因为它们展示了数字系统中无法获得的集体特性。然而,目前的耦合振荡器平台只能解决非常有限的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FALCON,通过跨领域的努力克服这些挑战,该平台跨越了开发新的基于振荡器的计算模型,以设计新的铁电材料、器件和实现它们的电路。该研究将使模拟计算的基础进步,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,该团队将创建一个计算模型、耦合体系结构和设计方案的开源存储库,这些将通过这个项目的过程来开发。该团队还将通过各种活动关注劳动力发展,例如组织工业日,开发新课程,以及为STEM领域代表性不足的学生创造研究机会。该项目开发的基于耦合振荡器的FALCON平台将提供定制的耦合核,具有差异化的相位同步动力学,这些耦合核经过专门设计,可以直接在硬件中映射和解决特定类别的CO问题。所提出的范式标志着与迄今为止使用的“一刀切”方法的彻底背离,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),这对于解决CO问题可能并不总是计算效率高。这种方法可能导致显著的预处理开销,并带来远远超过原始问题大小的额外硬件需求(振荡器节点)。此外,额外的预处理和硬件需求即使不能消除,也会降低模拟方法的性能优势,并限制其可扩展性。相比之下,FALCON耦合核将提供多种类型的同步动态,每个核都有助于以最小的开销将大量CO问题直接映射到硬件上。猎鹰平台将通过铁电材料、器件和混合信号电路的跨栈创新来开发,并与基于耦合振荡器的计算理论基础的进步紧密结合。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识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

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Nikhil Shukla其他文献

Role of female sex steroids in regulating cholesteryl ester transfer protein in transgenic mice.
雌性类固醇在调节转基因小鼠胆固醇酯转移蛋白中的作用。
  • DOI:
  • 发表时间:
    1998
  • 期刊:
  • 影响因子:
    0
  • 作者:
    S. Vadlamudi;Paul S. MacLean;Thomas D. Green;Nikhil Shukla;John F. Bradfield;Stephen J. Vore;Hisham A. Barakat
  • 通讯作者:
    Hisham A. Barakat
A Note on Analyzing the Stability of Oscillator Ising Machines
振荡机稳定性分析的一个注记
  • DOI:
    10.48550/arxiv.2310.09322
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. K. Bashar;Z. Lin;Nikhil Shukla
  • 通讯作者:
    Nikhil Shukla
Designing a K-state P-bit Engine
设计 K 状态 P 位引擎
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. K. Bashar;Abir Hasan;Nikhil Shukla
  • 通讯作者:
    Nikhil Shukla
An FPGA-based Max-K-Cut Accelerator Exploiting Oscillator Synchronization Model
基于 FPGA 的利用振荡器同步模型的 Max-K-Cut 加速器
Pro12Ala Polymorphism in PPARγ Is Associated With Lower Risk of Mechanical Ventilation After Coronary Artery Bypass Graft Surgery (CABG
  • DOI:
    10.1378/chest.124.4_meetingabstracts.103s-b
  • 发表时间:
    2003-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Sachin Yende;Richard G. Wunderink;Michael W. Quasney;Theodore J. Sandiford;Nikhil Shukla;Qing Zhang;Charles R. Yates
  • 通讯作者:
    Charles R. Yates

Nikhil Shukla的其他文献

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{{ truncateString('Nikhil Shukla', 18)}}的其他基金

ASCENT: Ferroelectric-based Compute-in-Memory Dynamical Engine (Ferro-CoDE) to Solve Hard Combinatorial Optimization
ASCENT:基于铁电的内存计算动态引擎 (Ferro-CoDE) 解决硬组合优化问题
  • 批准号:
    2132918
  • 财政年份:
    2021
  • 资助金额:
    $ 69.78万
  • 项目类别:
    Standard Grant
Using an Insulator-Metal Transition to Overcome the Fundamental Limits of Non-Volatile Memory Based on Ferroelectric Field Effect Transistors
利用绝缘体-金属转变克服基于铁电场效应晶体管的非易失性存储器的基本限制
  • 批准号:
    1914730
  • 财政年份:
    2019
  • 资助金额:
    $ 69.78万
  • 项目类别:
    Standard Grant

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Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
  • 批准号:
    2328975
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    2024
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    $ 69.78万
  • 项目类别:
    Continuing Grant
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
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    $ 69.78万
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    Continuing Grant
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
  • 批准号:
    2328972
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    2024
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    $ 69.78万
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    Continuing Grant
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
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    2024
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Collaborative Research: FuSe: Indium selenides based back end of line neuromorphic accelerators
合作研究:FuSe:基于硒化铟的后端神经形态加速器
  • 批准号:
    2328741
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Collaborative Research: FuSe: Interconnects with Co-Designed Materials, Topology, and Wire Architecture
合作研究:FuSe:与共同设计的材料、拓扑和线路架构互连
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Collaborative Research: FuSe: Interconnects with Co-Designed Materials, Topology, and Wire Architecture
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