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Collaborative Research: FET: Small: Massive Scale Computing and Optimization through On-chip ParameTric Ising MAchines (OPTIMA)

Collaborative Research: FET: Small: Massive Scale Computing and Optimization through On-chip ParameTric Ising MAchines (OPTIMA)
合作研究:FET:小型:通过片上 ParameTric Ising 机器进行大规模计算和优化 (OPTIMA)
批准号:
2103091
负责人:
Philip Feng
金额:
$22.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-07-15 至 2025-06-30

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中文摘要
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英文摘要
For decades, academia and industry have relied on deterministic algorithms and on general-purpose von-Neumann computing architectures to solve combinatorial-optimization (CO) problems within natural and social sciences. As Moore’s law continues to slow down, the existing computing paradigm is reaching the limit of maximum complexity of the CO problems it can tackle, thus becoming increasingly inadequate to answer, in reasonable times, the fundamental questions that keep rising in a wide range of disciplines, spanning from engineering, physics and medicine to economics and finance. By emulating quantum systems, new computing architectures known as Ising Machines (IMs) have been emerging. IMs offer the unique opportunity to solve extraordinarily complex CO problems much faster than any existing von-Neumann counterparts. Yet, to date, no IM technology can afford a massive number of spins to handle the currently unsolvable CO problems, while ensuring a low-power consumption, a compact form factor, a chip-scale integration and a manufacturability en masse through the consolidated wafer-scale fabrication processes offered by the semiconductor industry. The goal of this project is to explore and develop a new IM, namely the first On-chip ParameTric Ising MAchine (OPTIMA). Thanks to its unique highly reprogrammable dynamics, triggered without requiring any special environmental conditions or any time-consuming pre-processing steps while exclusively requiring chip-scale components that can be monolithic integrated in favor of a massive scale production, the development of OPTIMA will pave the way towards powerful, fast and miniaturized quantum-inspired computing systems, accessible to everybody from everywhere. This will allow the creation of new cyber infrastructures that scholars, scientists, engineers and educators worldwide will be able to use in order to address relevant technological and social challenges. The project team is collaborating with STEM education and workforce development programs, at both Northeastern University and the University of Florida, to organize and host on-campus activities with students and teachers from both K-12 schools and community colleges, as well as outreach visits to local schools to encourage and broaden participation of underrepresented groups. The project achievements are enriching both the undergraduate and the graduate courses that the investigators teach on circuit theory, advanced acoustic-based technologies for communication and sensing, micro/nanoelectromechanical systems (MEMS/NEMS), and quantum engineering devices and systems. OPTIMA is leveraging the unique dynamical features governing the electrical response of a synchronized network of coupled on-chip Electro-Acoustic-Parametric-Oscillators (EAPOs) exploiting the uniquely combined ferroelectric and acoustic properties of Aluminum Scandium Nitride (AlScN) micro/nano devices to create extraordinarily low-power and highly miniaturized artificial spins, manufacturable through complementary-metal-oxide-semiconductor (CMOS) processes. Such unique features allow the breaking of all the previous paradigms in the design of IMs by simultaneously enabling 106 spins, a CMOS-compatible wafer-scale manufacturing and room-temperature operation while consuming less than 1 Watt. Further, thanks to its highly parallelized computational flow and because the EAPOs are operating in the Super-High-Frequency (SHF) range, OPTIMA is able to solve even the hardest nondeterministic polynomial time (NP) CO problems in nanosecond time scales, independently of the problem size. Finally, since OPTIMA is manufacturable through CMOS compatible processes, it is greatly leveraging conventional IC components built on the same silicon wafer to enable flexible programming, based on the CO problems of interest, as well as compact read-out schemes.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.
期刊论文(3)
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科研奖励(0)
会议论文
DOI: 10.1109/mems49605.2023.10052273
发表时间: 2023-01
期刊: 2023 IEEE 36th International Conference on Micro Electro Mechanical Systems (MEMS)
影响因子: --
作者: [Yuncong Liu;S. M. Enamul Hoque Yousuf;Afzaal Qamar;M. Rais-Zadeh;P. Feng]
通讯作者: Yuncong Liu;S. M. Enamul Hoque Yousuf;Afzaal Qamar;M. Rais-Zadeh;P. Feng
Thin Film PZT Multimode Resonant MEMS Temperature Sensor
薄膜 PZT 多模谐振 MEMS 温度传感器
DOI: 10.1109/sensors52175.2022.9967330
发表时间: 2022
期刊: Proceedings of IEEE Sensors 2022
影响因子: --
作者: [Sui, Wen, Kaisar, Tahmid, Wang, Haoran, Wu, Yihao, Lee, Jaesung, Xie, Huikai, Feng, Philip X.-L.]
通讯作者: Feng, Philip X.-L.
Retaining High Q Factors in Electrode-Less Aln-On-Si Bulk Mode Resonators with Non-Contact Electrical Drive
采用非接触式电力驱动的无电极硅基铝体模式谐振器保持高品质因数
DOI: 10.1109/mems51670.2022.9699607
发表时间: 2022
期刊: Proc. of the 35th IEEE International Conference on Micro Electro Mechanical Systems (IEEE MEMS 2022
影响因子: --
作者: [Yousuf, S M, Liu, Yuncong, Zheng, Xu-Qian, Qamar, Afzaal, Rais-Zadeh, Mina, Feng, Philip X.-L.]
通讯作者: Feng, Philip X.-L.
EAGER: Collaborative Research: Graphene Nanoelectromechanical Oscillators for Extreme Temperature and Harsh Environment Sensing
  • 批准号:
    2221881
  • 项目类别:
    Standard Grant
  • 资助金额:
    $15.89万
  • 财政年份:
    2022
  • 负责人:
    Philip Feng
  • 依托单位:
Collaborative Research: Innovating Quantum-Inspired Learning for Undergraduates in Research and Engineering
  • 批准号:
    2142552
  • 项目类别:
    Standard Grant
  • 资助金额:
    $125.0万
  • 财政年份:
    2022
  • 负责人:
    Philip Feng
  • 依托单位:
Collaborative Research: Harnessing Crystalline Phase Transition in 2D Materials for Ultra-Low-Power and Flexible Electronics
  • 批准号:
    2015670
  • 项目类别:
    Standard Grant
  • 资助金额:
    $13.71万
  • 财政年份:
    2019
  • 负责人:
    Philip Feng
  • 依托单位:
CAREER: Dynamically Tuning 2D Semiconducting Crystals and Heterostructures for Atomically-Thin Signal Processing Devices and Systems
  • 批准号:
    2015708
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.35万
  • 财政年份:
    2019
  • 负责人:
    Philip Feng
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)