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
• 负责人: Nikhil Shukla
• 金额: $ 149.87万
• 依托单位: University of Virginia Main Campus
• 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
• 起止时间: 2021-08-15 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2132918&HistoricalAwards=false
• 关键词: ASCENT; Ferroelectric; based; Compute; Memory

Not all computing problems are created equal. At the heart of many, increasingly important, applications ranging from the design of intelligent machines that can explain their decisions, to electronic design automation for tamper-proof integrated circuits, lies a class of combinatorial optimization problems that remain an unconquered bastion of traditional digital computing. As a case in point, solving the archetypal Boolean satisfiability problem, integral to many such applications, requires exponentially increasing energy and computation time that makes its practical deployment at large scales unfeasible. The proposed research aims to address this challenge through a cohesive across-the-stack effort that spans from the formulation of a physics-inspired computational model to designing a supporting hardware ecosystem that encompasses novel engineered materials and devices, circuits, and their subsequent system integration. The foundational principle of the Ferroelectric-based Compute-in-Memory Dynamical Engine (FerroCoDE) is based on exploiting the inherent efficiency of physical phenomena in nature (namely, maximization of entropy production) by creating unique synergies between physics and computation. To execute these computational models efficiently, the team of researchers is developing a new hardware platform that converges the unique capabilities of dynamical systems with compute-in-memory architectures, enabled through fundamental innovation in ferroelectric materials and their device functionalities. The FerroCoDE platform will enable orders-of-magnitude improvement in computational efficiency enabling the deployment of relevant applications at a scale and in (energy-constrained) environments that are presently challenging to achieve using present day computers. Furthermore, to broaden the impact of this work, the team will develop a publicly accessible online platform, OscWorks, for applying oscillator-based computing in education and research. Additionally, the team will engage with K-12 and undergraduate students through various initiatives such as workshops, online seminars, and research opportunities.The systems challenge that is being addressed by this ASCENT project is to design, fabricate and demonstrate a Ferroelectric Hafnium Oxide (HfO2) based Compute-in-Memory (CiM) Dynamical Engine (FerroCoDE) that leverages the rich non-linear analog dynamics of oscillators in conjunction with the area and energy efficiency of ferroelectric CiM architecture to accelerate the computationally hard maximum satisfiability problem. The FerroCoDE exploits a novel formulation of the satisfiability problem as the direct maximization of entropy in the compute engine which is being developed through a vertically integrated materials-to-systems effort that focusses on: (i) Development of phase- and crystallographic-texture-engineered HfO2-based ultra-thin ferroelectric and antiferroelectric films with tunable properties; (ii) Design and fabrication of a novel non-volatile 1FeFET-1FTJ memory cell and array to enable in-memory programming and evaluation of the satisfiability clauses; and energy efficient AFE oscillator arrays (iii) Building synergistic convergence between the hardware and algorithm; (iv) System engineering, with emphasis on developing learning algorithms to optimize dynamical system initialization, development of annealing schedules and hardware scalability. (v) Development and demonstration of a FerroCoDE prototype on PCB.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.

并非所有的计算问题都是一样的。在许多越来越重要的应用程序的核心，从智能机器的设计，可以解释他们的决定，电子设计自动化的防篡改集成电路，是一类组合优化问题，仍然是传统的数字计算不可征服的堡垒。作为一个例子，解决原型布尔可满足性问题，许多这样的应用程序的组成部分，需要指数增加的能量和计算时间，使其实际部署在大规模不可行。拟议的研究旨在通过一个有凝聚力的跨栈工作来解决这一挑战，该工作从物理启发的计算模型的制定到设计一个支持硬件生态系统，该生态系统包括新型工程材料和设备，电路及其后续系统集成。基于铁电的内存计算动态引擎（FerroCoDE）的基本原理是通过在物理和计算之间创建独特的协同效应来利用自然界中物理现象的固有效率（即熵产生的最大化）。为了有效地执行这些计算模型，研究人员团队正在开发一种新的硬件平台，该平台将动态系统的独特功能与内存计算架构融合在一起，通过铁电材料及其设备功能的根本创新实现。FerroCoDE平台将实现计算效率的数量级改进，从而能够在当前计算机难以实现的大规模和（能源受限）环境中部署相关应用程序。此外，为了扩大这项工作的影响，该团队将开发一个可公开访问的在线平台OscWorks，用于在教育和研究中应用基于计算机的计算。此外，该团队将通过各种举措，如研讨会，在线研讨会和研究机会，与K-12和本科生接触。该ASCENT项目正在解决的系统挑战是设计，制造并演示了一个基于铁电氧化铪（HfO 2）的内存计算（CiM）动力引擎（FerroCoDE），其利用振荡器的丰富的非线性模拟动力学结合铁电CiM架构的面积和能量效率来加速计算困难的最大可满足性问题。FerroCoDE开发了一种新的可满足性问题的公式，作为计算引擎中熵的直接最大化，该计算引擎正在通过垂直集成的材料到系统的努力进行开发，该努力集中于：（i）开发具有可调特性的基于HfO 2的相和晶体织构工程超薄铁电和反铁电薄膜;（ii）设计和制造新颖的非易失性1FeFET-1FTJ存储器单元和阵列，以实现存储器内编程和可满足性条款的评估;以及能量高效的AFE振荡器阵列。㈣系统工程，重点是开发学习算法以优化动态系统初始化、开发退火时间表和硬件可扩展性。(v)在PCB上开发和演示FerroCoDE原型。该奖项反映了NSF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

A 2-Transistor-2-Capacitor Ferroelectric Edge Compute-in-Memory Scheme with Disturb-Free Inference and High Endurance

具有无干扰推理和高耐用性的 2 晶体管 2 电容器铁电边缘计算内存方案

• DOI: 10.1109/led.2023.3274362
• 发表时间: 2023
• 期刊: IEEE Electron Device Letters
• 影响因子: 4.9
• 作者: Ma, Xiaoyang;Deng, Shan;Wu, Juejian;Zhao, Zijian;Lehninger, David;Ali, Tarek;Seidel, Konrad;De, Sourav;He, Xiyu;Chen, Yiming
• 通讯作者: Chen, Yiming

Oscillator-based Dynamical Computing Platforms to Solve Combinatorial Optimization

基于振荡器的动态计算平台解决组合优化

• DOI: 10.1109/edtm53872.2022.9798043
• 发表时间: 2022
• 期刊: 2022 6th IEEE Electron Devices Technology & Manufacturing Conference (EDTM
• 作者: Mallick, Antik;Bashar, Mohammad Khairul;Shukla, Nikhil
• 通讯作者: Shukla, Nikhil

Computational Models Based on Synchronized Oscillators for Solving Combinatorial Optimization Problems

• DOI: 10.1103/physrevapplied.17.064064
• 发表时间: 2022-06-30
• 期刊: PHYSICAL REVIEW APPLIED
• 影响因子: 4.6
• 作者: Mallick, Antik;Bashar, Mohammad Khairul;Shukla, Nikhil
• 通讯作者: Shukla, Nikhil

FeFET-Based Logic-in-Memory Supporting SA-Free Write-Back and Fully Dynamic Access With Reduced Bitline Charging Activity and Recycled Bitline Charge

• DOI: 10.1109/tcsi.2023.3251961
• 发表时间: 2023-06
• 期刊: IEEE Transactions on Circuits and Systems I: Regular Papers
• 作者: Wenjun Tang;Ming-En Lee;Juejian Wu;Yixin Xu;Yao Yu;Yongpan Liu;Kai Ni;Yu Wang;Huazhong Yang;V. Narayanan;Xueqing Li

Dynamical System-Based Computational Models for Solving Combinatorial Optimization on Hypergraphs

• DOI: 10.1109/jxcdc.2023.3235113
• 发表时间: 2023-06-01
• 期刊: IEEE JOURNAL ON EXPLORATORY SOLID-STATE COMPUTATIONAL DEVICES AND CIRCUITS
• 影响因子: 2.4
• 作者: Bashar, Mohammad Khairul;Mallick, Antik;Shukla, Nikhil
• 通讯作者: Shukla, Nikhil