EAGER: Monolithic 3D Integration of Resistive Random Access Memory (ReRAM): A Technological Exploration

EAGER:电阻式随机存取存储器 (ReRAM) 的单片 3D 集成:技术探索

基本信息

  • 批准号:
    1449653
  • 负责人:
  • 金额:
    $ 25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-09-01 至 2017-08-31
  • 项目状态:
    已结题

项目摘要

With the rapid growth of big data, next generation non-volatile memory technologies are needed to enable a large capacity and fast bandwidth. The resistive random access memory (ReRAM) technology is one of the emerging candidates beyond the scaling limit of today's FLASH technology. The research and development of the ReRAM technology will benefit nearly every digital device available today from consumer electronics to enterprise electronics. It may also spawn new applications involving the computation on the exascale of data, e.g. data mining, machine learning, and bio-informatics etc. thus benefitting the semiconductor industry at large. Student summer internships are planned with the industrial partners, which will be invaluable for broadening the knowledge and skills of the students. The tools and techniques developed in this research will be used in the newly developed seminar course on memory design at ASU. The PI will make simulator tools available for use by other educators, researchers, and industry practitioners. Dissemination of research findings will also be carried out through conference tutorials, panel discussions, and workshops. A concerted effort will be made to involve underrepresented groups and undergraduate students in this research, and also to promote the K-12 students to major in science and engineering. This proposal aims to tackle the fundamental technological challenges for the monolithic 3D integration of ReRAM. Although the ReRAM technology shows very attractive characteristics at single cell level, at the array level its lower integration density limits its economical competiveness over the mainstream NAND FLASH technology. The project examines the use of monolithic 3D integration of ReRAM as a promising approach for enabling ultra-high density cross-point memory architecture. The proposed research activities focus on the device-level engineering with the design targets from the circuit-level array modeling, aiming at enabling the large-scale integration of 3D ReRAM technology. Array macro model that can assess integration density, cost per bit, read/write margin, access latency, and power/energy consumption will be developed and calibrated by SPICE simulation. Device prototypes for 3D ReRAM will be fabricated and optimized towards the desired targets given by the array macro model. All device engineering activities will leverage the existing knowledge of the electrode/oxide interface engineering and oxide/oxide interface engineering and further contribute to new understandings of relevant issues.
随着大数据的快速增长,需要下一代非易失性存储器技术来实现大容量和快速带宽。电阻式随机存取存储器(ReRAM)技术是超越当今闪存技术的缩放限制的新兴候选技术之一。ReRAM技术的研究和开发将使当今从消费电子到企业电子的几乎所有数字设备受益。它还可能产生涉及数据的exascale计算的新应用,例如数据挖掘,机器学习和生物信息学等,从而使整个半导体行业受益。学生暑期实习计划与工业合作伙伴,这将是扩大学生的知识和技能的宝贵。在这项研究中开发的工具和技术将用于在亚利桑那州立大学新开发的存储器设计研讨会课程。PI将使模拟器工具可供其他教育工作者,研究人员和行业从业者使用。还将通过会议指导、小组讨论和讲习班传播研究成果。将作出共同努力,让代表性不足的群体和本科生参与这项研究,并促进K-12学生主修科学和工程。该提案旨在解决ReRAM单片3D集成的基本技术挑战。虽然ReRAM技术在单单元级显示出非常有吸引力的特性,但在阵列级,其较低的集成密度限制了其相对于主流NAND FLASH技术的经济竞争力。该项目研究了ReRAM单片3D集成的使用,作为实现超高密度交叉点存储器架构的一种有前途的方法。拟议的研究活动侧重于器件级工程,设计目标来自电路级阵列建模,旨在实现3D ReRAM技术的大规模集成。阵列宏模型,可以评估集成密度,每比特的成本,读/写裕度,访问延迟,和功耗/能耗将开发和SPICE模拟校准。3D ReRAM的设备原型将被制造和优化,以实现阵列宏模型给出的目标。所有器械工程活动将利用电极/氧化物界面工程和氧化物/氧化物界面工程的现有知识,并进一步促进对相关问题的新理解。

项目成果

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Shimeng Yu其他文献

Optimization of RRAM-Based Physical Unclonable Function With a Novel Differential Read-Out Method
采用新颖的差分读出方法优化基于 RRAM 的物理不可克隆功能
  • DOI:
    10.1109/led.2016.2647230
  • 发表时间:
    2017-02
  • 期刊:
  • 影响因子:
    4.9
  • 作者:
    Yachuan Pang;Huaqiang Wu;Bin Gao;Ning Deng;Dong Wu;Rui Liu;Shimeng Yu;An Chen;He Qian
  • 通讯作者:
    He Qian
First Experimental Demonstration of Robust HZO/β-Ga₂O₃ Ferroelectric Field-Effect Transistors as Synaptic Devices for Artificial Intelligence Applications in a High-Temperature Environment
鲁棒 HZO/β-Ga2O3 铁电场效应晶体管作为高温环境下人工智能应用突触器件的首次实验演示
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    3.1
  • 作者:
    J. Noh;H. Bae;Junkang Li;Yandong Luo;Y. Qu;T. J. Park;M. Si;Xuegang Chen;A. Charnas;W. Chung;Xiaochen Peng;S. Ramanathan;Shimeng Yu;P. Ye
  • 通讯作者:
    P. Ye
Resistive Random Access Memory (RRAM)
  • DOI:
    10.1007/978-3-031-02030-8
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Shimeng Yu
  • 通讯作者:
    Shimeng Yu
Ferroelectric FET based Non-Volatile Analog Synaptic Weight Cell
基于铁电 FET 的非易失性模拟突触重量单元
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. Jerry;S. Dutta;K. Ni;Jianchi Zhang;Pankaj Sharma;S. Datta;A. Kazemi;X. Hu;M. Niemier;Pai;Shimeng Yu
  • 通讯作者:
    Shimeng Yu
A phenomenological model of oxygen ion transport for metal oxide resistive switching memory
金属氧化物阻变存储器氧离子传输的唯象模型

Shimeng Yu的其他文献

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{{ truncateString('Shimeng Yu', 18)}}的其他基金

Collaborative Research: FET: Medium:Compact and Energy-Efficient Compute-in-Memory Accelerator for Deep Learning Leveraging Ferroelectric Vertical NAND Memory
合作研究:FET:中型:紧凑且节能的内存计算加速器,用于利用铁电垂直 NAND 内存进行深度学习
  • 批准号:
    2312885
  • 财政年份:
    2023
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
Low Temperature Embedded Memory Devices for Near-Memory and In-Memory Computing
用于近内存和内存计算的低温嵌入式存储器件
  • 批准号:
    2218604
  • 财政年份:
    2022
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
CAREER: Scaling-up Resistive Synaptic Arrays for Neuro-inspired Computing
职业:扩大电阻突触阵列以实现神经启发计算
  • 批准号:
    1903951
  • 财政年份:
    2018
  • 资助金额:
    $ 25万
  • 项目类别:
    Continuing Grant
Exploiting Metal-Insulator-Transition in Strongly Correlated Oxides as Neuron Device for Neuro-Inspired Computing
利用强相关氧化物中的金属-绝缘体转变作为神经元设备进行神经启发计算
  • 批准号:
    1903577
  • 财政年份:
    2018
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
STARSS: Small: Design of Light-weight RRAM based Hardware Security Primitives for IoT devices
STARSS:小型:为物联网设备设计基于 RRAM 的轻量级硬件安全原语
  • 批准号:
    1903631
  • 财政年份:
    2018
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
Exploiting Metal-Insulator-Transition in Strongly Correlated Oxides as Neuron Device for Neuro-Inspired Computing
利用强相关氧化物中的金属-绝缘体转变作为神经元设备进行神经启发计算
  • 批准号:
    1701565
  • 财政年份:
    2017
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
CAREER: Scaling-up Resistive Synaptic Arrays for Neuro-inspired Computing
职业:扩大电阻突触阵列以实现神经启发计算
  • 批准号:
    1552687
  • 财政年份:
    2016
  • 资助金额:
    $ 25万
  • 项目类别:
    Continuing Grant
STARSS: Small: Design of Light-weight RRAM based Hardware Security Primitives for IoT devices
STARSS:小型:为物联网设备设计基于 RRAM 的轻量级硬件安全原语
  • 批准号:
    1615774
  • 财政年份:
    2016
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant

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