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RFAM: RESET-Failure-Aware-Model for HfO2-based Memristor to Enhance the Reliability of Neuromorphic Design

Published: 05 June 2023 Publication History

Abstract

Memristors are a suitable candidate to design synapse circuits and neuromorphic systems. Due to device and voltage variability, operating a memristive device with reliability is a big challenge. To enhance the reliability of memristive synapse, RESET failure needs to be considered. In this work, we are focused on RESET failure modeling with RESET voltage variation. Here, the RESET failure is defined as hard failure of the memristive synapse due to a high RESET voltage being applied. The proposed Verilog-A model is derived based on experimental data collected from 1T1R devices, which are fabricated on 65 nm CMOS process. To enhance the reliability of system-level simulation, this device model will provide better guidelines to the designer. In addition, power consumption for a successful RESET operation is 7.065 μW at 1.5 V, which can RESET the memristor resistance from 5 kΩ to 200 kΩ.

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  1. RFAM: RESET-Failure-Aware-Model for HfO2-based Memristor to Enhance the Reliability of Neuromorphic Design

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    cover image ACM Conferences
    GLSVLSI '23: Proceedings of the Great Lakes Symposium on VLSI 2023
    June 2023
    731 pages
    ISBN:9798400701252
    DOI:10.1145/3583781
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    Published: 05 June 2023

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    Author Tags

    1. high resistive state
    2. low resistive state
    3. memristor
    4. neuromorphic
    5. reliability
    6. reram
    7. reset failure
    8. synapse

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    June 5 - 7, 2023
    TN, Knoxville, USA

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    Overall Acceptance Rate 312 of 1,156 submissions, 27%

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    Cited By

    View all
    • (2024)Hardware-Application Co-Design to Evaluate the Performance of an STDP-based Reservoir Computer2024 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)10.1109/ISVLSI61997.2024.00127(666-670)Online publication date: 1-Jul-2024
    • (2024)A Memristive Reconfigurable Neuromorphic Array for Neuro-Inspired Dynamic Architectures2024 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)10.1109/ISVLSI61997.2024.00081(415-420)Online publication date: 1-Jul-2024
    • (2024)In-Sensor Motion Recognition with Memristive System and Light Sensing Surfaces2024 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)10.1109/ISVLSI61997.2024.00044(192-197)Online publication date: 1-Jul-2024
    • (2024) HfO 2 -Based Synaptic Spiking Neural Network Evaluation to Optimize Design and Testing Cost 2024 IEEE International Symposium on Circuits and Systems (ISCAS)10.1109/ISCAS58744.2024.10558518(1-5)Online publication date: 19-May-2024
    • (2024)Enhanced read resolution in reconfigurable memristive synapses for Spiking Neural NetworksScientific Reports10.1038/s41598-024-58947-214:1Online publication date: 17-Apr-2024
    • (2023)An Efficient and Accurate Memristive Memory for Array-Based Spiking Neural NetworksIEEE Transactions on Circuits and Systems I: Regular Papers10.1109/TCSI.2023.330102070:12(4804-4815)Online publication date: Dec-2023
    • (2023)Spike-Driven Synaptic Plasticity for a Memristive Neuromorphic Core2023 IEEE 66th International Midwest Symposium on Circuits and Systems (MWSCAS)10.1109/MWSCAS57524.2023.10406136(644-648)Online publication date: 6-Aug-2023
    • (2023)Spike-Timing-Dependent Plasticity for a Hafnium-Oxide Memristive Synapse2023 IEEE 66th International Midwest Symposium on Circuits and Systems (MWSCAS)10.1109/MWSCAS57524.2023.10406099(463-467)Online publication date: 6-Aug-2023
    • (2023)Energy Efficient and High-Performance Synaptic Operating Point Evaluation for SNN Applications2023 IEEE 66th International Midwest Symposium on Circuits and Systems (MWSCAS)10.1109/MWSCAS57524.2023.10406062(918-922)Online publication date: 6-Aug-2023
    • (2023)Optimizations for a Current-Controlled Memristor- Based Neuromorphic Synapse DesignIEEE Journal on Emerging and Selected Topics in Circuits and Systems10.1109/JETCAS.2023.331216313:4(889-900)Online publication date: Dec-2023

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