Bending Resistant Multibit Memristor for Flexible Precision Inference Engine Application

Parthasarathi Pal, Ke Jing Lee, Sunanda Thunder, Sourav De, Po Tsang Huang, Thomas Kampfe, Yeong Her Wang

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)

摘要

This work reports 2-bits/cell hafnium oxide-based stacked resistive random access memory devices fabricated on flexible polyimide substrates for neuromorphic applications considering the high thermal budget. The ratio of low-resistance state current (ION) to high-resistance state current (IOFF) or ION/IOFF for the fabricated devices was above 1.4×103 with a low device-to-device variation at 100 μA current compliance. The mechanical stability over 104 bending cycles at a 5 mm bending radius and endurance over 106 WRITE cycles makes these devices suitable for online neural network training. The data retention capability over 104s at 125°C also infuses these devices' long-term inference capability. Furthermore, the performance of the devices has been verified for neuromorphic applications by system-level simulations with experimentally calibrated data. The system-level simulation reveals only a 2% loss in inference accuracy over ten years from the baseline.

原文English
頁(從 - 到)4737-4743
頁數7
期刊IEEE Transactions on Electron Devices
69
發行號8
DOIs
出版狀態Published - 2022 8月 1

All Science Journal Classification (ASJC) codes

  • 電子、光磁材料
  • 電氣與電子工程

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