ECRAM as Scalable Synaptic Cell for High-Speed, Low-Power Neuromorphic Computing

@article{Tang2018ECRAMAS,
  title={ECRAM as Scalable Synaptic Cell for High-Speed, Low-Power Neuromorphic Computing},
  author={Jianshi Tang and Douglas M. Bishop and Seyoung Kim and Matthew Copel and Tayfun Gokmen and Teodor K. Todorov and SangHoon Shin and Ko-Tao Lee and Paul M. Solomon and Kevin K. H. Chan and Wilfried E. Haensch and John Rozen},
  journal={2018 IEEE International Electron Devices Meeting (IEDM)},
  year={2018},
  pages={13.1.1-13.1.4}
}
We demonstrate a nonvolatile Electro-Chemical Random-Access Memory (ECRAM) based on lithium (Li) ion intercalation in tungsten oxide (WO3) for high-speed, low-power neuromorphic computing. Symmetric and linear update on the channel conductance is achieved using gate current pulses, where up to 1000 discrete states with large dynamic range and good retention are demonstrated. MNIST simulation based on the experimental data shows an accuracy of 96%. For the first time, high-speed programming with… Expand

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