Hybrid control system for memristive arrays: development of a high-level scheme and implementation prospects

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Аннотация

The article proposes a memristive array control architecture that allows working with passive crossbar structures, which significantly increases the layout density and reduces the technological complexity of production. The main functional blocks of the system are described.

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Авторлар туралы

A. Tokarev

МИРЭА – Технологический университет (РТУ МИРЭА)

Хат алмасуға жауапты Автор.
Email: santokar5@gmail.com
Ресей

Әдебиет тізімі

  1. Yadav D.N., Thangkhiew P.L., Chakraborty S., et al. Efficient grouping approach for fault tolerant weight mapping in memristive crossbar array // Memories – Materials, Devices, Circuits and Systems 4 (2023) 100045 https://doi.org/10.1016/ j.memori.2023.100045.
  2. Zhang B., Uysal N., Fan D., Ewetz R., et al. Handling Stuck-at-Fault Defects Using Matrix Transformation for Robust Inference of DNNs // IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. Vol. 39. No. 10. PP. 2448–2460. Oct. 2020, doi: 10.1109/TCAD.2019.2944582.
  3. Xu Y., Jin S., Wang Y., et al. Aggressive Fault Tolerance for Memristor Crossbar-Based Neural Network Accelerators by Operational Unit Level Weight Mapping // IEEE Access. Vol. 9. PP. 102828–102834, 2021, doi: 10.1109/ACCESS.2021.3097724.
  4. Xia L., Huangfu W., Tang T., et al. Stuck-at Fault Tolerance in RRAM Computing Systems // IEEE Journal on Emerging and Selected Topics in Circuits and Systems. Vol. 8. No. 1. PP. 102–115. March 2018, doi: 10.1109/JETCAS.2017.2776980.
  5. Roy K., et al. Towards spike-based machine intelligence with neuromorphic computing // Nature 13 575. 607-617 (2019). http://doi.org/10.1038/s41586-019-1677-2.
  6. Xiaoyang Liu & Zhigang Zeng. Memristor crossbar architectures for implementing deep neural networks // Springer Nature Link. 2022. Vol. 8. PP. 787–802.
  7. Yao P., Wu H., Gao B., et al. Fully hardware-implemented memristor convolutional neural network // Nature. 2020. Vol. 577. PP. 641–646, 641–646 (2020). http://doi.org/10.1038/s41586-020-1942-4.
  8. Zhang J., Cheng L., Zeng H., Song Y. Thermal Management in Memristor-Based Crossbar Arrays for High-Density Nonvolatile Memories // IEEE Transactions on Electron Devices. Vol. 65. Is. 1. Jan. 2018.
  9. Deen M.J. RF noise models of MOSFETs- A review // NSTI-Nanotech. 2004. Vol. 2.

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2. Fig. 1. High-level functional diagram of interaction with the crossbar

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© Tokarev A., 2025