Resources

Wang, Z., Wu, H., Burr, G.W. et al. Resistive switching materials for information processing. Nat Rev Mater 5, 173–195 (2020)
Wang, Shaocong et al. “Echo state graph neural networks with analogue random resistor arrays.” ArXiv abs/2112.15270 (2021)
C. Li, et al, “Efficient and self-adaptive in-situ learning in multilayer memristor neural networks”, Nature Communications, 9, 1 (2018)
C. Li, et al, “Analog error correcting codes for defect tolerant matrix multiplication in crossbars”, IEDM 2020
R. Mao, et al, “Experimentally-Validated Crossbar Model for Defect-Aware Training of Neural Networks”, IEEE TCAS2, (early access) 2022
Qiming Shao, Zhongrui Wang & J. Joshua Yang, Efficient AI with MRAM, Nature Electronics 5, 67–68 (2022)
Seungchul Jung, et al., A crossbar array of magnetoresistive memory devices for in-memory computing, Nature 601, 211–216 (2022)
Peng Yao, et al., Fully hardware-implemented memristor convolutional neural network, Nature 577, 641–646 (2020)
Jonas Doevenspeck et al., SOT-MRAM based analog in-memory computing for DNN inference, 2020 IEEE Symposium on VLSI Technology
https://www.youtube.com/channel/UCQKeknQioXvHk1wZZB-dliw
B. Murmann, “Mixed-Signal Computing for Deep Neural Network Inference,” IEEE Trans. Very Large Scale Integration (VLSI) Systems, vol. 29, no. 1, pp. 3-13, Jan. 2021.
Jiang, Weiwen, Xinyi Zhang, Edwin H-M. Sha, Lei Yang, Qingfeng Zhuge, Yiyu Shi, and Jingtong Hu. "Accuracy vs. efficiency: Achieving both through fpga-implementation aware neural architecture search." In Proceedings of the 56th Annual Design Automation Conference 2019, pp. 1-6. 2019.
Jiang, Weiwen, Lei Yang, Edwin Hsing-Mean Sha, Qingfeng Zhuge, Shouzhen Gu, Sakyasingha Dasgupta, Yiyu Shi, and Jingtong Hu. "Hardware/software co-exploration of neural architectures." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 39, no. 12 (2020): 4805-4815.
Sheng, Yi, Junhuan Yang, Yawen Wu, Kevin Mao, Yiyu Shi, Jingtong Hu, Weiwen Jiang, and Lei Yang. "The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices." arXiv preprint arXiv:2202.11317 (2022). Accepted by DAC’22
Yang, Junhuan, Yi Sheng, Sizhe Zhang, Ruixuan Wang, Kenneth Foreman, Mikell Paige, Xun Jiao, Weiwen Jiang, and Lei Yang. "Automated Architecture Search for Brain-inspired Hyperdimensional Computing." arXiv preprint arXiv:2202.05827 (2022). Accepted by AutoML-Conf 2022