[1] Y. LeCun, Y. Bengio, G. Hinton. Deep learning. Nature, 521, 436(2015).

[2] D. Silver, T. Hubert, J. Schrittwieser, I. Antonoglou, M. Lai, A. Guez, M. Lanctot, L. Sifre, D. Kumaran, T. Graepel, T. Lillicrap, K. Simonyan, D. Hassabis. A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science, 362, 1140(2018).

[3] J. Shi, F. Zhang, D. Ben, S. Pan. Photonic-assisted single system for microwave frequency and phase noise measurement. Chin. Opt. Lett., 18, 092501(2020).

[4] R. Wang, S. Xu, J. Chen, W. Zou. Ultra-wideband signal acquisition by use of channel-interleaved photonic analog-to-digital converter under the assistance of dilated fully convolutional network. Chin. Opt. Lett., 18, 123901(2020).

[5] S. Xu, X. Zou, B. Ma, J. Chen, L. Yu, W. Zou. Deep-learning-powered photonic analog-to-digital conversion. Light: Sci. Appl., 8, 66(2019).

[6] L. Yu, W. Zou, X. Li, J. Chen. An X- and Ku-band multifunctional radar receiver based on photonic parametric sampling. Chin. Opt. Lett., 18, 042501(2020).

[7] D. Amodei, D. Hernandez. AI and compute(2018).

[8] M. Horowitz. Computing’s energy problem (and what we can do about it). IEEE International Solid-state Circuits Conference, 10(2014).

[9] M. A. Nahmias, T. F. Lima, A. N. Tait, H. Peng, B. J. Shastri, P. R. Prucnal. Photonic multiply-accumulate operations for neural networks. IEEE J. Sel. Top. Quantum Electron., 26, 7701518(2020).

[10] Y. Shen, N. C. Harris, S. Skirlo, M. Prabhu, T. Baehr-Jones, M. Hochberg, X. Sun, S. Zhao, H. Larochelle, D. Englund, M. Soljačić. Deep learning with coherent nanophotonic circuits. Nat. Photon., 11, 441(2017).

[11] S. Xu, J. Wang, R. Wang, J. Chen, W. Zou. High-accuracy optical convolution unit architecture for convolutional neural networks by cascaded acousto-optical modulator arrays. Opt. Express, 27, 19778(2019).

[12] V. Bangari, B. A. Marquez, H. Miller, A. N. Tait, M. A. Nahmias, T. Lima, H. Peng, P. R. Prucnal, B. J. Shastri. Digital electronics and analog photonics for convolutional neural networks (DEAP-CNNs). IEEE J. Sel. Top. Quantum Electron., 26, 7701213(2020).

[13] Y. Zuo, B. Li, Y. Zhao, Y. Jiang, Y. Chen, P. Chen, G. Jo, J. Liu, S. Du. All-optical neural network with nonlinear activation functions. Optica, 6, 1132(2019).

[14] X. Lin, Y. Rivenson, N. T. Yardimci, M. Veli, Y. Luo, M. Jarrahi, A. Ozcan. All-optical machine learning using diffractive deep neural networks. Science, 361, 1004(2018).

[15] R. Hamerly, L. Bernstein, A. Sludds, M. Soljačić, D. Englund. Large-scale optical neural networks based on photoelectric multiplication. Phys. Rev. X, 9, 021032(2019).

[16] J. Chiles, S. Buckley, N. Nader, S. Nam, R. P. Mirin, J. M. Shainline. Multi-planar amorphous silicon photonics with compact interplanar couplers, cross talk mitigation, and low crossing loss. APL Photon., 2, 116101(2017).

[17] S. Chetlur, C. Woolley, P. Vandermersch, J. Cohen, J. Tran, B. Catanzaro, E. Shelhamer. cuDNN: efficient primitives for deep learning(2014).

[18] J. Chiles, S. M. Buckley, S. Nam, R. P. Mirin, J. M. Shainline. Design, fabrication, and metrology of 10 × 100 multi-planar integrated photonic routing manifolds for neural networks. APL Photon., 3, 106101(2018).

[19] J. Lee, S. Cho, W. Choi. An equivalent circuit model for a Ge waveguide photodetector on Si. IEEE Photon. Technol. Lett., 28, 2435(2016).

[20] P. Yao, H. Wu, B. Gao, J. Tang, Q. Zhang, W. Zhang, J. J. Yang, H. Qian. Fully hardware-implemented memristor convolutional neural network. Nature, 577, 641(2020).