Researching | Integrated photonic convolution acceleration core for wearable devices

Opto-Electronic Science, Volume. 2, Issue 12, 230017(2023)

Integrated photonic convolution acceleration core for wearable devices

Baiheng Zhao¹, Junwei Cheng¹, Bo Wu¹, Dingshan Gao¹, Hailong Zhou¹, and Jianji Dong^1,2、*

Author Affiliations

¹Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China

²Optics Valley Laboratory, Wuhan 430074, China

show less

Full Text Get PDF

Figures&Tables (6)

References (34)

Paper Information

References(34)

[1] SB Zhang, YX Li, S Zhang, F Shahabi, S Xia et al. Deep learning in human activity recognition with wearable sensors: a review on advances. Sensors, 22, 1476(2022).

[2] WJ Chang, LB Chen, YZ Chiou. Design and implementation of a drowsiness-fatigue-detection system based on wearable smart glasses to increase road safety. IEEE Trans Consum Electron, 64, 461-469(2018).

[3] E Ramanujam, T Perumal, S Padmavathi. Human activity recognition with smartphone and wearable sensors using deep learning techniques: a review. IEEE Sensors J, 21, 13029-13040(2021).

[4] KX Chen, DL Zhang, LN Yao, B Guo, ZW Yu et al. Deep learning for sensor-based human activity recognition: overview, challenges, and opportunities. ACM Comput Surv, 54, 77(2022).

[5] JD Wang, YQ Chen, SJ Hao, XH Peng, LS Hu. Deep learning for sensor-based activity recognition: a survey. Pattern Recognit Lett, 119, 3-11(2019).

[6] HF Nweke, YW Teh, MA Al-garadi, UR Alo. Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: state of the art and research challenges. Expert Syst Appl, 105, 233-261(2018).

[7] JR Terven, B Raducanu, ME Meza-de-Luna, J Salas. Head-gestures mirroring detection in dyadic social interactions with computer vision-based wearable devices. Neurocomputing, 175, 866-876(2016).

[8] M Perusquía-Hernández, M Hirokawa, K Suzuki. A wearable device for fast and subtle spontaneous smile recognition. IEEE Trans Affective Comput, 8, 522-533(2017).

[9] A Gruebler, K Suzuki. Design of a wearable device for reading positive expressions from facial EMG signals. IEEE Trans Affective Comput, 5, 227-237(2014).

[10] TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan et al. Language models are few-shot learners, 159(2020).

[11] AI Hussein. Wearable computing: challenges of implementation and its future, 14-19(2015).

[12] HL Zhou, JJ Dong, JW Cheng, WC Dong, CR Huang et al. Photonic matrix multiplication lights up photonic accelerator and beyond. Light Sci Appl, 11, 30(2022).

[13] BJ Shastri, AN Tait, T Ferreira De Lima, WHP Pernice, H Bhaskaran et al. Photonics for artificial intelligence and neuromorphic computing. Nat Photonics, 15, 102-114(2021).

[14] MA Nahmias, TF De Lima, AN Tait, HT Peng, BJ Shastri et al. Photonic multiply-accumulate operations for neural networks. IEEE J Sel Top Quantum Electron, 26, 1-18(2020).

[15] X Lin, Y Rivenson, NT Yardimci, M Veli, Y Luo et al. All-optical machine learning using diffractive deep neural networks. Science, 361, 1004-1008(2018).

[16] CL Panuski, I Christen, M Minkov, CJ Brabec, S Trajtenberg-Mills et al. A full degree-of-freedom spatiotemporal light modulator. Nat Photonics, 16, 834-842(2022).

[17] JX Li, YC Hung, O Kulce, D Mengu, A Ozcan. Polarization multiplexed diffractive computing: all-optical implementation of a group of linear transformations through a polarization-encoded diffractive network. Light Sci Appl, 11, 153(2022).

[18] XY Xu, MX Tan, B Corcoran, JY Wu, A Boes et al. 11 TOPS photonic convolutional accelerator for optical neural networks. Nature, 589, 44-51(2021).

[19] BW Bai, QP Yang, HW Shu, L Chang, FH Yang et al. Microcomb-based integrated photonic processing unit. Nat Commun, 14, 66(2023).

[20] YC Shen, NC Harris, S Skirlo, M Prabhu, T Baehr-Jones et al. Deep learning with coherent nanophotonic circuits. Nat Photonics, 11, 441-446(2017).

[21] TW Hughes, M Minkov, Y Shi, SH Fan. Training of photonic neural networks through in situ backpropagation and gradient measurement. Optica, 5, 864-871(2018).

[22] HL Zhou, YH Zhao, X Wang, DS Gao, JJ Dong et al. Self-configuring and reconfigurable silicon photonic signal processor. ACS Photonics, 7, 792-799(2020).

[23] H Zhang, M Gu, XD Jiang, J Thompson, H Cai et al. An optical neural chip for implementing complex-valued neural network. Nat Commun, 12, 457(2021).

[24] AN Tait, TF De Lima, E Zhou, AX Wu, MA Nahmias et al. Neuromorphic photonic networks using silicon photonic weight banks. Sci Rep, 7, 7430(2017).

[25] SF Xu, J Wang, SC Yi, WW Zou. High-order tensor flow processing using integrated photonic circuits. Nat Commun, 13, 7970(2022).

[26] CR Huang, S Bilodeau, T Ferreira De Lima, AN Tait, PY Ma et al. Demonstration of scalable microring weight bank control for large-scale photonic integrated circuits. APL Photonics, 5, 040803(2020).

[27] JW Cheng, ZM He, YH Guo, B Wu, HL Zhou et al. Self-calibrating microring synapse with dual-wavelength synchronization. Photonics Res, 11, 347(2023).

[28] WP Zhang, CR Huang, HT Peng, S Bilodeau, A Jha et al. Silicon microring synapses enable photonic deep learning beyond 9-bit precision. Optica, 9, 579-584(2022).

[29] A Bandini, J Zariffa. Analysis of the hands in egocentric vision: a survey. IEEE Trans Pattern Anal Mach Intell, 45, 6846-6866(2023).

[30] YF Zhang, CQ Cao, J Cheng, HQ Lu. EgoGesture: a new dataset and benchmark for egocentric hand gesture recognition. IEEE Trans Multimedia, 20, 1038-1050(2018).

[31] L Razzari, D Duchesne, M Ferrera, R Morandotti, S Chu et al. CMOS-compatible integrated optical hyper-parametric oscillator. Nat Photonics, 4, 41-45(2010).

[32] DJ Moss, R Morandotti, AL Gaeta, M Lipson. New CMOS-compatible platforms based on silicon nitride and Hydex for nonlinear optics. Nat Photonics, 7, 597-607(2013).

[33] TJ Kippenberg, AL Gaeta, M Lipson, ML Gorodetsky. Dissipative kerr solitons in optical microresonators. Science, 361, eaan8083(2018).

[34] A Graves, G Wayne, M Reynolds, T Harley, I Danihelka et al. Hybrid computing using a neural network with dynamic external memory. Nature, 538, 471-476(2016).

Tools

Get Citation

Copy Citation Text

Baiheng Zhao, Junwei Cheng, Bo Wu, Dingshan Gao, Hailong Zhou, Jianji Dong. Integrated photonic convolution acceleration core for wearable devices[J]. Opto-Electronic Science, 2023, 2(12): 230017

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Category: Research Articles

Received: Jun. 30, 2023

Accepted: Sep. 17, 2023

Published Online: Mar. 19, 2024

The Author Email: Dong Jianji (JJDong)

DOI:10.29026/oes.2023.230017

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology