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Microcomb-based integrated photonic processing unit

Author

Listed:
  • Bowen Bai

    (Peking University)

  • Qipeng Yang

    (Peking University)

  • Haowen Shu

    (Peking University)

  • Lin Chang

    (Peking University
    University of California
    Peking University)

  • Fenghe Yang

    (Zhangjiang Laboratory)

  • Bitao Shen

    (Peking University)

  • Zihan Tao

    (Peking University)

  • Jing Wang

    (Shanghai Jiao Tong University)

  • Shaofu Xu

    (Shanghai Jiao Tong University)

  • Weiqiang Xie

    (University of California)

  • Weiwen Zou

    (Shanghai Jiao Tong University)

  • Weiwei Hu

    (Peking University)

  • John E. Bowers

    (University of California)

  • Xingjun Wang

    (Peking University
    Peking University
    Peking University Yangtze Delta Institute of Optoelectronics)

Abstract

The emergence of parallel convolution-operation technology has substantially powered the complexity and functionality of optical neural networks (ONN) by harnessing the dimension of optical wavelength. However, this advanced architecture faces remarkable challenges in high-level integration and on-chip operation. In this work, convolution based on time-wavelength plane stretching approach is implemented on a microcomb-driven chip-based photonic processing unit (PPU). To support the operation of this processing unit, we develop a dedicated control and operation protocol, leading to a record high weight precision of 9 bits. Moreover, the compact architecture and high data loading speed enable a preeminent photonic-core compute density of over 1 trillion of operations per second per square millimeter (TOPS mm−2). Two proof-of-concept experiments are demonstrated, including image edge detection and handwritten digit recognition, showing comparable processing capability compared to that of a digital computer. Due to the advanced performance and the great scalability, this parallel photonic processing unit can potentially revolutionize sophisticated artificial intelligence tasks including autonomous driving, video action recognition and image reconstruction.

Suggested Citation

  • Bowen Bai & Qipeng Yang & Haowen Shu & Lin Chang & Fenghe Yang & Bitao Shen & Zihan Tao & Jing Wang & Shaofu Xu & Weiqiang Xie & Weiwen Zou & Weiwei Hu & John E. Bowers & Xingjun Wang, 2023. "Microcomb-based integrated photonic processing unit," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-022-35506-9
    DOI: 10.1038/s41467-022-35506-9
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    References listed on IDEAS

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    1. Lin Chang & Weiqiang Xie & Haowen Shu & Qi-Fan Yang & Boqiang Shen & Andreas Boes & Jon D. Peters & Warren Jin & Chao Xiang & Songtao Liu & Gregory Moille & Su-Peng Yu & Xingjun Wang & Kartik Srinivas, 2020. "Ultra-efficient frequency comb generation in AlGaAs-on-insulator microresonators," Nature Communications, Nature, vol. 11(1), pages 1-8, December.
    2. Zi Wang & Tiantian Li & Anishkumar Soman & Dun Mao & Thomas Kananen & Tingyi Gu, 2019. "On-chip wavefront shaping with dielectric metasurface," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    3. Amir H. Atabaki & Sajjad Moazeni & Fabio Pavanello & Hayk Gevorgyan & Jelena Notaros & Luca Alloatti & Mark T. Wade & Chen Sun & Seth A. Kruger & Huaiyu Meng & Kenaish Al Qubaisi & Imbert Wang & Bohan, 2018. "Publisher Correction: Integrating photonics with silicon nanoelectronics for the next generation of systems on a chip," Nature, Nature, vol. 560(7716), pages 4-4, August.
    4. H. Zhang & M. Gu & X. D. Jiang & J. Thompson & H. Cai & S. Paesani & R. Santagati & A. Laing & Y. Zhang & M. H. Yung & Y. Z. Shi & F. K. Muhammad & G. Q. Lo & X. S. Luo & B. Dong & D. L. Kwong & L. C., 2021. "An optical neural chip for implementing complex-valued neural network," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    5. J. Feldmann & N. Youngblood & M. Karpov & H. Gehring & X. Li & M. Stappers & M. Gallo & X. Fu & A. Lukashchuk & A. S. Raja & J. Liu & C. D. Wright & A. Sebastian & T. J. Kippenberg & W. H. P. Pernice , 2021. "Parallel convolutional processing using an integrated photonic tensor core," Nature, Nature, vol. 589(7840), pages 52-58, January.
    6. Amir H. Atabaki & Sajjad Moazeni & Fabio Pavanello & Hayk Gevorgyan & Jelena Notaros & Luca Alloatti & Mark T. Wade & Chen Sun & Seth A. Kruger & Huaiyu Meng & Kenaish Al Qubaisi & Imbert Wang & Bohan, 2018. "Integrating photonics with silicon nanoelectronics for the next generation of systems on a chip," Nature, Nature, vol. 556(7701), pages 349-354, April.
    7. Haowen Shu & Lin Chang & Yuansheng Tao & Bitao Shen & Weiqiang Xie & Ming Jin & Andrew Netherton & Zihan Tao & Xuguang Zhang & Ruixuan Chen & Bowen Bai & Jun Qin & Shaohua Yu & Xingjun Wang & John E. , 2022. "Microcomb-driven silicon photonic systems," Nature, Nature, vol. 605(7910), pages 457-463, May.
    8. J. Feldmann & N. Youngblood & M. Karpov & H. Gehring & X. Li & M. Stappers & M. Gallo & X. Fu & A. Lukashchuk & A. S. Raja & J. Liu & C. D. Wright & A. Sebastian & T. J. Kippenberg & W. H. P. Pernice , 2021. "Publisher Correction: Parallel convolutional processing using an integrated photonic tensor core," Nature, Nature, vol. 591(7849), pages 13-13, March.
    9. Xingyuan Xu & Mengxi Tan & Bill Corcoran & Jiayang Wu & Andreas Boes & Thach G. Nguyen & Sai T. Chu & Brent E. Little & Damien G. Hicks & Roberto Morandotti & Arnan Mitchell & David J. Moss, 2021. "11 TOPS photonic convolutional accelerator for optical neural networks," Nature, Nature, vol. 589(7840), pages 44-51, January.
    10. Boqiang Shen & Lin Chang & Junqiu Liu & Heming Wang & Qi-Fan Yang & Chao Xiang & Rui Ning Wang & Jijun He & Tianyi Liu & Weiqiang Xie & Joel Guo & David Kinghorn & Lue Wu & Qing-Xin Ji & Tobias J. Kip, 2020. "Integrated turnkey soliton microcombs," Nature, Nature, vol. 582(7812), pages 365-369, June.
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    1. Qi Han & Jun Wang & Shuangshuang Tian & Shen Hu & Xuefeng Wu & Rongxu Bai & Haibin Zhao & David W. Zhang & Qingqing Sun & Li Ji, 2024. "Inorganic perovskite-based active multifunctional integrated photonic devices," Nature Communications, Nature, vol. 15(1), pages 1-9, December.

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