1.National Information Optoelectronics Innovation Center, China Information and Communication Technologies Group Corporation, Youkeyuan Road 88, Wuhan 430074 Hubei, China
2.State Key Laboratory of Optical Communication Technologies and Networks, China Information and Communication Technologies Group Corporation, Gaoxinsi Road 6, Wuhan 430074 Hubei, China
3.Peng Cheng Laboratory, Shahexi Road 6001, Shenzhen 518108 Guangdong, China
Xi Xiao (xiaoxi@noeic.com)
收稿:2025-05-22,
修回:2026-01-09,
录用:2026-01-23,
网络首发:2026-03-11,
纸质出版:2026-05-31
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Ying Zhu, Yifan Liu, Xinyu Yang, 等. LightIN: a versatile silicon-integrated photonic field programmable gate array with an intelligent configuration framework for next-generation AI clusters[J]. Light: Science & Applications, 2026,15(5):1736-1750.
Zhu, Y. et al. LightIN: a versatile silicon-integrated photonic field programmable gate array with an intelligent configuration framework for next-generation AI clusters. Light: Science & Applications, 15, 1736-1750 (2026).
Ying Zhu, Yifan Liu, Xinyu Yang, 等. LightIN: a versatile silicon-integrated photonic field programmable gate array with an intelligent configuration framework for next-generation AI clusters[J]. Light: Science & Applications, 2026,15(5):1736-1750. DOI: 10.1038/s41377-026-02209-5.
Zhu, Y. et al. LightIN: a versatile silicon-integrated photonic field programmable gate array with an intelligent configuration framework for next-generation AI clusters. Light: Science & Applications, 15, 1736-1750 (2026). DOI: 10.1038/s41377-026-02209-5.
Artificial Intelligence models pose serious challenges to intensive computing and high-bandwidth communication for conventional electronic circuit-based computing clusters. Silicon photonic technologies
due to their high speed
low latency
large bandwidth
and complementary metal-oxide-semiconductor compatibility
have been widely implemented for data transmission and actively explored as photonic neural networks in AI clusters. However
current silicon photonic integ
rated chips lack adaptability for multifunctional use and hardware-software systematic coordination
which is adverse to the development of photo-electronic AI clusters. Here
we develop a reconfigurable silicon photonic chip with 40 programmable unit cells integrating over 160 components
which
to the best of our knowledge
is the first to realize diverse functions for AI clusters with a chip
from computing acceleration and signal processing to network switching and secure encryption. Using a self-developed testing
compilation
and adjustment framework to the chip without in-chip monitoring photodetectors
we have demonstrated (1) 4 × 4 bi-direction unitary and 3 × 3 uni-direction non-unitary matrix multiplications
achieving a speed of over 1.92 TOPS with 6.22-bit precision and energy efficiency of 1.875 pJ MAC
−1
and neural networks for image recognition with a latency of 260 ps; (2) micro-ring modulator wavelength locking in the 5 to 32 Gb s
−1
transmission systems; (3) 4 × 4 photonic channel switching with low to –44 dB inter-channel crosstalk; (4) silicon photonic physical unclonable functions. This optoelectronic processing system
incorporating the photonic chip and its software stack
paves the way for both advanced photonic system-on-chip design and the construction of photo-electronic AI clusters.
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