Abstract
The large data movement required in high-performance computing and artificial intelligence workloads has exposed the fundamental limits of electrical interconnects, where resistive losses, capacitive loading and frequency-dependent distortion increasingly constrain bandwidth, latency and energy efficiency. Optical compute interconnects, which replace electrical links with co-packaged photonic channels, could provide low propagation loss, high bandwidth and superior signal integrity. Here, we examine the development of optical chip-to-chip interconnects and co-packaged optics for high-performance computing and artificial intelligence. We analyse the key domains, including electrical subsystems, electro–optical and opto–electronic conversion interfaces, and optical transmission networks, that determine system-level performance across bandwidth, energy and latency metrics. We also provide a technology roadmap from two-dimensional (2D) co-packaged optics, 2.5D interposer-based integration and 3D heterogeneous stacking, identifying critical challenges in thermal management, manufacturability and standardization that will need to be addressed to establish optical compute interconnects as a foundational communication technology for high-performance computing infrastructure.
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Acknowledgements
This work was supported by the Air Force Office of Scientific Research Young Investigator Program (YIP) (FA9550-23-1-0159), the National Science Foundation (NSF) under Electrical, Communications and Cyber Systems (ECCS) (ECCS-2332060 and ECCS-2328839), under Industry-University Cooperative Research Centers (IUCRC) (EEC-2231625), and under Materials Research Science and Engineering Centers (MRSEC) (DMR-2309037), the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and ICT; RS-2025-24535263 and RS-2025-25442127), the Global–Learning & Academic research institution for Master’s–PhD students and Postdocs (LAMP) Program of the NRF funded by the Ministry of Education (RS-2024-00442483), the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korean government (MOTIE; RS-2025-02263458), the MOE AcRF Tier 3 grant (MOE-MOET32023-0003) ‘Quantum Geometric Advantage’ and the A*STAR, Singapore, Advanced Manufacturing and Engineering (AME) Individual Research Grant (IRG) under the Project M23M6c0109.
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These authors contributed equally: Byungsoo Kim, Soo Ho Choi, Georgii Zograf, Young Jin Yoo, Yongmin Baek, Seokho Kim
Authors and Affiliations
Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA
Byungsoo Kim, Yongmin Baek, Seokho Kim & Kyusang Lee
School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
Byungsoo Kim & Jongchan Kim
Department of Integrated Display Engineering, Yonsei University, Seoul, Republic of Korea
Byungsoo Kim & Jongchan Kim
Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
Soo Ho Choi & Hyunseok Kim
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore
Georgii Zograf & Sang Hoon Chae
School of Materials Science and Engineering, Nanyang Technological University, Singapore, Singapore
Georgii Zograf & Sang Hoon Chae
Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
Young Jin Yoo & Jeehwan Kim
AI Infra Optimization Team, SK hynix Inc., Seoul, Republic of Korea
Seunghoon Hong
Department of Material Science and Engineering, University of Virginia, Charlottesville, VA, USA
Kyusang Lee
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B.K., S. H. Choi, G.Z., Y.J.Y., Y.B. and S.K. contributed equally to this review article. B.K., S. H. Choi, G.Z., Y.J.Y., Y.B. and K.L. wrote the initial draft and researched data for this review article. B.K., Y.B., S.K., Jongchan Kim, Jeehwan Kim, S. H. Chae, H.K., S.H. and K.L. contributed to reviewing and editing before submission
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Kim, B., Choi, S.H., Zograf, G. et al. Co-packaged optics for high-performance computing and artificial intelligence.
Nat Electron (2026). https://doi.org/10.1038/s41928-026-01681-6
Received:18 November 2025
Accepted:08 July 2026
Published:19 August 2026
Version of record:19 August 2026
DOI
:https://doi.org/10.1038/s41928-026-01681-6
