Evidence map›Paper›PMID 40603838›Full record

ArticleNature communications2025

Seamless optical cloud computing across edge-metro network for generative AI.

Sizhe Xing, Aolong Sun, Chengxi Wang, Yizhi Wang, Boyu Dong, Junhui Hu, Xuyu Deng, An Yan, Yinjun Liu, Fangchen Hu and 11 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Sizhe Xing *School of Information Science and Technology, Fudan University, Shanghai, China.
Aolong Sun *School of Information Science and Technology, Fudan University, Shanghai, China.
Chengxi Wang *School of Information Science and Technology, Fudan University, Shanghai, China.
Yizhi WangCentre for Photonic Systems, Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, CB3 0FA, UK.
Boyu DongSchool of Information Science and Technology, Fudan University, Shanghai, China.
Junhui HuSchool of Information Science and Technology, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0002-9250-8084
Xuyu DengSchool of Information Science and Technology, Fudan University, Shanghai, China.
An YanSchool of Information Science and Technology, Fudan University, Shanghai, China.
Yinjun LiuSchool of Information Science and Technology, Fudan University, Shanghai, China.
Fangchen HuZhangjiang Laboratory, Shanghai, China.
Zhongya LiSchool of Information Science and Technology, Fudan University, Shanghai, China.
Ouhan HuangSchool of Information Science and Technology, Fudan University, Shanghai, China.
Junhao ZhaoSchool of Information Science and Technology, Fudan University, Shanghai, China.
Yingjun ZhouSchool of Information Science and Technology, Fudan University, Shanghai, China.
Ziwei LiSchool of Information Science and Technology, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0002-7631-989X
Jianyang ShiSchool of Information Science and Technology, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0002-5478-3704
Xi XiaoNational Information Optoelectronics Innovation Center, Wuhan, 430074, China.ORCID http://orcid.org/0000-0003-3696-877X
Richard PentyCentre for Photonic Systems, Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, CB3 0FA, UK.
Qixiang ChengCentre for Photonic Systems, Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, CB3 0FA, UK. qc223@cam.ac.uk.ORCID http://orcid.org/0000-0001-8671-2102
Nan ChiSchool of Information Science and Technology, Fudan University, Shanghai, China. nanchi@fudan.edu.cn.ORCID http://orcid.org/0000-0003-4966-3844
Junwen ZhangSchool of Information Science and Technology, Fudan University, Shanghai, China. junwenzhang@fudan.edu.cn.ORCID http://orcid.org/0000-0001-8041-1608

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62171137National Natural Science Foundation of China (National Science Foundation of China) 62235005
6 · The paper itself

Abstract

The rapid advancement of generative artificial intelligence (AI) in recent years has profoundly reshaped modern lifestyles, necessitating a revolutionary architecture to support the growing demands for computational power. Cloud computing has become the driving force behind this transformation. However, it consumes significant power and faces computation security risks due to the reliance on extensive data centers and servers in the cloud. Reducing power consumption while enhancing computational scale remains persistent challenges in cloud computing. Here, we propose and experimentally demonstrate an optical cloud computing system that can be seamlessly deployed across edge-metro network. By modulating inputs and models into light, a wide range of edge nodes can directly access the optical computing center via the edge-metro network. The experimental validations show an energy efficiency of

Identifiers

PMID40603838
PMCPMC12223312

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.