Welcome to Lightning, the next-generation photonic computing system invented here at MIT!

Lightning is a reconfigurable photonic-electronic smartNIC that serves real-time deep neural network inference requests at 100 Gbps. Lightning uses a novel datapath that feeds traffic from the NIC into the photonic domain without creating digital packet processing and data movement bottlenecks. Lightning achieves this by employing a reconfigurable count-action abstraction, which keeps track of the computation Directed Acyclic Graph (DAG) of each inference packet. Our count-action abstraction decouples the compute control plane from the data plane by counting the number of operations in each task of the DAG and triggers the execution of the next tasks as soon as the previous task is finished, without interrupting the flow of the data.

To know more about this project:

What's New?


Technical publications

    [1] Lightning: A Reconfigurable Photonic-Electronic SmartNIC for Fast and Energy-Efficient Inference

    Zhizhen Zhong, Mingran Yang, Jay Lang, Christian Williams, Liam Kronman, Alexander Sludds, Homa Esfahanizadeh, Dirk Englund, Manya Ghobadi

    ACM SIGCOMM 2023 

    Paper | Artifact | Demo | Slides | Video



    [2] On-Fiber Photonic Computing

    Zhizhen Zhong*, Mingran Yang*, Manya Ghobadi (co-first author)

    ACM HotNets 2023 



    [3] Delocalized Photonic Deep Learning on the Internet's Edge

    Alexander Sludds, Saumil Bandyopadhyay, Zaijun Chen, Zhizhen Zhong, Jared Cochrane, Liane Bernstein, Darius Bunandar, P. Ben Dixon, Scott Hamilton, Matthew Streshinsky, Ari Novack, Tom Baehr-Jones, Michael Hochberg, Manya Ghobadi, Ryan Hamerly, Dirk Englund

    Science, Vol. 378 (6617) 2022

    Paper | Artifact 


    [4] IOI: In-Network Optical Inference

    Zhizhen Zhong, Weiyang Wang, Manya Ghobadi, Alexander Sludds, Ryan Hamerly, Liane Bernstein, Dirk Englund

    ACM SIGCOMM 2021 Workshop on Optical Systems (OptSys 2021)

    Paper | Slides