Shurui Li

Shurui Li

Ph.D. Candidate at UCLA, Specialized in Deep Learning Accelerator, Optical Neural Network, and Computer Architecture

ReFOCUS: Reusing Light for Efficient Fourier Optics-Based Photonic Neural Network Accelerator

Published in IEEE/ACM International Symposium on Microarchitecture (MICRO), 2023

Recommended citation: Li, S., Yang, H., Wong, C.W., Sorger, V.J. and Gupta, P., 2023, October. ReFOCUS: Reusing Light for Efficient Fourier Optics-Based Photonic Neural Network Accelerator. In Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture (pp. 569-583). https://dl.acm.org/doi/proceedings/10.1145/3613424

Follow up work of PhotoFourier, introduced optical buffer and WDM to further improve power efficiency of JTC-based neural network accelerator.

Download paper here

BibTeX citation:

@proceedings{10.1145/3613424, title = {MICRO ‘23: Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture}, year = {2023}, isbn = {9798400703294}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, location = {, Toronto, ON, Canada, } }