PIC-based joint transform correlator CNN

Nicola Peserico; Hangbo Yang; Xiaoxuan Ma; Shurui Li; Zibu Hu; Mostafa Hosseini; Aydin Babakhani; Puneet Gupta; Chee Wei Wong; Volker J. Sorger

doi:10.1117/12.2613810

9 March 2022 PIC-based joint transform correlator CNN

Nicola Peserico, Hangbo Yang, Xiaoxuan Ma, Shurui Li, Zibu Hu, Mostafa Hosseini, Aydin Babakhani, Puneet Gupta, Chee Wei Wong, Volker J. Sorger

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Proceedings Volume PC12019, AI and Optical Data Sciences III; PC120190L (2022) https://doi.org/10.1117/12.2613810
Event: SPIE OPTO, 2022, San Francisco, California, United States

Abstract

Here we show two PIC-based prototypes of a photonic convolution layer. System 1) is a Fourier-optics based 4F system integrated into a PIC. Unliked our earlier demonstration of a massively-parallel optical DMD-based CNN layer (Miscuglio, Sorger et al. OPTICA 2020), which processes 1000x1000 pixel matrices in a single time-step at 20KHz update rates (8x faster than SOW GPUs), this first-ever PIC-based 4F processor processes only 10’s of pixels, but at GHz rates (10^6 times faster than DMD, and 10^8 times faster than SLM). System 2) is a PIC-based joint-transform correlator where both the data and the convolution kernel are fed front-end and auto-convolve in the Fourier domain (autocorrelation). Note, the rapid 10GHz update rate of the kernel using foundry PIC components allows to perform online training on the system as well. Rapid and low SWaP ASICs are powerful tools for network edge processing and enable ns-short latency for rapid target tracking, for example.

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Nicola Peserico, Hangbo Yang, Xiaoxuan Ma, Shurui Li, Zibu Hu, Mostafa Hosseini, Aydin Babakhani, Puneet Gupta, Chee Wei Wong, and Volker J. Sorger "PIC-based joint transform correlator CNN", Proc. SPIE PC12019, AI and Optical Data Sciences III, PC120190L (9 March 2022); https://doi.org/10.1117/12.2613810

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KEYWORDS

Optical correlators

Joint transforms

Convolution

Photonic integrated circuits

Digital micromirror devices

Matrices

Prototyping

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