Optical kernel computing: a photonic hardware accelerator for AI

Bahram Jalali; Tingyi Zhou; Fabien Scalzo

doi:10.1117/12.2613829

9 March 2022 Optical kernel computing: a photonic hardware accelerator for AI

Bahram Jalali, Tingyi Zhou, Fabien Scalzo

Proceedings Volume PC12019, AI and Optical Data Sciences III; PC120190V (2022) https://doi.org/10.1117/12.2613829
Event: SPIE OPTO, 2022, San Francisco, California, United States

Abstract

We show that spectral mapping of data onto femtosecond optical pulses and a projection into an implicit, higher dimensional space using nonlinear optical transformation of data reduces the latency in data classification by several orders of magnitude. The approach is validated by the classification of various datasets, including brain intracranial pressure, cancer cell imaging, spoken digit recognition, and the classic Exclusive OR (XOR) benchmark for nonlinear classification. Single-shot operation is demonstrated using time stretch data acquisition. Due to the modest degrees of freedom in the optical domain, the classification accuracy is data-dependent.

Conference Presentation

Citation Download Citation

Bahram Jalali, Tingyi Zhou, and Fabien Scalzo "Optical kernel computing: a photonic hardware accelerator for AI", Proc. SPIE PC12019, AI and Optical Data Sciences III, PC120190V (9 March 2022); https://doi.org/10.1117/12.2613829

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available