Lithography-free integrated photonics for reconfigurable computing acceleration

Liang Feng; Tianwei Wu; Marco Menarini

doi:10.1117/12.2692545

13 March 2024 Lithography-free integrated photonics for reconfigurable computing acceleration

Liang Feng, Tianwei Wu, Marco Menarini

Proceedings Volume PC12903, AI and Optical Data Sciences V; PC1290301 (2024) https://doi.org/10.1117/12.2692545
Event: SPIE OPTO, 2024, San Francisco, California, United States

Abstract

We present a new lithography-free integrated photonic processor, targeting dynamic control of spatial-temporal modulations of the imaginary index on an active semiconductor platform. Leveraging its real-time reconfigurability, we aim to realize photonic neural networks with extraordinary flexibility to perform in-situ learning and training with high accuracy. Our work delivers a brand new and ultra-flexible integrated photonic paradigm for reconfigurable networking and computing, with great potential to process large, non-local datasets with high throughputs.

Conference Presentation

Citation Download Citation

Liang Feng, Tianwei Wu, and Marco Menarini "Lithography-free integrated photonics for reconfigurable computing acceleration", Proc. SPIE PC12903, AI and Optical Data Sciences V, PC1290301 (13 March 2024); https://doi.org/10.1117/12.2692545

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