Integrated Photonic Neural Networks: Opportunities and Challenges
Kun Liao, Tianxiang Dai, Qiuchen Yan, Xiaoyong Hu, Qihuang Gong
Abstract
High Resolution Image Download MS PowerPoint Slide Photonic neural networks benefit from the use of photons to perform intelligent inference computing with ultrafast and ultralow energy consumption in ultra-high-throughput, providing the efficient photonic hardware for the new generation of intelligent computing, and the effective way to support large-scale integration for on-chip all-optical computing chips. With the rapid development of photonic neural networks, demands for efficient computation power have increased dramatically. However, the weak and impractical optical nonlinear activations, the lack of suitable configurations for integrated photonic hardware, and proper optical storage mediums pose challenges to this field. In this Perspective, we propose our current point of view and a suggestive roadmap in the field of integrated photonic platform for optical neural networks. Throughout the discussion, we highlight recent progresses meeting with major challenges. We also identify some next challenges still ahead to realize integrated photonic neural networks capable of matching the current computational power of graphic cards.