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Accelerating Neural Networks for Large Language Models and Graph Processing with Silicon Photonics
In the rapidly evolving landscape of artificial intelligence, large language models (LLMs) and graph processing have emerged as transformative technologies for natural language processing (NLP), computer vision, and graph-structured data applications.
GHOST: A Graph Neural Network Accelerator using Silicon Photonics
Graph neural networks (GNNs) have emerged as a powerful approach for modelling and learning from graph-structured data.
TRON: Transformer Neural Network Acceleration with Non-Coherent Silicon Photonics
Transformer neural networks are rapidly being integrated into state-of-the-art solutions for natural language processing (NLP) and computer vision.
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