Deep learning has led to unprecedented successes in solving some very difficult problems
in domains such as computer vision, natural language processing, and general pattern …

Deep learning has been revolutionizing information processing in many fields of science
and engineering owing to the massively growing amounts of data and the advances in deep …

Convolutional Neural Networks (CNNs) are powerful and highly ubiquitous tools for
extracting features from large datasets for applications such as computer vision and natural …

Photonic solutions are today a mature industrial reality concerning high speed, high
throughput data communication and switching infrastructures. It is still a matter of …

The massive growth of machine learning-based applications and the end of Moore's law
have created a pressing need to redesign computing platforms. We propose Lightning, the …

Domain-specific neural network accelerators have seen growing interest in recent years due
to their improved energy efficiency and performance compared to CPUs and GPUs. In this …

The number of parameters in deep neural networks (DNNs) is scaling at about 5× the rate of
Moore's Law. To sustain this growth, photonic computing is a promising avenue, as it …

摘要由于光传输具备高通量, 低延迟, 低能耗等优势, 光学神经网络有望应对目前人工智能技术
发展中所面临的能耗和计算效率的挑战, 成为近年来学术界和工业界的研究热点 …

Advances in deep learning research over the past decade have been enabled by an
increasingly unsustainable demand for compute power. This trend has dramatically …

In recent decades, the demand for computational power has surged, particularly with the
rapid expansion of artificial intelligence (AI). As we navigate the post-Moore's law era, the …