Photonic matrix multiplication lights up photonic accelerator and beyond
Matrix computation, as a fundamental building block of information processing in science
and technology, contributes most of the computational overheads in modern signal …
and technology, contributes most of the computational overheads in modern signal …
Optical neural networks: progress and challenges
Artificial intelligence has prevailed in all trades and professions due to the assistance of big
data resources, advanced algorithms, and high-performance electronic hardware. However …
data resources, advanced algorithms, and high-performance electronic hardware. However …
An optical neural chip for implementing complex-valued neural network
Complex-valued neural networks have many advantages over their real-valued
counterparts. Conventional digital electronic computing platforms are incapable of executing …
counterparts. Conventional digital electronic computing platforms are incapable of executing …
Efficient on-chip training of optical neural networks using genetic algorithm
Recent advances in silicon photonic chips have made huge progress in optical computing
owing to their flexibility in the reconfiguration of various tasks. Its deployment of neural …
owing to their flexibility in the reconfiguration of various tasks. Its deployment of neural …
[HTML][HTML] Analog optical computing for artificial intelligence
The rapid development of artificial intelligence (AI) facilitates various applications from all
areas but also poses great challenges in its hardware implementation in terms of speed and …
areas but also poses great challenges in its hardware implementation in terms of speed and …
Integrated photonic neural networks: Opportunities and challenges
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 …
computing with ultrafast and ultralow energy consumption in ultra-high-throughput, providing …
A compact butterfly-style silicon photonic–electronic neural chip for hardware-efficient deep learning
The optical neural network (ONN) is a promising hardware platform for next-generation
neurocomputing due to its high parallelism, low latency, and low energy consumption …
neurocomputing due to its high parallelism, low latency, and low energy consumption …
Interfacing photonics with artificial intelligence: an innovative design strategy for photonic structures and devices based on artificial neural networks
Over the past decades, photonics has transformed many areas in both fundamental
research and practical applications. In particular, we can manipulate light in a desired and …
research and practical applications. In particular, we can manipulate light in a desired and …
Recent progress of neuromorphic computing based on silicon photonics: Electronic–photonic Co-design, device, and architecture
The rapid development of neural networks has led to tremendous applications in image
segmentation, speech recognition, and medical image diagnosis, etc. Among various …
segmentation, speech recognition, and medical image diagnosis, etc. Among various …
Generalized robust training scheme using genetic algorithm for optical neural networks with imprecise components
One of the pressing issues for optical neural networks (ONNs) is the performance
degradation introduced by parameter uncertainties in practical optical components. Hereby …
degradation introduced by parameter uncertainties in practical optical components. Hereby …