A survey on silicon photonics for deep learning
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 …
in domains such as computer vision, natural language processing, and general pattern …
A review of capabilities and scope for hybrid integration offered by silicon-nitride-based photonic integrated circuits
In this review we present some of the recent advances in the field of silicon nitride photonic
integrated circuits. The review focuses on the material deposition techniques currently …
integrated circuits. The review focuses on the material deposition techniques currently …
An optical neural network using less than 1 photon per multiplication
Deep learning has become a widespread tool in both science and industry. However,
continued progress is hampered by the rapid growth in energy costs of ever-larger deep …
continued progress is hampered by the rapid growth in energy costs of ever-larger deep …
Noise-resilient and high-speed deep learning with coherent silicon photonics
The explosive growth of deep learning applications has triggered a new era in computing
hardware, targeting the efficient deployment of multiply-and-accumulate operations. In this …
hardware, targeting the efficient deployment of multiply-and-accumulate operations. In this …
Scalable reservoir computing on coherent linear photonic processor
Photonic neuromorphic computing is of particular interest due to its significant potential for
ultrahigh computing speed and energy efficiency. The advantage of photonic computing …
ultrahigh computing speed and energy efficiency. The advantage of photonic computing …
Neuromorphic silicon photonics and hardware-aware deep learning for high-speed inference
M Moralis-Pegios… - Journal of Lightwave …, 2022 - ieeexplore.ieee.org
The relentless growth of Artificial Intelligence (AI) workloads has fueled the drive towards
non-Von Neuman architectures and custom computing hardware. Neuromorphic photonic …
non-Von Neuman architectures and custom computing hardware. Neuromorphic photonic …
Optical coherent dot-product chip for sophisticated deep learning regression
Optical implementations of neural networks (ONNs) herald the next-generation high-speed
and energy-efficient deep learning computing by harnessing the technical advantages of …
and energy-efficient deep learning computing by harnessing the technical advantages of …
Analog nanophotonic computing going practical: silicon photonic deep learning engines for tiled optical matrix multiplication with dynamic precision
Analog photonic computing comprises a promising candidate for accelerating the linear
operations of deep neural networks (DNNs), since it provides ultrahigh bandwidth, low …
operations of deep neural networks (DNNs), since it provides ultrahigh bandwidth, low …
Programmable photonic neural networks combining WDM with coherent linear optics
Neuromorphic photonics has relied so far either solely on coherent or Wavelength-Division-
Multiplexing (WDM) designs for enabling dot-product or vector-by-matrix multiplication …
Multiplexing (WDM) designs for enabling dot-product or vector-by-matrix multiplication …
Scalable and compact photonic neural chip with low learning-capability-loss
Photonic computation has garnered huge attention due to its great potential to accelerate
artificial neural network tasks at much higher clock rate to digital electronic alternatives …
artificial neural network tasks at much higher clock rate to digital electronic alternatives …