Photonic Accelerator

Photonic accelerators leverage the speed and energy efficiency of light to accelerate computationally intensive tasks, primarily focusing on deep neural network (DNN) inference and training. Current research emphasizes developing efficient architectures, such as those based on Mach-Zehnder interferometers and microring resonators, and optimizing algorithms to mitigate challenges like thermal sensitivity and hardware noise, including exploring sparse architectures and in-situ calibration techniques. This field holds significant promise for improving the performance and energy efficiency of AI applications, particularly in resource-constrained environments like edge computing, and for solving complex problems like partial differential equations.

Papers

July 12, 2022

Photonic Reconfigurable Accelerators for Efficient Inference of CNNs with Mixed-Sized Tensors
Sairam Sri Vatsavai, Ishan G Thakkar
Convolutional Neural Network Hardware Accelerator Efficient Inference Photonic Accelerator Sparse Tensor

May 17, 2022

A Silicon Photonic Accelerator for Convolutional Neural Networks with Heterogeneous Quantization
Febin Sunny, Mahdi Nikdast, Sudeep Pasricha
Convolutional Neural Network Photonic Accelerator CNN Accelerator Silicon Photonics Heterogeneous Quantization

May 12, 2022

Controlling chaotic itinerancy in laser dynamics for reinforcement learning
Ryugo Iwami, Takatomo Mihana, Kazutaka Kanno, Satoshi Sunada, Makoto Naruse, Atsushi Uchida
Reinforcement Learning Multi Armed Bandit Photonic Neural Network Photonic Accelerator

March 30, 2022

Theory of Acceleration of Decision Making by Correlated Time Sequences
Norihiro Okada, Tomoki Yamagami, Nicolas Chauvet, Yusuke Ito, Mikio Hasegawa, Makoto Naruse
Theoretical Understanding Decision Making Low Rate ACCELERATION Photonic Accelerator Correlated Time Series

Photonic Accelerator

Papers

Photonic Reconfigurable Accelerators for Efficient Inference of CNNs with Mixed-Sized Tensors

A Silicon Photonic Accelerator for Convolutional Neural Networks with Heterogeneous Quantization

Controlling chaotic itinerancy in laser dynamics for reinforcement learning

Theory of Acceleration of Decision Making by Correlated Time Sequences