15 citations · 29 across the 9 of their papers we have counts for
9 papers
Delving into Effective Gradient Matching for Dataset Condensation
Zixuan Jiang, Jiaqi Gu, Mingjie Liu +1
As deep learning models and datasets rapidly scale up, network training is extremely time-consuming and resource-costly. Instead of training on the entire dataset, learning with a…
ELight: Enabling Efficient Photonic In-Memory Neurocomputing with Life Enhancement
Hanqing Zhu, Jiaqi Gu, Chenghao Feng +4
With the recent advances in optical phase change material (PCM), photonic in-memory neurocomputing has demonstrated its superiority in optical neural network (ONN) designs with nea…
ADEPT: Automatic Differentiable DEsign of Photonic Tensor Cores
Jiaqi Gu, Hanqing Zhu, Chenghao Feng +5
Photonic tensor cores (PTCs) are essential building blocks for optical artificial intelligence (AI) accelerators based on programmable photonic integrated circuits. PTCs can achiev…
L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization
Jiaqi Gu, Hanqing Zhu, Chenghao Feng +3
Silicon-photonics-based optical neural network (ONN) is a promising hardware platform that could represent a paradigm shift in efficient AI with its CMOS-compatibility, flexibility…
A New Acceleration Paradigm for Discrete CosineTransform and Other Fourier-Related Transforms
Zixuan Jiang, Jiaqi Gu, David Z. Pan
Discrete cosine transform (DCT) and other Fourier-related transforms have broad applications in scientific computing. However, off-the-shelf high-performance multi-dimensional DCT…
Delving into Macro Placement with Reinforcement Learning
Zixuan Jiang, Ebrahim Songhori, Shen Wang +5
In physical design, human designers typically place macros via trial and error, which is a Markov decision process. Reinforcement learning (RL) methods have demonstrated superhuman…