Search Results for author: Zixuan Jiang

Found 7 papers, 3 papers with code

An Efficient Training Framework for Reversible Neural Architectures

no code implementations ECCV 2020 Zixuan Jiang, Keren Zhu, Mingjie Liu, Jiaqi Gu, David Z. Pan

In this work, we formulate the decision problem for reversible operators with training time as the objective function and memory usage as the constraint.

ELight: Enabling Efficient Photonic In-Memory Neurocomputing with Life Enhancement

no code implementations15 Dec 2021 Hanqing Zhu, Jiaqi Gu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen, David Z. Pan

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 near-zero static power consumption, time-of-light latency, and compact footprint.

L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization

1 code implementation NeurIPS 2021 Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Zixuan Jiang, Ray T. Chen, David Z. Pan

In this work, we propose a closed-loop ONN on-chip learning framework L2ight to enable scalable ONN mapping and efficient in-situ learning.

Delving into Macro Placement with Reinforcement Learning

no code implementations6 Sep 2021 Zixuan Jiang, Ebrahim Songhori, Shen Wang, Anna Goldie, Azalia Mirhoseini, Joe Jiang, Young-Joon Lee, David Z. Pan

In physical design, human designers typically place macros via trial and error, which is a Markov decision process.

reinforcement-learning

Optimizer Fusion: Efficient Training with Better Locality and Parallelism

no code implementations1 Apr 2021 Zixuan Jiang, Jiaqi Gu, Mingjie Liu, Keren Zhu, David Z. Pan

Machine learning frameworks adopt iterative optimizers to train neural networks.

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