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


Oct 27, 2021
Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Zixuan Jiang, Ray T. Chen, David Z. Pan

* 10 pages. Accepted to NeurIPS 2021 

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Delving into Macro Placement with Reinforcement Learning


Sep 06, 2021
Zixuan Jiang, Ebrahim Songhori, Shen Wang, Anna Goldie, Azalia Mirhoseini, Joe Jiang, Young-Joon Lee, David Z. Pan

* Accepted at 3rd ACM/IEEE Workshop on Machine Learning for CAD (MLCAD) 

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Towards Memory-Efficient Neural Networks via Multi-Level in situ Generation


Sep 05, 2021
Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen, David Z. Pan

* Accepted by International Conference on Computer Vision (ICCV) 2021 

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Optimizer Fusion: Efficient Training with Better Locality and Parallelism


Apr 01, 2021
Zixuan Jiang, Jiaqi Gu, Mingjie Liu, Keren Zhu, David Z. Pan

* It is published as a paper at the Hardware Aware Efficient Training (HAET) workshop of ICLR 2021. There are 4 pages excluding references and appendices 

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Logic Synthesis Meets Machine Learning: Trading Exactness for Generalization


Dec 15, 2020
Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa Junior, Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. de Abreu, Isac de Souza Campos, Augusto Berndt, Cristina Meinhardt, Jonata T. Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit O. Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee

* In this 23 page manuscript, we explore the connection between machine learning and logic synthesis which was the main goal for International Workshop on logic synthesis. It includes approaches applied by ten teams spanning 6 countries across the world 

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Logic Synthesis Meets Machine Learning:Trading Exactness for Generalization


Dec 04, 2020
Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa Junior, Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. de Abreu, Isac de Souza Campos, Augusto Berndt, Cristina Meinhardt, Jonata T. Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit O. Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee

* In this 23 page manuscript, we explore the connection between machine learning and logic synthesis which was the main goal for International Workshop on logic synthesis. It includes approaches applied by ten teams spanning 6 countries across the world 

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