EDA-AI

EDA-AI

Implementation of NeurIPS 2021 paper "On Joint Learning for Solving Placement and Routing in Chip Design" & NeurIPS 2022 paper "The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design".

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EDA-AI is a repository containing implementations of cutting-edge research papers in the field of chip design. It includes DeepPlace, PRNet, HubRouter, and PreRoutGNN models for tasks such as placement, routing, timing prediction, and global routing. Researchers and practitioners can leverage these implementations to explore advanced techniques in chip design.

README:

Implementations of

  • NeurIPS 2021 paper "On Joint Learning for Solving Placement and Routing in Chip Design" (DeepPlace)
  • NeurIPS 2022 paper "The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design" (PRNet)
  • NeurIPS 2023 paper "HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection" (HubRouter)
  • AAAI 2024 paper "PreRoutGNN for Timing Prediction with Order Preserving Partition: Global Circuit Pre-training, Local Delay Learning and Attentional Cell Modeling" (PreRoutGNN)

Citations

If you find our paper/code useful in your research, please citing

@article{cheng2021joint,
  title={On Joint Learning for Solving Placement and Routing in Chip Design},
  author={Cheng, Ruoyu and Yan, Junchi},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={16508--16519},
  year={2021}
}
@article{cheng2022policy,
  title={The policy-gradient placement and generative routing neural networks for chip design},
  author={Cheng, Ruoyu and Lyu, Xianglong and Li, Yang and Ye, Junjie and Hao, Jianye and Yan, Junchi},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={26350--26362},
  year={2022}
}
@inproceedings{du2023hubrouter,
  title = {HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection},
  author = {Du, Xingbo and Wang, Chonghua and Zhong, Ruizhe and Yan, Junchi},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2023}
}
@inproceedings{zhong2024preroutgnn,
  title={PreRoutGNN for Timing Prediction with Order Preserving Partition: Global Circuit Pre-training, Local Delay Learning and Attentional Cell Modeling},
  author={Zhong, Ruizhe and Ye, Junjie and Tang, Zhentao and Kai, Shixiong and Yuan, Mingxuan and Hao, Jianye and Yan, Junchi},
  booktitle={AAAI},
  year={2024}
}

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