https://github.com/thinklab-sjtu/eda-ai

Implementations of DeepPlace, PRNet, HubRouter, PreRoutGNN and FlexPlanner.
https://github.com/thinklab-sjtu/eda-ai

ai4eda deep-learning eda-ai floorplan placement pytorch routing

Last synced: 2 days ago
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Implementations of DeepPlace, PRNet, HubRouter, PreRoutGNN and FlexPlanner.

• Host: GitHub
• URL: https://github.com/thinklab-sjtu/eda-ai
• Owner: Thinklab-SJTU
• License: mit
• Created: 2021-10-24T03:47:55.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2024-11-26T04:00:57.000Z (26 days ago)
• Last Synced: 2024-12-13T14:07:35.791Z (9 days ago)
• Topics: ai4eda, deep-learning, eda-ai, floorplan, placement, pytorch, routing
• Language: Raku
• Homepage:
• Size: 26.9 MB
• Stars: 214
• Watchers: 8
• Forks: 48
• Open Issues: 11
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

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*)

- NeurIPS 2024 paper "FlexPlanner: Flexible 3D Floorplanning via Deep Reinforcement Learning in Hybrid Action Space with Multi-Modality Representation" (*FlexPlanner*)

# 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},

  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},

  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={Proceedings of the AAAI Conference on Artificial Intelligence},

  year={2024}

}

```

```

@inproceedings{zhongflexplanner,

  title={FlexPlanner: Flexible 3D Floorplanning via Deep Reinforcement Learning in Hybrid Action Space with Multi-Modality Representation},

  author={Zhong, Ruizhe and Du, Xingbo and Kai, Shixiong and Tang, Zhentao and Xu, Siyuan and Jianye, HAO and Yuan, Mingxuan and Yan, Junchi},

  booktitle = {Advances in Neural Information Processing Systems},

  year = {2024}

}

```