Unverified Commit 9ef9154f by ZhiangWang033 Committed by GitHub

Update README.md

parent bf695eb7
......@@ -96,7 +96,17 @@ while allowing soft macros (standard-cell clusters) to also find good locations.
## **Related Links**
- R. Cheng and J. Yan, "On joint learning for solving placement and routing in chip design'',
*Proc. NeurIPS*, 2021. \[[paper](https://arxiv.org/pdf/2111.00234v1.pdf)\] [Code](https://github.com/Thinklab-SJTU/EDA-AI)
- F. -C. Chang, Y. -W. Tseng, Y. -W. Yu, S. -R. Lee, A. Cioba et al.,
*Proc. NeurIPS*, 2021. \[[paper](https://arxiv.org/pdf/2111.00234v1.pdf)\] \[[Code](https://github.com/Thinklab-SJTU/EDA-AI)\]
- F. -C. Chang, Y. -W. Tseng, Y. -W. Yu, S. -R. Lee, A. Cioba, et al.,
"Flexible multiple-objective reinforcement learning for chip placement",
*arXiv:2204.06407*, 2022. [paper](https://arxiv.org/pdf/2204.06407.pdf)
*arXiv:2204.06407*, 2022. \[[paper](https://arxiv.org/pdf/2204.06407.pdf)\]
- S. Guadarrama, S. Yue, T. Boyd, J. Jiang, W. Joe, et al.,
"Circuit training: an open-source framework for generating chip floor plans with distributed deep reinforcement learning",
2021. \[[code](https://github.com/google-research/circuit_training)\]
- A. Mirhoseini, A. Goldie, M. Yazgan, J. Jiang, E. Songhori, et al.,
"A graph placement methodology for fast chip design", *Nature*, 594(7862) (2021), pp. 207-212.
\[[paper](https://www.nature.com/articles/s41586-021-03544-w)\]
- A. Mirhoseini, A. Goldie, M. Yazgan, J. Jiang, E. Songhori, et al.,
"Chip Placement with Deep Reinforcement Learning",
*arXiv:2004.10746*, 2020. \[[paper](https://arxiv.org/pdf/2004.10746.pdf)\]
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