Updated README

Flows/README.md

@@ -101,4 +101,8 @@ Clone ORFS and build OpenROAD tools following the steps given [here](https://git
   ```
   
 The screenshot of the Ariane 136 testcase using the ORFS (RTL-MP) on NanGate45 enablement is shown below.  
+<<<<<<< HEAD
 <img src="./NanGate45/ariane136/screenshots/Ariane136_ORFS_SPNR.png" alt="ariane136_orfs" width="400"/>
+=======
+<img src="./NanGate45/ariane136/screenshots/Ariane136_ORFS_SPNR.png" alt="ariane136_orfs" width="400"/>
+>>>>>>> f203df754b535b476f5d8edf541bc18ca6d902ea

README.md

@@ -194,11 +194,12 @@ 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., 
 "Flexible multiple-objective reinforcement learning for chip placement",
 *arXiv:2204.06407*, 2022. \[[paper](https://arxiv.org/pdf/2204.06407.pdf)\]
+- S. Yue, E. M. Songhori, J. W. Jiang, T. Boyd, A. Goldie, A. Mirhoseini and S. Guadarrama, "Scalability and Generalization of Circuit Training for Chip Floorplanning", *ISPD*, 2022. \[[paper](https://dl.acm.org/doi/abs/10.1145/3505170.3511478)\]\[[ppt](http://www.ispd.cc/slides/2021/protected/2_2_Goldie_Mirhoseini.pdf)\]
+- R. Cheng and J. Yan, "On joint learning for solving placement and routing in chip design",
+*Proc. NeurIPS*, 2021. \[[paper](https://arxiv.org/pdf/2111.00234v1.pdf)\] \[[code](https://github.com/Thinklab-SJTU/EDA-AI)\]
 - S. Guadarrama, S. Yue, T. Boyd, J. Jiang,  E. Songhori, 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.,
@@ -207,7 +208,6 @@ while allowing soft macros (standard-cell clusters) to also find good locations.
 - A. Mirhoseini, A. Goldie, M. Yazgan, J. Jiang, E. Songhori, et al.,
 "Chip Placement with Deep Reinforcement Learning",
 *arXiv:2004.10746*, 2020. \[[paper](https://arxiv.org/pdf/2004.10746.pdf)\]
-- S. Yue, E. M. Songhori, J. W. Jiang, T. Boyd, A. Goldie, A. Mirhoseini and S. Guadarrama, "Scalability and Generalization of Circuit Training for Chip Floorplanning", *ISPD*, 2022. \[[paper](https://dl.acm.org/doi/abs/10.1145/3505170.3511478)\]\[[ppt](http://www.ispd.cc/slides/2021/protected/2_2_Goldie_Mirhoseini.pdf)\]
 - Z. Jiang, E. Songhori, S. Wang, A. Goldie, A. Mirhoseini, et al., "Delving into Macro Placement with Reinforcement Learning", *MLCAD*, 2021. \[[paper](https://arxiv.org/pdf/2109.02587)\]
 - A Gentle Introduction to Graph Neural Networks. [[Link](https://distill.pub/2021/gnn-intro/)]
 - TILOS AI Institute. \[[link](https://tilos.ai/)\]
\ No newline at end of file