Update README.md

README.md

@@ -7,6 +7,7 @@
   - [Enablements](#enablements) contains PDKs for open-source enablements such as NanGate45, ASAP7 and SKY130HD with FakeStack. Memories required by the designs are also included.
   - [Flows](#flows) contains tool setups and runscripts for both proprietary and open-source SP&R tools such as Cadence Genus/Innovus and OpenROAD.
   - [Code Elements](#code-elements) contains implementation of engines such as Clustering, Grouping, Gridding, Format translators required by Circuit Training flow.
+  - [Baseline for Circuit Training](#baseline) provides a competitive baseline for [Google Brain's Circuit Training](https://github.com/google-research/circuit_training).
   - [FAQ](#faq)
   - [Related Links](#related-links)
 
@@ -173,6 +174,12 @@ while allowing soft macros (standard-cell clusters) to also find good locations.
 
 <!--## **Reproducible Example Solutions** -->
 
+## **Baseline for Circuit Training**
+We provides a competitive baseline for [Google Brain's Circuit Training](https://github.com/google-research/circuit_training) by placing macros manually following similar rules as the RL agent. The example for Ariane133 implemented on NanGate45 is shown [here](https://github.com/TILOS-AI-Institute/MacroPlacement/tree/main/Flows/NanGate45/ariane133). We generate the manual macro placement in two steps:  
+(1) we call the [gridding](https://github.com/TILOS-AI-Institute/MacroPlacement/tree/main/CodeElements/Gridding) scripts to generate grid cells (27 x 27 in our case); (2) we manually place macros on the center of grid cells.
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 ## **FAQ**
 **Why are you doing this?**
 - The challenges of data and benchmarking in EDA research have, in our view, been contributing factors in the controversy regarding the Nature work. The mission of the [TILOS AI Institute](https://tilos.ai/) includes finding solutions to these challenges -- in high-stakes applied optimization domains (such as IC EDA), and at community-scale. We hope that our effort will become an existence proof for transparency, reproducibility, and democratization of research in EDA. [We applaud and thank Cadence Design Systems for allowing their tool runscripts to be shared openly by researchers, enabling reproducibility of results obtained via use of Cadence tools.]
@@ -210,4 +217,4 @@ while allowing soft macros (standard-cell clusters) to also find good locations.
 *arXiv:2004.10746*, 2020. \[[paper](https://arxiv.org/pdf/2004.10746.pdf)\]
 - 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. \[[link](https://tilos.ai/)\]
+- TILOS AI Institute. \[[link](https://tilos.ai/)\]
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