Update README.md

Docs/CodeElements/README.md

@@ -15,6 +15,9 @@ We are glad to see [grouping (clustering)](https://github.com/google-research/ci
 However, these [grouping (clustering)](https://github.com/google-research/circuit_training/tree/main/circuit_training/grouping) scripts still rely on the wrapper functions of plc client, which is a black box for the community.  In this doc, we document the implementation details of gridding, grouping and clustering. We implement all the code elements from scratch using python scripts, and our results match exactly that of Circuit Training.
 
 
+Note that we build our implementation on top of the [OpenROAD](https://github.com/ravi-varadarajan/OpenROAD.git) application, you need to build your own OpenROAD binary before you can run our scripts.  We also provide the [flow.py](https://github.com/TILOS-AI-Institute/MacroPlacement/blob/main/CodeElements/CodeFlowIntegration/flow.py), which runs Gridding, Grouping and Hypergraph Clustering in sequence.
+
+
 
 ## Table of Content
   - [Gridding](#gridding)
@@ -311,22 +314,20 @@ All methodologies that span synthesis and placement (of which we are aware) must
 #### **Our Implementation of Hypergraph Clustering.**
 Our implementation of hypergraph clustering takes the synthesized netlist and a .def file with placed IO ports as input, 
 then generates the clustered netlist (in lef/def format) using hMETIS (1998 binary). 
-In default mode, our implementation will also run RePlAce in GUI mode automatically to place the clustered netlist. 
-We implement the entire flow based on [OpenROAD APIs](https://github.com/the-openroad-project).
-**Please refer to [the OpenROAD repo](https://github.com/the-openroad-project) for explanation of each Tcl command.**
-
-We have provided the openroad exe in the [utils](https://github.com/TILOS-AI-Institute/MacroPlacement/tree/main/CodeElements/Clustering/src/utils) dir. Please note that [The OpenROAD Project](https://github.com/the-openroad-project) does not 
-distribute any compiled binaries. While we build our implementation on top of the OpenROAD application, our effort is not associated with the OpenROAD project.
+In default mode, our implementation will generate the clustered netlist in protocol buffer format and cooresponding plc file.
+We implement the entire flow based on [OpenROAD APIs](https://github.com/ravi-varadarajan/OpenROAD.git).
+**Please refer to [the OpenROAD repo](https://github.com/ravi-varadarajan/OpenROAD.git) for explanation of each Tcl command.**
 
+Please note that [The OpenROAD Project](https://github.com/ravi-varadarajan/OpenROAD.git) does not 
+distribute any compiled binaries. You need to build your own OpenROAD binary before you run our scripts.
 
 Input file: [setup.tcl](https://github.com/TILOS-AI-Institute/MacroPlacement/blob/main/CodeElements/Clustering/test/setup.tcl) (you can follow the example to set up your own design) and [FixFile](https://github.com/TILOS-AI-Institute/MacroPlacement/blob/main/CodeElements/Clustering/test/fix_files_grouping/ariane.fix.old) (This file is generated by our [Grouping](https://github.com/TILOS-AI-Institute/MacroPlacement/tree/main/CodeElements/Grouping) scripts)
 
-Output_files: [clusters.lef](https://github.com/TILOS-AI-Institute/MacroPlacement/blob/main/CodeElements/Clustering/test/results/OpenROAD/clusters.lef) and [clustered_netlist.def](https://github.com/TILOS-AI-Institute/MacroPlacement/blob/main/CodeElements/Clustering/test/results/OpenROAD/clustered_netlist.def) for OpenROAD flows; [cluster.tcl](https://github.com/TILOS-AI-Institute/MacroPlacement/blob/main/CodeElements/Clustering/test/results/Cadence/ariane_cluster_500.tcl) for Cadence flows; [ariane.pb.txt](https://github.com/TILOS-AI-Institute/MacroPlacement/blob/main/CodeElements/Clustering/test/results/Protocol_buffer_format/ariane.pb.txt) for clustered netlist in protocol buffer format.
+Output_files: the clustered netlist in protocol buffer format and cooresponding plc file.
 
-Note that the [example](https://github.com/TILOS-AI-Institute/MacroPlacement/tree/main/CodeElements/Clustering/test) that we provide is the Ariane133 design implemented in NanGate45.  The netlist and corresponding def file with placed instances are generated by [Genus iSpatial](https://github.com/TILOS-AI-Institute/MacroPlacement/tree/main/Flows/NanGate45/ariane133) flow. Here, the macro placement is automatically done by the Genus and Innovus tools,
+Note that the [example](https://github.com/TILOS-AI-Institute/MacroPlacement/tree/main/CodeElements/Clustering/test) that we provide is the ariane design implemented in NanGate45.  The netlist and corresponding def file with placed instances are generated by [Genus iSpatial](https://github.com/TILOS-AI-Institute/MacroPlacement/tree/main/Flows/NanGate45/ariane133) flow. Here the macro placement is automatically done by the Genus and Innovus tools,
 i.e., according to Flow **(B.1)** above.
 
- 
 ## **Thanks**
  
 We thank Google engineers for Q&A in a shared document, as well as live discussions on May 19, 2022, that explained the hypergraph clustering method used in Circuit Training. All errors of understanding and implementation are the authors'. We will rectify such errors as soon as possible after being made aware of them.