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/ /___/ /_/ / _, _/ ___ /_____/ __/ / / /_/ / |/ |/ /
\____/\____/_/ |_/_/  |_|    /_/   /_/\____/|__/|__/


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CGRA-Flow is an integrated framework for CGRA compilation, exploration, synthesis, and development.

User Interface Snapshot/Demo

A demo at repl.it (https://repl.it/@ChengTan/cgra-flow) shows some features of CGRA-Flow (the verilog generation and evaluation are not available due to repl.it's limited support of python environment). To explore all the features, please setup CGRA-Flow locally or leverage the docker image.

Docker

The docker image is available here.

Recommended machine configuration

• CPU: >= 6 cores
• Memory: 25~30G

2x2 tiles run time:

clk_period (ps)	frequency (Hz)	time (hour)
1000	1G	~40
10,000	100M	~7
100,000	10M	~7

As CGRA-Flow requires GUI, a script is provided for setting up the display:

 docker pull cgra/cgra-flow:20251214_demo

 # For Mac users:
 sh ./run_mac_docker.sh

 # Windows Docker customtkinter style UI (Please setup GUI (X-11) first)
 # In WSL, execute below script, it will enter container and config x11 DISPLAY automatically
 sh ./run_windows_docker.sh

 # Don't forget to activate the python virtual environment once you are in the container:
 source /WORK_REPO/venv/bin/activate

Otherwise, if you don't need the GUI, development can be performed in the container with the environment well set up:

 docker pull cgra/cgra-flow:20251214_demo
 docker run -it cgra/cgra-flow:20251214_demo
 source /WORK_REPO/venv/bin/activate

Building Docker Image from Dockerfile

If you prefer to build the Docker image locally:

 # Build the Docker image
 docker build -t cgra-flow:latest .

Execution

 # Startup theme mode selector UI
 python launch.py

Mac user debugging and troubleshooting steps doc

Installation

CGRA-Flow requires Python3.7.

Refer to the build scripts or look into specific repo for the manual installation if you don't want to use docker.

Contribution Guide

👋 Welcome Contributors!

To contribute to this project, you can clone the Github repository and mount it as a volume in the Docker container. This allow you to edit code on your host machine while testing changes inside the container environment. Update the Docker run command to mount your local repository(take run_windows_docker.sh as an example):

IMAGE=cgra/cgra-flow:20251112
CONTAINER=mycgraflow
XSOCK=/tmp/.X11-unix
# for developer: mount the upstream repo to the container.
# Please update the path to the actual path on your machine.
MOUNT_PATH=/path/to/your/cloned/CGRA-Flow:/path/to/container
sudo docker run \
    -it \
    --name=$CONTAINER \
    -v $XSOCK:$XSOCK:rw \
    -v $MOUNT_PATH \
    -e DISPLAY=$DISPLAY \
    $IMAGE \
    /bin/bash

Citation

@inproceedings{tan2020opencgra,
  title={OpenCGRA: An open-source unified framework for modeling, testing, and evaluating CGRAs},
  author={Tan, Cheng and Xie, Chenhao and Li, Ang and Barker, Kevin J and Tumeo, Antonino},
  booktitle={2020 IEEE 38th International Conference on Computer Design (ICCD)},
  pages={381--388},
  year={2020},
  organization={IEEE}
}

License

CGRA-Flow is offered under the terms of the Open Source Initiative BSD 3-Clause License. More information about this license can be found here:

• http://choosealicense.com/licenses/bsd-3-clause
• http://opensource.org/licenses/BSD-3-Clause

OpenAI GPT (coming soon)

Arch Wizard.