The CGRA-ME framework enables modeling, simulation, and optimization of Coarse-Grained Reconfigurable Arrays (CGRAs) for high-performance applications such as signal processing and machine learning. It provides flexibility in exploring different configurations to balance factors like power consumption, throughput, and scheduling. Gurobi, a powerful mathematical optimization solver, can be integrated with CGRA-ME to solve complex problems like task scheduling and resource allocation.
This guide will walk you through setting up Gurobi within CGRA-ME to optimize CGRA designs, enhancing performance and resource efficiency.
- Download CGRA-ME from the official site:
π CGRA-ME Download
- Get the appropriate Gurobi tar file for your operating system:
π Gurobi Downloads - This guide assumes Ubuntu as the target system.
tar -xvf gurobi<version>.tar.gz
- If you have an institutional email, you can get a Named-User Academic License from Gurobi.
- Note: The license key may expire after one day.
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Make sure CGRA-ME and Gurobi share the same parent directory to ensure smooth setup and integration:
π Parent_Directory/ βββ π CGRA-ME/ β βββ src/ β βββ bin/ β βββ examples/ β βββ Makefile βββ π gurobi702/ β βββ bin/ β βββ lib/ β βββ doc/ β βββ license/
Navigate to the bin subdirectory of the extracted Gurobi folder. Run the following command to activate Gurobi with your license key:
./grbgetkey <your-license-key>
Open your .bashrc file and add the following lines to set the Gurobi environment:
export GUROBI_HOME="$HOME/gurobi[your_version]"
export PATH="${PATH}:${GUROBI_HOME}/bin"
export LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:${GUROBI_HOME}/lib"
Replace [your_version] with the specific version of Gurobi you're using. Save and apply the changes:
source ~/.bashrc
Navigate to the CGRA-ME directory and run:
make
If you encounter an error about Gurobi not found, check and update the paths in .bashrc.
If you are running CGRA-ME inside a Docker container, remember to commit and push your changes to avoid losing them:
docker commit <container_id> <image_name>
docker push <image_name>
You have successfully integrated Gurobi with CGRA-ME. You can now take advantage of Gurobi's optimization strength to boost CGRA design efficiency!