SimpleCGRA: An Open-Source Platform for Temporal-Mapping CGRAs

We are still tidying the codes of SimpleCGRA. The codes of all modules are available. We will keep improving SimpleCGRA. Note that there exist various repos named SimpleCGRA due to some historical reasons. Recently, it is maintained in shelljane/SimpleCGRA.

• Most modules of SimpleCGRA are written in Python. We test SimpleCGRA on anaconda and python 3.7.

• Install the dependencies:

conda create -n scip python=3.7
conda activate scip
conda install matplotlib scikit-learn networkx xmltodict scip graphviz pyscipopt cvxpy -c conda-forge
pip install graphviz

• Run the benchmark

export SET=express
export BENCH=cosine2
python3 ./test/pnr.py ./benchmark/${SET}/${BENCH}/${BENCH}_DFG.txt ./benchmark/${SET}/${BENCH}/${BENCH}_compat.txt \
        -p ./benchmark/${SET}/${BENCH}/${BENCH}_param.txt 

• The default mapping parameters will be used if ./test/pnr.py is run without "-p xxx_param.txt ".

• Compilation is optional. It is needed if you want to use the front-end or use the C++ interface.

• You can compile SimpleCGRA by running "make". The front-end is tested in LLVM 11.

• arch/: code about CGRA modeling
• benchmark/: CGRA-ME/ExPRESS/standard benchmarks
• common/: provides basic functions
• dataflow/: code about dataflow modeling
• mapping/: code about CGRA mapping (scheduling, placement, routing)
• test/: code about experiments

• test/pnr.py: CGRA mapping
• test/dse.py: design space exploration
• test/dfgpart.py: dataflow graph partition