0. The Project includes two parts:
   • GCNN/main_MultiChannelGCNN.py generate the computation for CFG of each program
   • CNN written in C for training the neural network. Compiler the CNN:
     • install CBLAS and BLAS
     • run sh CNN.sh
1. Prepare data
   • Generate CFG data for training, validation and testing.
     • run ASMCFG/ProcessData.py
     • make sure some parameters: "data_dir" - the directory containing assembly files, "dest_dir" - the directory for storing the CFG data, 'problems'- names of the datasets
2. Generate computations for CFGs
   • the common parameters for networks are in "gcnn_params.py"
   • run GCNN/main_MultiChannelGCNN.py
3. Training the network 8. run CNN setting.txt

Please cite our paper entiles "DGCNN: A convolutional neural network over large-scale labeled graphs" published in Neural Network 2018, if you used in your research.