graphnn

Prerequisites

Tested under Ubuntu 14.04

Download and install cuda from https://developer.nvidia.com/cuda-toolkit

wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_7.5-18_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1404_7.5-18_amd64.deb
sudo apt-get update
sudo apt-get install cuda

in .bashrc, add the following path

export CUDA_HOME=/usr/local/cuda
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH

Download and install intel mkl

in .bashrc, add the following path

source {path_to_your_intel_root/name_of_parallel_tool_box}/bin/psxevars.sh
export MKL_ROOT={path_to_your_intel_root}/mkl

Install cppformat

check https://github.com/cppformat/cppformat for help

Install Spiral-wht

wget http://www.ece.cmu.edu/~spiral/software/spiral-wht-1.8.tgz
tar -zxvf spiral-wht-1.8.tgz
cd spiral-wht-1.8
./configure
make
make install

Build static library

make

Run example

Run mnist

cd examples/mnist
make
./run_exp.sh

Run graph classification

cd examples/graph_classification
make
./local_run.sh

The 5 datasets under the data/ folder are commonly used in graph kernel.