Install CUDA 9.2, cuDNN 7.2.1, Anaconda and PyTorch on Ubuntu 16.04.
# tested on AWS p2.xlarge August 29, 2018 | |
# install CUDA | |
sudo apt-get update && sudo apt-get install wget -y --no-install-recommends | |
CUDA_URL="https://developer.nvidia.com/compute/cuda/9.2/Prod2/local_installers/cuda-repo-ubuntu1604-9-2-local_9.2.148-1_amd64" | |
wget -c ${CUDA_URL} -O cuda.deb | |
sudo dpkg --install cuda.deb | |
sudo apt-key add /var/cuda-repo-9-2-local/7fa2af80.pub | |
sudo apt-get update | |
sudo apt-get install -y cuda | |
rm cuda.deb | |
CUDA_PATCH_URL="https://developer.nvidia.com/compute/cuda/9.2/Prod2/patches/1/cuda-repo-ubuntu1604-9-2-148-local-patch-1_1.0-1_amd64" | |
wget -c ${CUDA_PATCH_URL} -O cuda_patch.deb | |
sudo dpkg --install cuda_patch.deb | |
sudo apt-get upgrade -y cuda | |
rm cuda_patch.deb | |
# install cuDNN 7.2.1 | |
CUDNN_URL="http://developer.download.nvidia.com/compute/redist/cudnn/v7.2.1/cudnn-9.2-linux-x64-v7.2.1.38.tgz" | |
wget -c ${CUDNN_URL} -O cudnn.tgz | |
sudo tar -xzf cudnn.tgz -C /usr/local | |
rm cudnn.tgz | |
sudo ldconfig | |
# add variables to .profile | |
echo 'export CUDA_HOME=/usr/local/cuda' >> ~/.profile | |
echo 'export PATH=${CUDA_HOME}/bin:${PATH}' >> ~/.profile | |
echo 'export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:$LD_LIBRARY_PATH' >> ~/.profile | |
# install conda | |
wget -c "https://repo.anaconda.com/archive/Anaconda3-5.2.0-Linux-x86_64.sh" -O conda.sh | |
bash conda.sh -b | |
rm conda.sh | |
echo 'export PATH=/home/ubuntu/anaconda3/bin:${PATH}' >> ~/.profile | |
# setup environment variables | |
source ~/.profile | |
# install pytorch | |
conda install -y pytorch torchvision cuda92 -c pytorch |
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Great!
But how to know which cudnn version is compatible with particular cuda version?