Created
June 12, 2018 12:01
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Install CUDA v8.0, cuDNN v6.0, Anaconda, and PyTorch GPU on Ubuntu 16.04
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| #!/bin/bash | |
| CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb" | |
| wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG} | |
| sudo dpkg -i ${CUDA_REPO_PKG} | |
| sudo apt-get update | |
| sudo apt-get -y install cuda-8-0 | |
| #nvidia-smi | |
| echo 'export PATH=$PATH:$CUDA_HOME/bin' >> ~/.bashrc | |
| echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_HOME/lib64' >> ~/.bashrc | |
| source ~/.bashrc | |
| # install cuDNN v6.0 | |
| CUDNN_TAR_FILE="cudnn-8.0-linux-x64-v6.0.tgz" | |
| wget http://developer.download.nvidia.com/compute/redist/cudnn/v6.0/${CUDNN_TAR_FILE} | |
| tar -xzvf ${CUDNN_TAR_FILE} | |
| sudo cp -P cuda/include/cudnn.h /usr/local/cuda-8.0/include | |
| sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-8.0/lib64/ | |
| sudo chmod a+r /usr/local/cuda-8.0/lib64/libcudnn* | |
| # install conda | |
| wget https://repo.anaconda.com/archive/Anaconda3-5.2.0-Linux-x86_64.sh | |
| bash Anaconda3-5.2.0-Linux-x86_64.sh | |
| # yes yes yes | |
| source ~/.bashrc | |
| # install PyTorch | |
| conda install pytorch torchvision -c pytorch |
for Keras GPU
conda install -c anaconda keras-gpu
conda install -c conda-forge jupyterlab
jupyter notebook --generate-config
jupyter notebook password
jupyter lab --ip=0.0.0.0 --port=8000 --no-browser &
from keras import backend as K
config = tf.ConfigProto()
config.gpu_options.allow_growth=True
sess = tf.Session(config=config)
K.set_session(sess)
watch -d -n 2 nvidia-smi
sudo ss -lptn 'sport = :8888'
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for the jupyter notebook:
jupyter notebook --ip=0.0.0.0 --port=8000 --no-browser &