Gcloud: Jupyter Notebook with GPUs from browser

GPUjupyter.txt

###### Gcloud: Jupyter Notebook with GPUs from browser

## First Step Install GCP 16.04 LTS with 20GB and Tesla K80 NVIDIA GPU and HTTP/HTTPS

## From Remote shell (*need to run twice after generating keys). Can also use SSH with default user
gcloud compute --project <project name> ssh --zone "us-central1-a" <gce name>

## Install Anaconda and setup path
# Required upfront: Installs nano / curl / bzip2 / etc.
sudo -s
sudo apt-get update 
mkdir Downloads
cd Downloads
wget "https://repo.continuum.io/archive/Anaconda3-5.0.1-Linux-x86_64.sh" -O "Anaconda3-5.0.1-Linux-x86_64.sh"
chmod +x Anaconda3-5.0.1-Linux-x86_64.sh
sudo sh "Anaconda3-5.0.1-Linux-x86_64.sh" -b
cd $HOME
rm -r Downloads
echo 'export PATH=$PATH:$HOME/anaconda3/bin' >> ~/.bashrc
source ~/.bashrc


## Install Cuda from NVIDIA
curl -O http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
sudo dpkg -i ./cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
rm -r cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
sudo apt-get update
sudo apt-get -y install cuda-8.0
# 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 ${CUDNN_TAR_FILE}
rm -r cudnn-8.0-linux-x64-v6.0.tgz
mkdir -p /usr/local/cuda/include/
mkdir -p /usr/local/cuda/lib64/
sudo cp -P cuda/include/cudnn.h /usr/local/cuda/include
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64/
sudo chmod a+r /usr/local/cuda/lib64/libcudnn*
# Paths
echo 'export CUDA_HOME=/usr/local/cuda' >> ~/.bashrc
echo 'export PATH=$PATH:$CUDA_HOME/bin' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=$CUDA_HOME/lib64' >> ~/.bashrc
source ~/.bashrc
# Shows Cuda / GPU Info
nvidia-smi


## Create Conda Environment with Tensorflow
sudo apt-get update
conda create --name tf_gpu tensorflow-gpu -y
source activate tf_gpu

	## Python
	from tensorflow.python.client import device_lib
	device_lib.list_local_devices()
	
## Configure Notebook
# .jupyter edit
# https://towardsdatascience.com/running-jupyter-notebook-in-google-cloud-platform-in-15-min-61e16da34d52
mkdir .jupyter
cd .jupyter/
pip install --upgrade jupyter
jupyter notebook --generate-config
nano jupyter_notebook_config.py
	
	# Add to jupyter_notebook_config.py
	c = get_config()
	c.NotebookApp.ip =  '*'
	c.NotebookApp.open_browser = False
	c.NotebookApp.port = 5000
	
	## To kill processes on open ports if needed
	sudo netstat -tlnp

	# Active Internet connections (only servers)
	# Proto Recv-Q Send-Q Local Address           Foreign Address         State       PID/Program name
	# tcp        0      0 0.0.0.0:5000            0.0.0.0:*               LISTEN      4216/python
	# tcp        0      0 0.0.0.0:22              0.0.0.0:*               LISTEN      1593/sshd
	# tcp6       0      0 :::5000                 :::*                    LISTEN      4216/python
	# tcp6       0      0 :::22                   :::*                    LISTEN      1593/sshd

	kill 4216



##
cd # Get back to home directory
jupyter-notebook --port=5000 --allow-root --no-browser

# To view jupyter notebook -- after setting static ip on External IP tab
# Copy paste token from output along with external ip to log into jupyter notebook
<External IP>:5000<Token Address>
# source deactivate tf_gpu