GCP from Scratch

Contents

• Create Your Instance
• Basics
• CUDA and cuDNN
• Miniconda and other packages
• Tensorflow

Create Your Instance

1. Please follow GCP Setup instructions to 'select image' part.
2. In boot disk, instead of custom image, select 'Ubuntu 16.04 LTS' from 'OS images'.

Basics

1. Update & upgrade System

   sudo apt-get update 
   sudo apt-get upgrade
   

2. Install python 3.6, pip, gcc, etc.

   sudo add-apt-repository ppa:deadsnakes/ppa
   sudo apt-get update
   sudo apt-get install python3.6
   wget https://bootstrap.pypa.io/get-pip.py
   sudo python3.6 get-pip.py
   sudo apt-get install build-essential
   sudo apt-get install git zip unzip
   

3. Verify GPU, Linux version, kernel headers and development packages

   lspci | grep -i nvidia
   uname -m && cat /etc/*release
   uname -r
   sudo apt-get install linux-headers-$(uname -r)
   

CUDA and cuDNN

1. Install CUDA 9.0

   wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb
   mv cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64.deb
   sudo dpkg -i cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64.deb
   sudo apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub
   sudo apt-get update
   sudo apt-get install cuda
   echo 'export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}' >> ~/.bashrc
   echo 'export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}' >> ~/.bashrc
   source ~/.bashrc
   

2. Install cuDNN v7.0.5

   Download cuDNN v7.0.5 from NVIDIA as in Local Setup

   gcloud compute scp [LOCAL_FILE_PATH] ecbm4040@your-instance-name:~/
   tar xvf cudnn-9.0-linux-x64-v7.tar
   sudo cp cuda/include/cudnn.h /usr/local/cuda/include
   sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
   sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
   

3. Check CUDA installation. You can use "nvcc -V" to check the version of CUDA toolkits. And "nvidia smi" can help you check availble GPU device.

Miniconda and other packages

1. Download Miniconda

   wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
   

2. Install Miniconda

   bash Miniconda3-latest-Linux-x86_64.sh
   source ~/.bashrc
   

3. Create your own virtual environment in Miniconda

   conda create -n dlenv
   

4. Activate the virtual environment.

   source activate dlenv
   

5. Install baisc packages.

   conda install pandas numpy scipy pillow matplotlib scikit-learn
   conda install jupyter notebook
   

Tensorflow

1. Use pip to install tensorflow-gpu.

   pip install tensorflow-gpu
   

2. Open python and try to run a simple tensorflow function.

Now you can proceed to Step 3 in GCP Setup.