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 18.04 LTS' from 'OS images'.

Basics

1. Update & upgrade System

   sudo apt-get update 
   sudo apt-get upgrade
   

2. Install essentials like gcc compiler, git e.t.c.

   sudo apt-get install build-essential
   sudo apt-get install git zip unzip
   

CUDA and cuDNN

1. Install CUDA 10.1

   wget https://developer.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.105-418.39_1.0-1_amd64.deb
   sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.105-418.39_1.0-1_amd64.deb
   sudo apt-key add /var/cuda-repo-ubuntu1804-10-1-local-10.1.105-418.39/7fa2af80.pub
   sudo apt-get update
   sudo apt-get install cuda
   echo 'export PATH=/usr/local/cuda-10.1/bin${PATH:+:${PATH}}' >> ~/.bashrc 
   echo 'export LD_LIBRARY_PATH=/usr/local/cuda-10.1/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}' >> ~/.bashrc 
   source ~/.bashrc
   

2. Install cuDNN v7.6.5 for CUDA 10.1

   Download cuDNN v7.6.5 from NVIDIA as in Local Setup. Note that this time you are installing cuDNN on virtual machine instance with Linux.

   gcloud compute scp [LOCAL_FILE_PATH] ecbm4040@your-instance-name:
   cp cudnn-10.1-linux-x64-v7.6.5.32.solitairetheme8 cudnn-10.1-linux-x64-v7.6.5.32.tgz
   tar xvf cudnn-10.1-linux-x64-v7.6.5.32.tgz
   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.

Anaconda and other packages

1. Download Anaconda

   https://repo.anaconda.com/archive/Anaconda3-2020.02-Windows-x86_64.exe
   

2. Install Anaconda

   bash https://repo.anaconda.com/archive/Anaconda3-2020.02-Windows-x86_64.exe
   source ~/.bashrc
   

3. Create your own virtual environment in Anaconda with Python 3.7

   conda create -n envTF22 python=3.7
   

4. Activate the virtual environment.

   conda activate envTF22
   

5. Install basic packages.

   conda install pandas numpy scipy pillow matplotlib scikit-learn
   conda install -c conda-forge jupyterlab 
   

Tensorflow

1. Use conda to install tensorflow-gpu.

   conda install tensorflow-gpu==2.2
   

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

Now you can proceed to Step 3 in GCP Setup.