Getting started with Tensorflow-GPU on Ubuntu 18.04 LTS

D@rklord

This post is a step-by-step guide to installing Tensorflow -GPU on Ubuntu 18.04 LTS (bionic).

MY SYSTEM SPECIFICATIONS:
OS : Ubuntu 18.04 LTS, 64 bit (i7, 8th Gen processor)
GeForce GTX 1050 Ti GPU with 4GB RAM

I would like to keep the process and post as short as possible so that, the process can be followed easily by anyone and everyone!

STEPS FOR INSTALLING

  1. The First step in the process is to get the right Nvidia Display drivers.
    I figured out that Nvidia-390 is the most stable for me, though nvidia-440 was latest driver for my system.
  2. Purge all preinstalled nvidia drivers, use the following commands to install the drivers.
    $ sudo apt-get purge nvidia*   
    $ sudo add-apt-repository ppa:graphics-drivers/ppa
    $ sudo apt-get update
    $ sudo apt-get install nvidia-driver-390 nvidia-settings
    $ sudo reboot
    Now check $ nvidia-smi. If this works then Nvidia Display Driver was installed correctly.
  3. Navigate https://developer.nvidia.com/cuda-toolkit  and download CUDA toolkit 9.0.
  4. Navigate to the folder where CUDA toolkit was downloaded and open the terminal.
    Use following commands to install CUDA.
    $ sudo chmod +x cuda_9.0.176_384.81_linux.run
    $ ./cuda_9.0.176_384.81_linux.run – – override
    ‘- -overide’ is used to ignore the gcc compiler check during the installation.
  5. say yes to installing with an unsupported configuration
    no to “Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 384.81?
    Yes to cuda install (now complete the whole installation)
    Yes to toolkit location
    Yes to symbolic link
    Yes to cuda samples
  6. Next, head to https://developer.nvidia.com/cudnn  to get CUDNN 7.0.5
    Download  “cuDNN v7.0.5 Library for Linux”.
    $ tar -zxvf cudnn-9.0-linux-x64-v7.tgz
    $ sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-9.0/lib64/
    $ sudo cp  cuda/include/cudnn*.h /usr/local/cuda-9.0/include/
    $ sudo chmod a+r /usr/local/cuda-9.0/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
  7. Now finally we need to install LIBCUPTI.
    $ sudo apt-get install libcupti-dev
  8. Now open “bashrc” file to add path of Cuda
     Add these following lines to the end of bashrc file
  9. export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}
    • export LD_LIBRARY_PATH=/usr/local/cuda/lib64:${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
  10. REBOOT the system
  11. Finally install Tensorflow-GPU $ pip install –upgrade tensorflow-gpu==1.12.0 
    this is specifically for CUDA 9.0 and cuDNN 7.0.5

You are good to go now!!
Try running any simple program!

  • nvidia-smi -l 1 gives the gpu running update every 1 sec interval

Install version 6 0f gcc as CUDA requires gcc 6.

(installing gcc version 6, and making symbolic link)

$ sudo apt install nvidia-cuda-toolkit gcc-6
sudo ln -s /usr/bin/gcc-6 /usr/local/cuda-9.2/bin/gcc
sudo ln -s /usr/bin/g++-6 /usr/local/cuda-9.2/bin/g++

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