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Setup Deep Learning Environment
on Ubuntu 16.04
SEUNGWOO LEE
01. System Information
Memory
Processor
Graphic Processor
64 Bit (x86_64)
Disc Storage, SSD
02. Install Ubuntu 16.04
● It’ll Based on Ubuntu 16.04 64­Bit
– All Environments are Containerized Using Docker (also 
nvidia­docker will help using dedicated Graphics 
Processor Unit)
– For Example, You can use Dockerized Tensorflow image 
for Train & Serve
● & There are Several types of tensorflow images
● https://hub.docker.com/r/tensorflow/tensorflow/tags/
● Install using USB Flash Driver
03. Install NVIDIA Driver
● Unfortuneately, NVIDIA Drivers are SHIT
● First, You should download CUDA Driver on Link 
BELOW
● https://developer.nvidia.com/cuda­downloads
● Select distribution and click “Download” Button
● (I prefer download local deb archive to increase 
download time)
03. Install NVIDIA Driver
● (All Commands are based on “Base Installer”)
● First, Go to downloaded directory (using cd, ls, etc)
● Second, Using dpkg to decompress deb archive
– `sudo dpkg ­i cuda­repo­ubuntu1604­9­1­local_9.1.85­1_amd64.deb`
● Third, Watch Terminal and Copy and paste String Like this
– `sudo apt­key add /var/cuda­repo­<version>/7fa2af80.pub`
– DO NOT COPY & PASTE On this Slide, You Should Copy and 
Paste On TERMINAL
03. Install NVIDIA Driver
● Fourth, Update APT using
– `sudo apt­get update`
● Fifth, Install CUDA using APT
– `sudo apt­get install cuda`
– It’ll Remove Old NVIDIA and Install Newer Driver
● Lastly, Reboot Computer
– After Reboot, Type `nvidia­smi` on Terminal to check 
graphics card’s Driver are Successfully Installed
04. Install Docker
Please Follow instructions on
https://docs.docker.com/install/linux/docker­ce/ubuntu/
#install­docker­ce­1
05. Install nvidia­docker
Please Follow Instructions on
https://github.com/NVIDIA/nvidia­docker
How To Setup NVIDIA CUDA Drvier on Ubuntu

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