nvidia-gpu-cloud-with-titannvidia-gpu-cloud-with-titan

This is my notes after 6-7 installs.

Once the server is set up the promise of a 5 minute install holds true, but you still need to know the basics of using Docker.

Ubunutu Setup:

• Following with:

• http://docs.nvidia.com/ngc/ngc-titan-setup-guide/index.html

• Burn 16.04.3 Desktop AMD64 Aug 2017 ISO to DVD

• or create a flash USB: "Startup Disk Creator" in Ubuntu Desktop

• (They really should state the exact ISO to pull.)

• http://releases.ubuntu.com/16.04/

• Don’t check the boxes for “download updates or install third party software”

• Force UEFI Installation:click “Go Back”

• “Erase Disk and install Ubuntu”: Install Now

• On first start up make sure 4.10 kernel is running by typing:

• uname -a

• you might have to edit grub to get 4.10 kernel to boot:

•  sudo gedit /etc/default/grub
  

•   sudo update-grub
  

• Follow the directions at:

• http://docs.nvidia.com/ngc/ngc-titan-setup-guide/index.html

• Make script files by copying out of Firefox(Chrome copies wrong)

• I keeping having to run second script more than once. If so:

• Remove reboot at end to make sure the second script works

• You might have to run manually:

• sudo rm /etc/apt/sources.list.d/cuda.list

• sudo apt-key add /var/nvidia-driver-local-repo-387.34/7fa2af80.pub

• Then run the second script again, then reboot.

• Run the 3rd and forth scripts.

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Software to install on local machines:

• sudo apt-get install libxss1 libappindicator1 libindicator7
• wget https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb
• sudo dpkg -i google-chrome*.deb
• sudo apt-get install openssh-server
• sudo apt-get install terminator
• download PyCharm Community to ~/pycharm https://www.jetbrains.com/pycharm/download/download-thanks.html?platform=linux&code=PCC
• samba: https://help.ubuntu.com/community/How%20to%20Create%20a%20Network%20Share%20Via%20Samba%20Via%20CLI%20%28Command-line%20interface/Linux%20Terminal%29%20-%20Uncomplicated,%20Simple%20and%20Brief%20Way!
• sudo apt-get install vnc4server
• Setup Desktop Sharing:
• • Search for “Desktop Sharing”:
• • Change the settings
• • Yes: “Allow other users to take control”
• • No: Confirm each access
• • Yes: Set Password
• • No: Automatically Configure ports

Using Nvidia GPU Cloud with Titan Usage:

• sudo mkdir /workspace
• cd /workspace
• sudo mkdir jobs
• cd jobs
• login(you need to paste in your key):
• docker login -u '$oauthtoken' --password-stdin nvcr.io <<< 'Qt4M2VkL---------Your API KEY -------3ZGZZmNIw'
• docker pull nvcr.io/nvidia/digits:18.04
• nvidia-docker run -it --rm --net=host --name digits -v /data:/data -v /digits-jobs:/workspace/jobs nvcr.io/nvidia/digits:18.04
• In a new terminal open a shell inside the workspace:
• docker exec -it digits /bin/bash
• The base directory for the frameworks(caffe/tensorflow/digits/etc) inside the container:
• cd /opt/ | ls
• To show the binaries the container has:
• cd/usr/local/bin

Other setup :

• Git clone required git repos
• Move common shell scripts to: /~ and /workspace/jobs/

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Docker tasks for myself

• Write a script to start a container on system startup

Links for myself:

• https://ngc.nvidia.com
• http://docs.nvidia.com/ngc/ngc-user-guide/index.html
• https://github.com/NVIDIA/nvidia-docker/wiki/
• https://hub.docker.com/r/nvidia/
• https://github.com/NVIDIA/nvidia-docker/wiki/Third-party

Useful Docker commands

• start the docker Daemon: sudo dockerd
• List containers:
• sudo docker ps
• Shell into container:
• sudo docker exec -it digits /bin/bash
• Use the ID from “docker ps” or name the container when you run it.