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Characterisation-Virtual-Laboratory / CharacterisationVL-Software

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CharacterisationVL-Software

The purpose of this repository is for storing definition files to submit to our internal application build and deployment system.

If you are new to Singularity containers, please refer to https://sylabs.io/guides/3.5/user-guide/ or a newer version of this documentation.

Each software package is located in its own folder. The files are tagged with the software name and version number or date of build. Please read below for the naming convention.

To add software to the repository you will need to create a new branch. The new branch is the name of the software product. By convention, the new branch will be checked and merged into the master branch and then deleted.

Steps to add a software package

  1. Clone this repository
  2. Create a branch 
    $ git branch <software name>
  3. Make a subdirectory for the software product. 
    $ mkdir <software name>
  4. Add all the necessary files.
  5. Commit all changes, including a helpful message 
    $ git commit -m "<software name> added as requested in support ticket"
  6. Push to the remote repository. i.e. this one.
  7. Submit merge request

Naming your Singularity definition file, Singularity Hub and Licensing

For all Singularity recipes where the software licensing permits redistribution, please use this naming convention:

   Singularity.applicationName_version
   Singularity.applicationName_version-cuda-cudaVersion

There is a Github action between this repository and a container builder VM hosted on Nectar. When a commit is merged into the master branch, this VM will build the container.

If successfully built, the container will be added to a repository that is downloadable from CVL nodes.

An example on how to handle this situation is the recipe for CCP-EM. The README.md contains a section on Prerequisites. This section lists the required files to build the container. The license must be accepted by the end user to obtain them.

Prerequisite files should not be committed to this repository.

Ubuntu Base Images

The folder 'ubuntu-base-image' contains recipes for pre built base containers. These can be used as a starting point to aid/speed up the development of your container recipe.

The current versions are built using Ubuntu 18.04 LTS, plus Cuda 9 or Cuda 10.1 if required.

For example: from the Graphviz Singularity.graphviz-2.40.1 recipe

Bootstrap: shub
From:      Characterisation-Virtual-Laboratory/CharacterisationVL-Software:1804

These two lines, will tell Singularity to use the 'shub' bootstrap to obtain the '1804' ubuntu-base-image container from Singularity Hub.

From here you just need to add the requirements to build a container for your required piece of software. Please see Singularity.graphviz-2.40.1 for the full recipe.

The current ubuntu-base-images include Python, VirtualGL and TurboVNC plus Cuda if indicated in the name.

Running GUI applications on a non-GPU node

The applications in the Singularity container should run without the need for a dedicated GPU.

However, an X server needs to be running for this to work. On nodes with GPU, X Server is started with NVIDIA driver, and on non-GPU nodes, the X Server is started with MESA library.

X Server can be started during boot (for example, using systemctl set-default graphical.target).

Make sure that VirtualGL package is installed in the container. The code below will download and install VirtualGL.

wget https://swift.rc.nectar.org.au/v1/AUTH_810/CVL-Singularity-External-Files/virtualgl_2.6.2_amd64.deb

dpkg -i virtualgl_2.6.2_amd64.deb