The one-slide lecture

• Some software packages on the CSC supercomputers are installed as containers
  • May cause some changes to usage
  • See the instructions in Docs CSC for each software for details
• Containers provide an easy way to install software
  • A single-command installation if a suitable Docker or Apptainer/Singularity container exists

Containers

• Containers are a way of packaging software and their dependencies (libraries, etc.)
• Popular container engines include Docker, Apptainer (previously called Singularity), Shifter, Podman etc
• Apptainer is most popular in HPC environments

Containers vs. virtual machines (1/2)

Containers vs. virtual machines (2/2)

• Virtual machines can run a totally different OS than the host computer (e.g. Windows on a Linux host or vice versa)
• Containers share the kernel with the host, but they can have their own libraries
  • They can run, e.g., a different Linux distribution than the host

Benefits of containers: Ease of installation

• Containers are becoming a popular way of distributing software
  • A single-command installation from existing image
  • More portable since all dependencies are included
• Limited root privileges inside the container if the build system supports it
  • Package managers (yum, apt, etc.) can be utilized even when not available on the target system.
  • Some containers need full root access in to build

Benefits of containers: Environment isolation

• Containers use the host system kernel, but they can have their own bins/libs layer
  • Can be a different Linux distribution than the host
  • Can solve some incompatibilities
  • Less likely to be affected by changes in the host system

Benefits of containers: Enviroment reproducibility

• Environment can be saved as a whole
  • Useful with, e.g., Python, where updating underlying packages (NumPy, etc.) can lead to differences in the behavior
    
• Sharing with collaborators is easy (a single file)

Apptainer in a nutshell

• Containers can be run with user-level rights
  • But: building new containers requires root access or support for --fakeroot option
• Minimal performance overhead
• Supports MPI
  • Requires containers tailored to the host system
• Can use host driver stack (Nvidia/CUDA)
  • Add option --nv
• Can import and run Docker containers
  • Running Docker directly would require root privileges

Apptainer on CSC supercomputers

• Apptainer jobs should be run as batch jobs or with sinteractive
• No need to load a module
• Users can run their own containers
• Some CSC software installations are provided as containers (e.g. Python environments)
  • See the software pages in Docs CSC for details

Running Apptainer containers: Basic syntax

• Execute a command in the container
  • apptainer exec [exec options...] <container> <command>
• Run the default action (runscript) of the container
  • Defined when the container is built
  • apptainer run [run options...] <container>
• Open a shell in the container
  • apptainer shell [shell options...] <container>

File system

• Containers have their own internal file system (FS)
  • The internal FS is always read-only when executed with user-level rights
• To access host directories, they need to be mapped to container directories
  • E.g., to map the host directory /scratch/project_2001234 to the /data directory inside the container: --bind /scratch/project_2001234:/data
  • The target directory inside the container does not need to exist, it is created if necessary
  • More than one directory can be mapped

Environment variables

• Most environment variables from the host are inherited by the container
  • Can be prevented if necessary by adding the option --cleanenv
• Environment variables can be set specifically inside the container by setting on the host $APPTAINERENV_variablename.
  • E.g., to set $TEST in a container, set $APPTAINERENV_TEST on the host

apptainer_wrapper

• Running containers with apptainer_wrapper takes care of the most common --bind commands automatically
• You just need to set the $SING_IMAGE environment variable to point to the correct Apptainer image file

export SING_IMAGE=/path/to/container.sif
apptainer_wrapper exec myprog <options>

• Additional options can be set with variable $SING_FLAGS, e.g. export SING_FLAGS=--nv

Using Docker containers with Apptainer

• You can build an Apptainer container from a Docker container with normal user rights:
  • apptainer build <image> docker://<address>:<tag>
• For example:
  • apptainer build pytorch_19.10-py3.sif docker://nvcr.io/nvidia/pytorch:19.10-py3
• More information in our documentation:
  • Running Apptainer containers
  • Creating Apptainer containers
  • Using Tykky to create Apptainer containers
  • Apptainer containers on LUMI

Apptainer containers as an installation method

• Apptainer is a good option in cases where the installation is otherwise problematic:
  • Complex installations with many dependencies/files
  • Obsolete dependencies incompatible with the native environment
    • Still needs to be kernel-compatible
  • Image is a single file

Just a random example (FASTX-toolkit)

• Tested installation methods:
  • Native: 47 files, total size 1.9 MB
    • Needed changes to source code to compile
  • Conda: 27464 files, total size 1.1 GB
  • Apptainer: 1 file, total size 339 MB

Methods of building a new Apptainer container

• Building using Tykky)
• Building from a definition (aka recipe) file
• Building in “sandbox” mode

Building using Tykky

• Especially suited for Conda environments
  • Can take an environment YAML file as an input
• Can be used for any application type
  • Use --post-install <file>to run the installation commands
  • See example

Building using a definition file

• Provides transparency
  • Everybody can see what commands were used to build the container
• Definition files reusable
  • Updating the software typically only requires minor changes to the file
• Can be a bit cumbersome if you have to try many things (e.g. installing missing libraries)

Building using sandbox mode

• container created as a directory structure instead of an image file
• Installation done interactively
  • Easier to test different options
• A production image needs to be built for general use
• Resulting image is a “black box”
  • No record left of installation commands used