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Singularity

Singularity is an alternative way to run containers, often with the purpose of scientific computing on HPCs. Whereas Docker excels at microservices i.e. small and single-application containers with a single TCP port open to the public, Singularity aims to provide reproducible results embedded in a container image available to the public. Because of that, several details such as image tagging and even image format differ between Singularity and Docker (with a conversion tool available). Additionally, Singularity has a different mode of operation which does not require superuser privileges, therefore it is more suitable to be installed on HPCs. It also has a native support for MPI and GPGPU calculations.

Availability

Singularity is installed on Marconi HPC and available there after executing: module load singularity

Instructions to install Singularity are available in the documentation.

Exercises

Start Singularity container

1. Search for Ubuntu image: singularity search ubuntu
2. Download latest image: singularity pull library://library/default/ubuntu
3. Notice that the image is in fact a file downloaded to your local directory: ls -l ubuntu_latest.sif
4. Run the image: ./ubuntu_latest.sif
5. Notice that you are mapped to the same user as in the host machine, run whoami and id
6. Notice that you are seeing your own $HOME directory from the container: ls -l
7. Check what system are you currently running: cat /etc/os-release

uDocker

uDocker was created in H2020 project INDIGO-DataCloud. It uses Docker images natively, but provides a userspace tool to run and manage containers. Because it does not require superuser privileges, it is also a good fit as a container tool to be used in HPCs. uDocker also supports MPI calculations and provides ways to access host's GPU. 

IMAS image