- Using OSG Provided Singularity Images
- Using Custom Singularity Images
- Frequently Asked Questions / Common Issues
Docker and Singularity are container systems that allow users full control over their environment. You can create your own container image (a blueprint for the running container) which your job will execute within, or choose from a set of pre-defined images.
For jobs on OSG, it does not matter whether you provide a Docker or Singularity image. Either is compatible with our system and can be used with little to no modification. This is of course highly dependent on your workload. Please feel free to contact us at firstname.lastname@example.org if you have any questions.
Using OSG Provided Singularity Images
The Open Science Grid user support team maintains a small set of images, hosted in a distributed file system called CVMFS. These images contain a basic set of tools and libraries. These include:
|EL 8||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-el8:latest||GitHub||A basic Enterprise Linux (CentOS) 8 based image.|
|EL 7||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-el7:latest||GitHub||A basic Enterprise Linux (CentOS) 7 based image.|
|EL 6||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-el6:latest||GitHub||A basic Enterprise Linux (CentOS) 6 based image. This is currently our default image|
|Ubuntu 20.04 (Focal)||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-ubuntu-20.04:latest||GitHub||A good image if you prefer Ubuntu over EL flavors|
|Ubuntu 18.04 (Bionic)||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-ubuntu-18.04:latest||GitHub||A good image if you prefer Ubuntu over EL flavors|
|Ubuntu 16.04 (Xenial)||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-ubuntu-xenial:latest||GitHub||A good image if you prefer Ubuntu over EL flavors|
|EL 7 CUDA 10||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-el7-cuda10:latest||GitHub||EL 7 based CUDA 10 base image|
|TensorFlow GPU||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/tensorflow-gpu:latest||GitHub||Used for running TensorFlow jobs on OSG GPU resources|
|TensorFlow||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/tensorflow:latest||GitHub||Base on the TensorFlow base image, with a few OSG package added|
|R||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-r:latest||GitHub||Example on how to build your on R image|
|Julia||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-julia:latest||GitHub||Example on how to build your on Julia image|
|GROMACS||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-gromacs:latest||GitHub||GROMACS base image|
|GROMACS GPU||/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-gromacs-gpu:latest||GitHub||GROMACS GPU base image|
You can indicate that your job should use one of these images by making the following changes to your submit file:
Requirements = HAS_SINGULARITY == TRUEwill trigger the scripts that load a Singularity image from CVMFS and run your job inside.
+SingularityImagewill tell the job which Singularity image to use for the job. If you don't include this option, your job will use a default OSG Singularity image (currently EL 6).
For example, this is what a submit file might look like to run your job under EL7:
universe = vanilla executable = job.sh Requirements = HAS_SINGULARITY == TRUE +SingularityImage = "/cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-el7:latest" output = out error = err log = log queue
Using Custom Singularity Images
OSG Connect provides tooling for users to create, publish and load custom images. This is useful if your job requires some very specific software setup. The general process goes like this:
- Create your own custom container image using Docker and push it to Docker Hub.
- Add your Docker image to the Open Science Grid image repository.
- Use the container image in jobs.
We will expand on each of these steps below.
Creating a Container
If you want to use an container image you have created yourself, the image should be defined as a Docker image and published in Docker Hub. The reason we use Docker as a source image repository is that it allows us to easily import the images into our own distribution system (see below).
See this page for how to create a Docker image on your own computer and push it to Docker Hub so it can be used by the Open Science Grid.
When creating the Docker image, you will give it with an
identifier with this format:
This identifier will be used both to submit the Docker container to
the Open Science Grid repository and to run jobs.
Submitting your Docker Container to the Open Science Grid Repository
Once your Docker image has been published on Docker Hub, it needs to be
submitted to the CVMFS image repository (
which also hosts the OSG-provided default images.
To get your images included, please create a git pull request with the container
docker_images.txt in the
and we can help you.
Once your submission has been accepted, it will be automatically converted to a Singularity image and pushed to the CVMFS Singularity repository. Note: some common Dockerfile features, like ENV and ENTRYPOINT, are ignored when the Docker image is converted to a Singularity image. See our the "Special Cases" section of our how to guide for more details of how to deal with this.
Once your container has been added to CVMFS, if you update your original Docker image, new versions pushed to Docker Hub will automatically be detected and the version on the OSG (in the CVMFS filesystem) will be updated accordingly.
Using Your Container
To use your container to run jobs, you will follow the same steps as above (under "Using OSG
Provided Singularity Images"), but will change the
+SingularityImage option to
include your container identifier, like so:
+SingularityImage = "/cvmfs/singularity.opensciencegrid.org/namespace/repository_name"
For example, if my Docker Hub username was
alice and I created a container called
ncbi-blast, my submit file might look like this:
universe = vanilla executable = job.sh Requirements = HAS_SINGULARITY == TRUE +SingularityImage = "/cvmfs/singularity.opensciencegrid.org/alice/ncbi-blast" output = out error = err log = log queue
Frequently Asked Questions / Common Issues
I already have a Singularity container, not a Docker one
Email the OSG Connect team: email@example.com
FATAL: kernel too old
If you get a FATAL: kernel too old error, it means that the glibc version in the image is too new for the kernel on the host. You can work around this problem by specifying the minimum host kernel. For example, if you want to run the Ubuntu 18.04 image, specfy a minimum host kernel of 3.10.0, formatted as 31000 (major * 10000 + minor * 100 + patch):
Requirements = HAS_SINGULARITY == True && OSG_HOST_KERNEL_VERSION >= 31000
Exploring Images on the Submit Host
Images can be explored interactively on the submit hosts by starting it in "shell" mode. The recommended command line, similar to how containers are started for jobs, is:
singularity shell \ --home $PWD:/srv \ --pwd /srv \ --bind /cvmfs \ --scratch /var/tmp \ --scratch /tmp \ --contain --ipc --pid \ /cvmfs/singularity.opensciencegrid.org/opensciencegrid/osgvo-ubuntu-xenial:latest
For more information about Docker, please see:
and Singularity, please see:
Singularity has become the preferred containerization method in scientific computing. The following talk describes Singularity for scientific computing:
This page was updated on Oct 28, 2020 at 17:22 from start/software/singularity-containers.md.