Singularity

Installed versions

Resource	Version
Dardel/cpe23.03	4.1.1

General information

Singularity

Instructions for using singularity at PDC

Singularity enables users to have full control of their environment. Singularity containers can be used to package entire scientific workflows, software and libraries, and even data. This means that you don’t have to ask your cluster admin to install anything for you - you can put it in a Singularity container and run. Did you already invest in Docker? The Singularity software can import your Docker images without having Docker installed or being a superuser. Need to share your code? Put it in a Singularity container and your collaborator won’t have to go through the pain of installing missing dependencies. Do you need to run a different operating system entirely? You can “swap out” the operating system on your host for a different one within a Singularity container. As the user, you are in control of the extent to which your container interacts with its host. There can be seamless integration, or little to no communication at all.

More information about singularity can be found at https://docs.sylabs.io/guides/latest/user-guide/

Security

Singularity is more secure on a HPC than other similar solutions like docker or shifter. Read a comparison about them at http://geekyap.blogspot.se/2016/11/docker-vs-singularity-vs-shifter-in-hpc.html

important to remember is that if you download images they should be trusted since any container you run will have full access tor your account and your data.

The same goes for images you build yourself that they are built upon trusted images.

Performance

Executing software in containers is very efficient as well as you create a sandbox of all applications that you do need. Very little performance loss has been seen.

Installation of singularity

Singularity is installed as a nosuid on the cluster, meaning that you are unable to use singularity files, but are able to use singularity sandboxes instead. Otherwise there should be no difference. At PDC you cannot write within your containers while being logged in on the cluster. Operation for creating containers is better performed on your local computer.

How to use singularity on your local computer

How to install singularity

Singularity can be installed on your computer, with root access, so you can build your own images. Installation instructions are available at… https://docs.sylabs.io/guides/latest/user-guide/quick_start.html#quick-installation-steps

Download images from singularity hub

You can find numerous images at https://singularity-hub.org/ Just download them directly to our file system and use them for your analysis. The build command in singularity, besides downloading the image, also converts the image to the latest singularity version.

singularity build --sandbox <sandbox name> shub://<name of image>

You can also use images from docker https://hub.docker.com

singularity build --sandbox <sandbox name> docker://<name of image>

Building your own images

Different Linux OS are available for you to download. At this time the best Ubuntu distribution is available as a docker image and can be downloaded

sudo singularity build --sandbox <sandbox name> docker://ubuntu:latest

Which will download this docker image and convert it into a sandbox.

Building your own image from recipes

You can also create an image using a recipe from our PDC github. Singularity recipes with MPI support are available at https://github.com/PDC-support/PDC-SoftwareStack/tree/master/other/singularity In order to create these

sudo singularity build --sandbox <sandbox name> <recipe name>

Here is a full example on how to create an image from one of our recipes.

wget https://raw.githubusercontent.com/PDC-support/PDC-SoftwareStack/master/other/singularity/ubuntu-mpich-full.def
sudo singularity build --sandbox ubuntu-full ubuntu-mpich-full.def

Test singularity

With this command you will automatically login into your singularity image shell.

singularity shell <sandbox name>

In the shell you can do the usual Linux shell commands.

Install software

So now that you do have a sandbox you can start by installing software in the image. By login into the writable sandbox you can use all the commands that are normal in the operating system, and your internetaccess is also available in the container, so you can use wget or other commands to download data and softwares. By default on a writable sandbox you login with the user root, therefore this should be executed on your personal computer where you have root access.

sudo singularity shell -w <sandbox name>

Read mode: You can read/write to file system outside container and read inside container.

write mode: You can read/write inside container. In write mode you are user ROOT, home folder: /root

Installing the essentials in your image

Although you have downloaded the latest OS, it still needs some basic software, compilers and libraries. This can either be installed using a recipe like explained above, or you can login into your image using write mode and install everything you need, for example updating a sandbox

sudo singularity shell -w ubuntu_sandbox
Singularity> apt-get install update
Singularity> exit

Copying data from local file system to singularity sandbox

You can copy data to your singularity sandbox in several ways. Either by adding your files into the /root folder in singularity, and then they will automatically be available in the /root folder in singularity.

sudo cp <your file> /root

You can also bind your folder in singularity. In order to do that you must bind a folder in singularity to your local file system. Also the folder in singularity must be created first. The following example…

creates a new folder in the sandbox
binds a local folder to that folder
logins into the container,
copies into your sandbox

sudo singularity exec -w ubuntu_write mkdir <singularity folder>
sudo singularity shell -B <local folder>:/root/<singularity folder> -w ubuntu_write/
Singularity> cp <singularity folder>/<files> .

Where to store runtime files

As the root folder you are login into when using a writable container is not available using exec from outside the container, if you plan to run software that you compiled yourself, you must put the executable somewhere that is accessible by PATH. /usr/local/bin is a good example. Installed software can then be executed by

singularity exec <sandbox name> <myexe>

You can also add a software path in the containers runscript which is a shell file which will be executed when you run the container. The runscript file should be stored in /.singularity.d/ folder The script is then executed using

singularity run <sandbox name>

Storing help

help documents on the image should be saved as runscript.help in the folder /.singularity.d This can then be read by

singularity run-help <sandbox name>

Saving your sandbox to PDC cluster

When you are ready installing all the software, paths, folders you need to transfer your sandbox to the cluster. To achieve this, it is advisable to first compress it and then transfer it.

sudo tar czf <sandbox name>.tar.gz <sandbox name>
scp <sandbox name>.tar.gz <username>@dardel.pdc.kth.se:/cfs/klemming/home/<u>/<username>
# On Dardel
tar xfp <sandbox name>.tar.gz

Another possibility is to transfer a .SIF file to Dardel and convert it to a sandbox with the build command

scp <name>.sif <username>@dardel.pdc.kth.se:/cfs/klemming/home/<u>/<username>
# On Dardel
singularity build --sandbox <sandbox name> <name>.sif

Do remember that you do need OpenMPI to execute your software in parallel on HPC systems. We provide images with OpenMPI installed in the PDC Hub, but you can also build your own.

How to remote build a singularity image on the cluster

Instead of running singularity on your local computer as a mean to create a singularity sandbox, you can instead use the remote build function with a singularity recipy. Examples of recipies are available at https://github.com/PDC-support/PDC-SoftwareStack/tree/master/other/singularity In the description below we use the free service from sylabs for creating sandboxes at PDC.

Create a sylabs account

In order to be able to get access to the remote building facility you need to create a free account at https://cloud.sylabs.io/builder

Create sylabs token

Login into sylabs https://cloud.sylabs.io/builder
Press USERNAME -> Access tokens
Enter a name for your token and press Create Access Token
Copy or download the token.

Adding an access token to the cluster

First of all login to the PDC cluster and access the module singularity

ml PDC/<version>
ml singularity

After this run command

singularity remote login

The first time you run this command on the cluster, it will save your access token to your profile. Running the same command again will erase the old token and you can add a new one.

Remote build a container on the cluster

After having a valid token you can build your singularity sandbox remotely using the command…

singularity build --remote --sandbox <sandbox name> <recipe name>

Create a container at seqera

There are sites where you can build your own singularity container as you see fit by adding which software you would need and then download the actual singularity container. Using seqera you can choose which software you want to use, and then download a container created for this purpose.

Running singularity images at PDC

Singularity works on Dardel by loading the singularity module. There are however restrictions. As explained above you are not able to write into singularity container. You are however able to build singularity sandboxes from containers available online, but not from recipes.

singularity build --sandbox <sandbox name> docker://ubuntu:latest

Also, you are able to run, run-help, exec, shell, as well as other non-write commands, on singularity sandboxes at PDC.

Below are a couple of example on how to run a singularity container on PDC systems. As the Lustre filesystem is not recognised by default it is important to bind said filesystem, which is done in the example scripts below.

Ready made containers at PDC

PDC provides some default containers for testing and certain software which are placed at /pdc/software/sing_hub These can also be reached by invoking $PDC_SHUB

ls $PDC_SHUB

As highlighted before these containers are built as a sandbox and can be run with our clusters. In order to get information about what they contain please run

singularity run-help $PDC_SHUB/<sandbox name>

Recipes on how several of these container are bult is available at https://github.com/PDC-support/PDC-SoftwareStack/tree/master/other/singularity

Job scripts

Follow information on how to create Job scripts at this page, which is not covered below. Although here are a couple of examples on how to run jobs on the dardel cluster.

Batch job without MPI

In case you would like to run on one node you do not need MPI support in your image and you can send in a job using…

#! bin bash  l
# The  l above is required to get the full environment with modules
# Set the allocation to be charged for this job
# not required if you have set a default allocation
#SBATCH  A 201X X XX
# The name of the script is myjob
#SBATCH  J myjob
# Only 1 hour wall clock time will be given to this job
#SBATCH  t 1 00 00
# Number of nodes
#SBATCH   nodes=1
# Using the shared partition as we are not using all cores
#SBATCH  p shared
# Number of MPI processes per node
#SBATCH   ntasks per node=24
# Run the executable named myexe
ml PDC/<version> singularity
srun -n 24 singularity exec -B /cfs/klemming <sandbox folder> <myexe>

Batchjob with MPI

In case you need to parallelize your software across nodes you should use one of the recipes with Cray MPI support mentioned earlier which do reside in the https://github.com/PDC-support/PDC-SoftwareStack

#! bin bash  l
# The  l above is required to get the full environment with modules
# Set the allocation to be charged for this job
# not required if you have set a default allocation
#SBATCH  A 201X X XX
# The name of the script is myjob
#SBATCH  J myjob
# Only 1 hour wall clock time will be given to this job
#SBATCH  t 1 00 00
# Number of nodes
#SBATCH   nodes=2
# Using the shared partition as we are not using all cores
#SBATCH  p shared
# Number of MPI processes per node
#SBATCH   ntasks per node=12
# Run the executable named myexe
ml PDC/<version> singularity
srun -n 24 --mpi=pmi2 singularity exec -B /cfs/klemming <sandbox folder> <myexe>

Batch job with GPU support

In case you would like to run on one node with AMD GPUs. Be aware that you need a container with software compilated using GPU support. Look at our https://github.com/PDC-support/PDC-SoftwareStack for recipes on how to build. in your image and you can send in a job using…

#! bin bash  l
# The  l above is required to get the full environment with modules
# Set the allocation to be charged for this job
# not required if you have set a default allocation
#SBATCH  A 201X X XX
# The name of the script is myjob
#SBATCH  J myjob
# Only 1 hour wall clock time will be given to this job
#SBATCH  t 1 00 00
# Number of nodes
#SBATCH   nodes=1
# Using the GPU partition which is at the moment is under testing
#SBATCH  p gpu
# Run the executable named myexe
ml PDC/<version> singularity
srun -n 1 singularity exec --rocm -B /cfs/klemming <sandbox folder> <myexe>