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Singularity Containers

Some software packages may not be available for the version of Linux running on the HPC cluster. In this case, users may want to run containers. Containers are self-contained application execution environments that contain all necessary software to run an application or workflow, so users don’t need to worry about installing all the dependencies. There are many pre-built container images for scientific applications available for download and use.

Singularity https://sylabs.io/ is an application for running containers on an HPC cluster. Containers are self-contained application execution environments that contain all necessary software to run an application or workflow, so you don’t need to worry about installing all the dependencies. There are many pre-built container images for scientific applications available for download and use, see section Container Images.

Prerequisites

To run containers on Ceres, you’ll need to execute the singularity command from a compute node. For example, to run an interactive session on a compute node, use the SLURM salloc command:

[user.name@ceres ~]$ salloc
salloc: Granted job allocation 1695904
salloc: Waiting for resource configuration
salloc: Nodes ceres20-compute-44 are ready for job
export TMPDIR=/local/bgfs//1695904
export TMOUT=5400
[user.name@ceres20-compute-44 ]$ module load singularity
[user.name@ceres20-compute-44 ]$

NOTE: salloc by default runs on a single hyper-threaded core (2 logical cores) with 6000 MB of allocated memory on one of the compute nodes. The session will last for 2 days, but will timeout after 1.5 hours of inactivity (no commands runnning). See the Running Jobs User Guide for more info on how to request resources for interactive jobs.

Container Images

Singularity executes a container from a Singularity container image either created by the user or downloaded from Singularity Library https://cloud.sylabs.io/library, and can also import and execute Docker https://www.docker.com/ container images, either directly uploaded by the user, or downloaded from Docker Hub https://hub.docker.com/.

BioContainers is a “community-driven project that provides the infrastructure and basic guidelines to create, manage and distribute Bioinformatics [Docker] containers with special focus in Proteomics, Genomics, Transcriptomics and Metabolomics.”

BioContainers can be obtained either via docker https://hub.docker.com/u/biocontainers/ or via Quay https://quay.io/

For leveraging GPU using containers, Nvidia provides a container library NGC. https://ngc.nvidia.com/catalog/all

NGC offers a comprehensive catalog of GPU-accelerated software for deep learning, machine learning, and HPC. NGC containers deliver powerful and easy-to-deploy software proven to deliver the fastest results. By taking care of the plumbing, NGC enables users to focus on building lean models, producing optimal solutions and gathering faster insights.

Docker Images

While Singularity can only execute containers from Singularity images, it can easily import Docker images directly from Docker Hub to create a Singularity image. For example, to download a Docker image of the R programming language from Docker Hub [https://hub.docker.com//r-base/](https://hub.docker.com//r-base/) and import it into a Singularity image, change the docker pull rbase command listed at the aforementioned URL to the equivalent Singularity command singularity pull docker://r-base (where specifying “docker://” before the image name lets Singularity know the image is a Docker image, and by default fetch the image from Docker Hub):

[user.name@sceres20-compute-44 ~]$ singularity pull docker://r-base
INFO:    Converting OCI blobs to SIF format
INFO:    Starting build...
Getting image source signatures
Copying blob 1fcd5305bc72 done
 ...
INFO:    Creating SIF file...
INFO:    Build complete: r-base_latest.sif

The resulting singularity image (r-base.img) contains a complete environment (operating system, libraries, R installation) for running R. A tag may be specified when selecting the Docker image to download; e.g., a list of tags for r-base is at: https://hub.docker.com/r/library/r-base/tags/. To specify a specific tag, append “:TAG” to the image name (e.g., singularity pull docker://r-base:3.3.3 ). If the tag is omitted, Singularity will look for an image labeled with the “latest” tag (note that the “latest” tag is merely a Docker Hub convention, and is not guaranteed to exist, nor is it guaranteed to point to the latest image—when in doubt, specify the tag).

Note on Home directory and Singularity

While pulling/building the containers, pay attention to the home directory as the cached image blobs will be saved in ${HOME}/.singularity . Since the home directory has a limited amount of space, this can fill up quite easily. Users can change where the files will be cached by setting SINGULARITY_CACHEDIR and SINGULARITY_TMPDIR environment variables. On Ceres we set SINGULARITY_TMPDIR to $TMPDIR. We also set SINGULARITY_CACHEDIR to $TMPDIR for all Slurm jobs if it’s not set by the user. As of January 13, 2022, these variables are not automatically set on Atlas. We recommend adding the following two commands to the job scripts that use singularity:

export SINGULARITY_CACHEDIR=$TMPDIR 
export SINGULARITY_TMPDIR=$TMPDIR

One can also use –disable-cache option to avoid saving cached image blobs (e.g., singularity pull --disable-cache docker://r-base:3.3.3 ).

In case the home directory is full, it is safe to delete the contents of ~/.singularity folder.

Singularity Images

Singularity Library

Singularity Library is a service that builds Singularity images from community-provided recipes (called “bootstrap files”) stored in GitHub repositories and makes them available for search and download. To download a singularity image, search the Singularity Library container collections, and follow the instructions to download and execute the container. This is similar to the directions for container images from Docker Hub, except replace the “docker://” URI prefix with “library://”.

Creating Your Own Singularity Images

Root access is needed to create a Singularity image from a bootstrap file. As Ceres users do not have root access, to create your own Singularity image, you can paste the bootstrap file to Singualrity cloud builder https://cloud.sylabs.io/builder.

Bootstrap examples - https://github.com/sylabs/singularity/tree/master/examples

Executing Containers

Three commands may be used to execute applications inside Singularity containers:

singularity run,

singularity exec,

and (less commonly) singularity shell

Note that applications executing within a container do not have access to applications installed outside of the container (e.g., environment modules, or executables installed in /usr/bin on the compute node).

singularity run

Singularity images may have a run script (Docker: ENTRYPOINT) that is executed when the singularity run command is used. To see the run script defined by the container (if any), use the singularity inspect command:

[user.name@ceres20-compute-44 ~]$ singularity inspect --runscript r-base.img
#!/bin/sh
exec R "$@"

The output above shows that in the aforementioned Docker image for the R programming language retrieved from Docker Hub, singularity run r-base.img will run R interactively in the container environment. Your home directory is automatically mounted in the container, so any files therein can be accessed (and R packages installed within the container, as illustrated in the example below):

[user.name@ceres20-compute-44 ~]$ singularity run r-base.img
R version 3.4.0 (2017-04-21) -- "You Stupid Darkness"
Copyright (C) 2017 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
...
> install.packages("stringr")
Installing package into '/usr/local/lib/R/site-library'
(as 'lib' is unspecified)
Warning in install.packages("stringr") :
'lib = "/usr/local/lib/R/site-library"' is not writable
Would you like to use a personal library instead? (y/n) y
Would you like to create a personal library
/home/user.name/R/x86_64-pc-linux-gnu-library/3.4
to install packages into? (y/n) y
trying URL 'https://cran.rstudio.com/src/contrib/stringr_1.2.0.tar.gz'
Content type 'application/x-gzip' length 94095 bytes (91 KB)
==================================================
downloaded 91 KB
* installing *source* package 'stringr' ...
...
* DONE (stringr)
The downloaded source packages are in
'/tmp/RtmpwP5YNn/downloaded_packages'
> library(stringr)
>

singularity exec

A container image can contain many executables / scripts. The singularity exec command can be used to select which program to run in the container. For example, to run a simple R script using the Rscript command in the container, prefix the Rscript command with singularity exec r-base.img:

[user.name@ceres20-compute-44 ~]$ cat test.R
summary(c(1:10))
[user.name@ceres20-compute-44 ~]$ singularity exec r-base.img Rscript test.R
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.00 3.25 5.50 5.50 7.75 10.00

singularity shell

singularity shell starts an interactive shell within the container image, allowing you to inspect files (and execute programs) within the container. For example, here we see that the r-base.img container image was created using Debian Linux as the base operating system:

[user.name@ceres20-compute-44 ~]$ type R
bash: type: R: not found
[user.name@ceres20-compute-44 ~]$ singularity shell r-base.img
Singularity: Invoking an interactive shell within container...
Singularity r-base.img:~> type R
R is /usr/bin/R
Singularity r-base.img:~> cat /etc/os-release
PRETTY_NAME="Debian GNU/Linux 9 (stretch)"
NAME="Debian GNU/Linux"
VERSION_ID="9"
VERSION="9 (stretch)"
ID=debian
HOME_URL="https://www.debian.org/"
SUPPORT_URL="https://www.debian.org/support"
BUG_REPORT_URL="https://bugs.debian.org/"
Singularity r-base.img:~> exit
exit
[user.name@ceres20-compute-44 ~]$

Ceres Container Repository

There are some containers locally available on Ceres at /reference/containers

These are available via modules, so the user doesn’t have to perform any additional tasks.

List of containers (may be out of date, ls /reference/containers on Ceres for the most up to date info):

  • RStudio
  • agbase_interproscan
  • antismash
  • bamm_groopm_checkm_refinem
  • bigscape
  • braker
  • cDNA_cupcake
  • cactus
  • cnvnator
  • combine_gafs
  • concoct
  • dastool
  • envi-jupyter
  • faststructure
  • funannotate
  • gatk
  • goanna
  • intarna
  • itasser
  • jupyter_notebook
  • kobas
  • metawrap
  • minimac4
  • nanopolish
  • nanopolish_500kbp
  • opendronemap
  • pb_assembly
  • plasflow
  • python36
  • qiime
  • qiime2
  • redundans
  • revbayes
  • rgi
  • roary
  • salmon
  • salsa
  • toil_vg
  • trinityrnaseq

Support

The SCINet Virtual Research Support Core (VRSC) can provide support for the Singularity application itself, but has no control over the contents of and cannot be expected to support container images.

Questions about application-specific container images may be directed to the SCINet community via the SCINet Forum (must have a SCINet account to access), or to the community responsible for maintaining the container image.