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Shipping containers have frequently been used as an analogy for computing containers because the container is generic, it does not care what is put inside, and it will be carried on any ship, or in the case of computing containers can run on many systems unlike the one it was created on.  Hence the log for Docker, the most common container platform.

Docker is widely used by researchers for reasons we won't get into here.  See their documentation

Singularity Overview


Singularity containers let users run applications in a Linux environment of their choosing.  This is similar to but not the same as Docker.   

The most important thing to know is that you create the singularity container called an image on a workstation where you have root privileges, and then transfer the image to HPC where you can execute the image. If root authority is an issue then the answer might be a virtual environment on your laptop, like Vagrant for MacOS

For an overview and more detailed information refer to:
http://singularity.lbl.gov

Here are some of the use cases we support using Singularity:

  • You already use Docker and want to run your jobs on HPC
  • You want to preserve your environment so that a system change will not affect your work
  • You need newer or different libraries than are offered on HPC systems
  • Someone else developed the workflow using a different version of linux
  • You prefer to use something other than Red Hat / CentOS, like Ubuntu 

Singularity Tutorials

There are some tutorials located here


Singularity Python and Machine Learning

More tutorials

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