Apptainer at TACC

Steve Lantz and Zilu Wang
Cornell Center for Advanced Computing

4/2026 (original)

This topic describes how to extend the capabilities of a single container by accessing one or more GPUs from it, and how to launch multiple containers so they work in parallel using MPI. It also covers how to set up a Python environment in a container so that it includes packages that you need to have installed, and how to use that Python environment as the kernel for a Jupyter notebook.
Objectives

After you complete this topic, you should be able to:

  • Access one or more of the host's GPUs from an Apptainer container
  • Launch multiple containers so they work in parallel using MPI
  • Describe the hybrid and bind models of running containerized applications with MPI
  • Set up a Python environment in a container to include packages that you need
  • Use a containerized Python environment as the kernel for a Jupyter notebook
Prerequisites

This topic covers basic information on containers and Apptainer usage through the command line interface. Some familiarity with Linux is preferred, but it is not necessary.

 
©  |   Cornell University    |   Center for Advanced Computing    |   Copyright Statement    |   Access Statement
CVW material development is supported by NSF OAC awards 1854828, 2321040, 2323116 (UT Austin) and 2005506 (Indiana University)