Tuesday, October 21, 10am-12pm

Machine learning workflows often involve complex software environments with numerous dependencies, making them challenging to manage, reproduce, and scale. Containerization technologies like Apptainer are powerful tools for addressing these challenges, especially when working in High-Performance Computing (HPC) environments.

This RC Short Course is designed to introduce researchers to containerized machine learning on CURC systems using Apptainer. Participants will gain practical, hands-on experience running pre-built containers (e.g., TensorFlow, PyTorch). The session will also demonstrate how to integrate containerized workflows into SLURM job submissions for scalable computing.

This session is intended for users with basic understanding of programming and some familiarity with Linux command-line environment. Participants should have a Research Computing Account prior to the start of the training if they wish to try hands-on examples.

What is an RC Short Course? A training that provides an in-depth understanding of a concept, system, or tool. You can expect to leave a "Short Course" with a solid grasp of the topic.