Join our two-day workshop, “Moving your AI training jobs to LUMI,” designed to familiarize you with the capabilities of the LUMI supercomputer for artificial intelligence applications. This workshop is ideal for those looking to transition from smaller-scale computing environments like laptops, workstations, or cloud VMs to the robust, GPU-intensive LUMI platform.
Participants are invited to bring their own AI training scripts to the workshop, where they will receive personalized support to adapt and run them on LUMI’s advanced GPU system. Whether you aim to leverage a single GPU or scale up to multiple GPUs, our workshop will provide valuable insights and practical skills to enhance your AI projects with LUMI’s powerful computing infrastructure.
Event Info
Dates: 25.– 26. November 2026
Time: 9:00 – 17:00 EET each day (final schedule TBD)
Location: University of Latvia, Riga
Organizer: LUMI User Support Team (LUST)
Hybrid Course
For those unable to attend in person, we are pleased to offer the option to join the lectures online.
While the interactive hands-on exercises and personalized support for implementing your own workflows will be exclusive to in-person attendees, remote participants will still benefit from the comprehensive lectures streamed live from the workshop.
Requirements
Participants are expected to have basic experience with:
- Working on a Linux command line
- Using Python and one or more of the Python AI frameworks PyTorch, Tensorflow, or JAX
- Training an AI model on at least a single GPU, e.g. using a laptop, workstation, or cloud service
- Managing Python environments, e.g. using the Conda and/or pip package managers
Participants are expected to bring an own laptop to the workshop, including a charger.
Learning outcomes
Attending the workshop, you will acquire an understanding of the LUMI-G architecture tailored for AI training, including an introduction to SLURM, ROCm, the Lustre/LUMI-O file systems, and the Slingshot 11 interconnect. Specifically, you will:
- Learn to utilize existing AI containers on LUMI and build your own using the container build tool, cotainer
- Learn to distribute AI workloads across multiple GPUs within a single LUMI-G node
- Explore strategies for scaling AI workloads across numerous GPUs distributed over several LUMI-G nodes
- Gain insight into advanced topics for optimizing AI training processes on the LUMI supercomputer
Agenda
The workshop consists of a mix of short lectures and hands-on exercises, that cover the following key topics:
- LUMI-G architecture overview and its applications in AI
Introduction to the LUMI web-interface for development and monitoring - Using the AI framework PyTorch on LUMI
- Building and deploying custom AI containers on LUMI
- Strategies for scaling AI workloads across multiple GPUs
- Get support to adapt and run your own AI training script on LUMI
Registration
Deadline: 29. October 2026, at 23:59 EET
Register for the Workshop:
Please register by the deadline to secure your place. Spaces are limited and available on a first-come, first-served basis. Participation in the workshop is free of charge and includes coffee/tea/water and a few snacks during the days. Please be prepared to cover your own lunch costs.
All details regarding the training venue, the final schedule, and how to join the LUMI project for this workshop will be provided shortly after the deadline. If your plans change, we kindly ask you to cancel your registration as soon as possible, ideally before the registration deadline. The email acknowledging your registration will contain a link to manage it.
Users who do not have an account on LUMI yet will receive temporary access for the purpose of the course. The allocated compute time should only be used for the course exercises. Any abuse will result in removal from the allocation for this and future courses.
Venue
The event will take place in University of Latvia in Riga. Precise instructions will follow with training preparatory information. Participants are responsible for arranging their own travel and accommodations.