HPC Primer - 2 (inc. RDM for HPC workflows)
Part 1: Git for HPC workflows (10:00 - 12:00)
Who is this for?
The HPC Primer sessions were specially designed to give supercomputing newcomers a running start. Users who will need to augment their research with supercomputing are encouraged to attend these sessions.
What will you learn?
- Understanding the basics of ssh, connections & keys safely
- Using a version control system (git) on a supercomputer
- Fundamentals of Research Data Management (RDM) applied to supercomputing
Why is this important?
Most users are familiar with personal computers/laptops, where most interaction is direct and with a mouse. However, newcomers to supercomputing/HPC are often met with a rather steep learning curve because the remote system operates very differently. Therefore this training session will help users quickly get up to speed and avoid costly mistakes (with or without LLMs).
How is the session structured?
A mixture of instructor led demonstrations, individual hands-on exercises and optional challenges in small groups. You are in no way required to present or say anything if you are not comfortable with that.
Prerequisite
There is no skill prerequisite for this session. Please bring your laptop.
Part 2: Research Data Managament (RDM) for HPC workflows (12:30 - 14:00)
Who is this for?
This workshop is designed for researchers who generate, analyze, or manage research data in HPC environments.
What will you learn?
You will learn how to evaluate the organization and documentation of your research data, and identify practical actions to improve both. Through guided exercises and discussions, you will assess your current practices and develop a realistic plan for enhancing the quality and sustainability of your research outputs.
Why is this important?
Well-organized and documented research data makes it easier to reproduce results, collaborate with colleagues, comply with funder and institutional requirements, and enable future reuse of data and workflows by others or yourself. In research conducted in HPC environments, where results often depend on complex computational environments, good documentation is essential for ensuring that valuable research outputs remain understandable and usable over time.
How is the session structured?
The workshop combines a short introduction with hands-on self-assessment, peer discussions, and consultation with research data management experts. Most of the session is dedicated to working on your own project dataset, exchanging experiences with other researchers, identifying gaps in your current practices, and creating a concrete action plan for improvement.
Prerequisite
There is no skill prerequisite for this session. Please bring your laptop. Participants are encouraged to bring an active project and use the session to reflect on and improve their own data organization and documentation practices. Dummy/synthetic datasets will also be provided if you do not have data available to bring.