Monthly HPC Café and Beginner’s Introduction

Monthly HPC Café and Beginner’s Introduction

Monthly HPC Café

The HPC Café complements our established contact channels and training offerings. Every second Tuesday of the month at 4:00 p.m., this is an opportunity to get to know each other.

We always start with a short Q&A session, where you can ask and discuss anything HPC related, from running job scripts to performance issues.  Starting at 4:30 p.m., we focus on a specific topic, either as a short talk or a discussion. These can include, e.g., advanced usage, workflow optimizations, or application-specific issues.

The HPC Café is also an informal platform to give feedback or talk about general requests. We look forward to meeting you and hope for lively participation.

If possible, the HPC Café will be held in hybrid mode; if you want to attend in person, free coffee and cake awaits!

Next HPC Café: Tuesday, May 12, 2026 at 4:00 p.m.
Focus topic: FAU’s services for research data management
Speaker: Dr. Marcus Walther, FAU Competence Center Research Data and Information (FAU CDI)
Location: RRZE, Martensstr. 1, Seminar Room 2.049 and online via Zoom: https://go-nhr.de/hpc-cafe
Contact address for inquiries: hpc-support@fau.de

More upcoming HPC Café events:

June 9, 2026: Agentic Coding Assistants: An Introduction and Field Report (Dr. Jan Eitzinger and Aditya Ujeniya, NHR@FAU)

July 14, 2026: The Blue Swan AI Gigafactory: A Bavarian Proposal (Prof. Dieter Kranzlmüller, LRZ Garching)

Beginner’s Introduction “HPC in a nutshell”

Each month, the two days after the HPC Café are specifically dedicated to new users and HPC beginners.

On Wednesday NHR@FAU offers a one-hour General Introduction (online) on using the HPC systems, including an overview of HPC clusters, how to connect to the systems, how to use the batch system, and more. This well-received format aims at reducing the entry barrier for new and inexperienced users. The content is continuously updated to reflect recent changes in NHR@FAU systems and access rules.

A one-hour Introduction for AI Users (online) on Thursday is aimed at newcomers who plan to run AI workloads on the NHR@FAU systems. The following topics are planned: File handling for AI workloads, fast storage options, setting up python environments for AI, setting up containers with Apptainer.

Next introduction for beginners (online):

It is highly recommended to visit the general introduction as a preparation for the introduction for AI users.

Location (Zoom): https://go-nhr.de/hpc-in-a-nutshell

In need of AI resources? Take a look at BayernKI, the central infrastructure of the State of Bavaria to advance academic AI research.

Slides and recordings from past HPC Café events:

  • December 14: Python beyond the basics: Numpy, Scipy, Matplotlib  –  GitHub repository with notebook and examples  –  Video recording at FAU.tv
  • November 9: Effective Editing With Vim  –  Slides  –  Video recording at FAU.tv  –  Video recording at YouTube
  • October 19: HowTo on using the Cx services based on the RRZE gitlab instances  –  Slides  –  Additional slides  –  Video recording
  • September 14: General Q&A, some advice on using (and not misusing) the file systems, current state of NHR system installation
  • August 10: summer break; only the usual introduction for beginners
  • July 13: Current status NHR@FAU resources and KONWIHR projects  –  Slides NHR@FAU  –  Slides KONWIHR
  • June 8: Build systems and “Make”  –  Video recording  –  Slides
  • May 11: “Continuous x” (Cx) for HPC Systems (guest talk by Jennifer Buchmüller and Terry Cojean, KIT)  –  Video recording
  • April 13: Julia in HPC (guest talk by Valentin Churavy, MIT CSAIL Julia Lab, MIT)  –  Video recording
  • March 9: Git part 2: advanced features and workflows  –  Slides  –  Video recording
  • February 9: Git: basics, common workflows, and tips and tricks  –  Slides  –  Video recording
  • January 12: Focus topic: AI-assisted research at FAU  –  Four FAU researchers give short talks about how their projects benefit from Artificial Intelligence (AI) methods and what resources they require for it.
    • Changes to expect for TinyGPU in 2021 and other news  –  Slides
    • Peter Uhrig: “HPC workflows for big data and machine learning applications”
    • Benedikt Lorch: “Deep learning in the HPC environment Computing demands for research in multimedia forensics”
    • Harald Köstler: “Deep learning for Computational Fluid Dynamics”
    • Thorsten Glüsenkamp: “AI research in astroparticle physics at ECAP”