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Tutorials & Courses

Erlangen National High Performance Computing Center (NHR@FAU) offers a wide range of HPC-related courses, covering topics such as modern C++, parallel programming, GPU programming, performance engineering, and domain-specific applications like molecular dynamics simulations.

We regularly present our flagship events Core–Level Performance Engineering and Node-Level Performance Engineering at leading conferences such as SC and ISC, as well as at high-performance computing centers. Many of our courses are conducted in collaboration with educators from Leibniz Supercomputing Centre (LRZ), High Performance Computing Center Stuttgart (HLRS), Vienna Scientific Cluster (VSC) at TU Wien, and NHR@TUD/ZIH at TU Dresden. Several of our GPU programming courses are offered in partnership with the Nvidia Deep Learning Institute (DLI), and we regularly contribute workshops to the European Master For High Performance Computing (EUMaster4HPC) program.

Upon request, we also conduct customized course sessions for interested computing centers, research institutions, and industry partners. Feel free to reach out to our head of training Sebastian Kuckuk, the NHR@FAU training team, or send a general inquiry to hpc-support@fau.de. For answers to common questions, visit our training FAQ page.

New users of the NHR@FAU computing resources are also encouraged to attend our beginner’s introduction “HPC in a nutshell” – offered monthly and online as a one-hour general introduction and as an additional one-hour introduction for AI users.

If you are an FAU student, we also encourage you to explore the curricular courses offered by the Professorship of High Performance Computing.

Upcoming Events

The same upcoming events, grouped by topic area:

NHR@FAU Course Portfolio by Topic

The performance engineering courses at NHR@FAU cover node-level hardware analysis and optimization in depth, using established tools and performance models. Topics range from microarchitecture fundamentals and cache behavior to solver-level performance analysis, and are frequently taught in collaboration with performance engineering experts from partnering institutions. For details, a full list of courses, and upcoming events, check the performance engineering courses overview page.

NHR@FAU offers the NVIDIA Deep Learning Institute (DLI) foundational deep learning course, covering computer vision, natural language processing, and pre-trained model usage. The course is delivered by certified NVIDIA DLI ambassadors from NHR@FAU. For details, a full list of courses, and upcoming events, check the artificial intelligence courses overview page.

NHR@FAU offers a broad range of GPU programming courses, from first-contact introductions to CUDA and high-level programming models all the way to advanced multi-GPU scaling and performance engineering with NVIDIA’s profiling tools. Courses are developed and maintained by NHR@FAU staff and regularly updated to reflect current hardware and software. For details, a full list of courses, and upcoming events, check the gpu programming courses overview page.

The parallel programming curriculum covers the dominant paradigms used in HPC: message passing with MPI, shared-memory threading with OpenMP, and hybrid MPI+X approaches. Courses range from introductory single-model workshops to the intensive multi-day PPHPS event, which covers multiple programming models and HPC system architecture in depth. For details, a full list of courses, and upcoming events, check the parallel programming courses overview page.

NHR@FAU’s software engineering courses help HPC practitioners write clean, correct, and maintainable code. Topics include modern C++ programming from beginner to advanced design patterns, and practical version control with Git – skills that underpin all serious software development work in scientific computing. For details, a full list of courses, and upcoming events, check the programming and software engineering courses overview page.

The molecular dynamics courses at NHR@FAU introduce widely used simulation packages – GROMACS and AMBER – and cover setup, execution, and analysis workflows on HPC clusters. These courses support researchers in structural biology, computational chemistry, and related fields who use NHR@FAU resources for their simulations. For details, a full list of courses, and upcoming events, check the molecular dynamics courses overview page.

Past Events

Our Trainers and Collaborators

We sincerely thank all our trainers and collaborators for their valuable contributions to our courses, trainings, and events. The lists below are ordered alphabetically.

HLRS

LRZ

  • Allalen, Momme
  • Azizi, Sajjad
  • Weinberg, Volker

NHR@KIT

  • Tuteja, Keshvi

TU Delft

TU Dresden

TU München

TU Wien (VSC, ASC)