High-Performance Computing Center Stuttgart

The Gray Scott HPC Summer School

Master high-performance computing on CPUs and GPUs while simulating the elegant complexity of the Gray-Scott reaction.

The summer school will cover optimisation of computations on different types of hardware (CPU, GPU), presenting their respective characteristics, architectures and bottlenecks. It will cover generic optimization methods applicable to all types of hardware, as well as the various libraries, technologies and languages available to achieve the best possible performance. Ideally, the peak performance of the machine.

This event will be offered in a satellite site format, with HLRS (Stuttgart, Germany) serving as one of the official satellite locations. A satellite site refers to a geographically separate venue connected to the main training hub at LAPP (Annecy, France), allowing participants to join the program without traveling to the primary location.

Participants attending the course at HLRS will benefit from an on-site environment with local teaching assistance available to support them throughout the training. This setup offers opportunities for in-person interaction, hands-on guidance, and collaboration with peers, while staying fully connected via videoconference to the main tutors/speakers in Annecy.

The school is co-organised by HLRS and LAPP (Annecy Particle Physics Laboratory) for SIDE and CC-FR, all National Competence Centres for High-Performance Computing.

Location

HLRS, University of Stuttgart
Nobelstraße 19
70569 Stuttgart, Germany
Room 0.439 / Rühle Saal
Location and nearby accommodations

Start date

Jun 22, 2026
13:45

End date

Jul 02, 2026
18:15

Language

English

Entry level

Basic

Intermediate

Course subject areas

Parallel Programming

Programming Languages for Scientific Computing

Topics

C/C++

Fortran

GPU Programming

Numerical Methods

Python

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Prerequisites and content levels

Prerequisites
  • Basic experience with either C++, Fortran or Python programming
Content levels
  • Basic: 28 hours
  • Intermediate: 11 hours
  • Advanced: 10.5 hours

Learn more about course curricula and content levels.

Learning outcomes

The school will cover the optimization of computations on different types of hardware (CPU, GPU), presenting their respective characteristics, architectures and bottlenecks. It will cover generic optimization methods applicable to all types of hardware, as well as the various libraries, technologies and languages available to achieve the best possible performance. Ideally, the peak performance of the machine.

  • Hardware: CPU, GPU
  • Languages considered: C++17 and newer, Fortran, Python, Julia
  • Libraries considered: SYCL, Eve, Numpy, cunumerics,  Jax, Thrust, cuPy, and PyTorch
  • Compilers considered: G++, Clang++, nvc++, gfortran, nvfortran, icpx.
  • Profiling tools: Valgrind, Maqao, Perf, NSight, Malt and NumaProf

All the methods will be illustrated on simple examples, such as Hadamard products, reductions, barycentre calculations and matrix products, in order to be applied to a single problem: the simulation of a Gray Scott reaction.

This problem is simple enough to be understood quickly and complex enough for compilers to have difficulties optimizing it without help. Each method will be broken down into a simple version, using default options, and one or more advanced versions, which will allow their advantages and disadvantages to be discussed and quantified.

Agenda

See https://cta-lapp.pages.in2p3.fr/COURS/GRAY_SCOTT_REVOLUTIONS/GrayScott2026/2-1132.html.

Note that there is also a series of webinars scheduled on Thursdays. Those are a great opportunity to familiarise yourself with the topic. You can register for the Gray Scott Thursdays or watch recordings at CC-FR's Youtube Channel: https://youtube.com/playlist?list=PLiZttWgOMudb6PsUoWtxY3G4Gv8f2lurG&si=7zTEPiz1Fs1lCNmY.

HLRS concept for on-site courses

Besides the content of the training itself, another important aspect of this event is the scientific exchange among the participants. We try to facilitate such communication by

  • offering common coffee and lunch breaks and
  • working together in groups of two during the exercises. Laptops wil be provided.

Registration information

Apply for this course via the button at the top of this page (will be available soon).

Registration closes on June 19, 2026.

Fees

This course is offered free of charge for participants from Europe and EuroCC countries. For lists of EU and EuroCC countries have a look at the Horizon Europe and EuroCC website.

Only participants from these countries can take part in this course.

Contact

Tobias Haas phone 0711 685 87223, training(at)hlrs.de

HLRS training collaborations in HPC and AI

HLRS is part of the Gauss Centre for Supercomputing (GCS), together with JSC in Jülich and LRZ in Garching near Munich. EuroCC@GCS is the German National Competence Centre (NCC) for High-Performance Computing. HLRS is also a member of the Baden-Württemberg initiative bwHPC. Since 2025, HLRS coordinates HammerHAI

This course is provided within the framework of EuroCC2.

Acknowledgements

Within the scope of the EuroCC3 project this training is offered free of charge. By participating in a training free of charge, companies receive state-aid corresponding to the regular market-prices listed in the service portfolio. Please note state-aid regulations in Germany.

EuroCC 2 and EuroCC4SEE have received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101101903 and No 101191697. The JU receives support from the European Union’s Digital Europe Programme and Germany, Bulgaria, Austria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, France, Netherlands, Belgium, Luxembourg, Slovakia, Norway, Türkiye, Republic of North Macedonia, Iceland, Montenegro, Serbia, Bosnia and Herzegovina.

Further courses and training team

See the training overview and the Supercomputing Academy pages.
See also information about the HLRS training department and staff.

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