The Gray Scott HPC Summer School

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 optimisation 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.

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.

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

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.