GPU Programming Part 2: Special and Advanced Topics
This advanced course will cover special and advanced aspects of GPU architectures and programming. Examples of increasing complexity are used to demonstrate the optimisation and tuning of scientific applications.
Praktische info:
Inschrijven?
- Voorwaarden: Some knowledge about Linux, e.g. make, command line editor, Linux shell, experience in C/C++ is also required.
- Prijs: Free
A personal institutional email address (university/research institution, government agency, organisation, or company) is required to register for JSC training courses. If you don't have an institutional email address, please get in touch with the contact person for this course.
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Leertraject
The course consists of modules providing more in-depth coverage of multi-GPU programming, modern CUDA concepts, CUDA Fortran, and portable programming models such as OpenACC and C++ parallel STL algorithms:
A) Advanced multi-GPU programming with MPI
B) Advanced multi-GPU programming with NVIDIA Collective Communications Library (NCCL) and NVIDIA Shared Memory (NVSHMEM)
C) Advanced and modern CUDA concepts (Cooperative Groups, CUB Primitives, modern C++ programming)
D) CUDA Fortran and GPU-accelerated standard Fortran or Kokkos for portable GPU programming
E) GPU programming with abstractions (OpenACC, Standard Language Programming (pSTL))
Attendees are invited to pick and choose the parts of the advanced course (A - E) they want to attend. The modules are mostly freestanding.
Note: If you want to learn the basics of GPU programming, there is a separate course GPU Programming Part 1: Foundation. It includes an introduction to GPU/parallel computing, programming with CUDA, GPU libraries, tools for debugging and profiling, and performance optimisations. It will take place 24.03.-26.03.2026 on-site at JSC. Please visit GPU Programming Part 1: Foundations for more information and to register.
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