1300212317
Anmeldung ab 11.12.2025 möglich
Link zur AnmeldungInformationen zur Veranstaltung
Attention: This is a five day
block course from
Mon. Feb 9 - Fri Feb. 13, 2026 ONLY!
with lectures in the morning and practical hands-on exercises in the afternoon. We will learn the basic technique to use GPU (graphical processing units, graphics cards) for numerical accelerated computing at the example of CUDA - an extension of the C programming language, which is used for the NVIDIA GPU accelerated supercomputer to be used in our course. Other approaches like HIP for AMD systems will be discussed. Concepts of parallel programming are introduced. GPU accelerated parallel computing is a technique, which is now widely used in computational physics and astrophysics. Many supercomputers of EuroHPC Petascale systems use GPU.
To pass the course (it is NOT graded): proof of daily hands-on exercises under your account, homework assignment submitted; you may do everything in a team of up to two students.
Topics: Parallel Computing, GPU Hardware, Elements of CUDA Language, Data Transfer, Vector and Matrix Operations, GPU accelerated supercomputers, Simple Application for N-Body Problem.
Lehrinhalt
This is a five day block course with lectures in the morning and practical hands-on exercises in the afternoon. We will learn the basic technique to use GPU (graphical processing units, graphics cards) for numerical accelerated computing at the example of CUDA - an extension of the C programming language, which is used for the NVIDIA GPU accelerated supercomputer to be used in our course. More general approaches for other systems will be discussed. Concepts of parallel programming are introduced. GPU accelerated parallel computing is a technique, which is now widely used in computational physics and astrophysics. Many supercomputers of EuroHPC Petascale systems use GPU.
Topics: Parallel Computing, GPU Hardware, Elements of CUDA Language, Data Transfer, Vector and Matrix Operations, Simple Application for N-Body Problem.