TY  - GEN
AU  - Herten, Andreas
AU  - Meinke, Jan
AU  - Haghighi Mood, Kaveh
AU  - Kraus, Jiri
AU  - Hrywniak, Markus
TI  - GPU Programming Part 1: Foundations
M1  - FZJ-2023-05176
PY  - 2023
AB  - GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GPUs offers high application performance by offloading compute-intensive portions of the code to a GPU.The course covers aspects of GPU architectures and programming. Focus is on the usage of the parallel programming language CUDA C++, which allows maximum control of NVIDIA GPU hardware. Examples of increasing complexity are used to demonstrate optimization and tuning of scientific applications.For the first time, the GPU Programming with CUDA course is held in two parts. This course is a basic course covering the foundations of GPU programming including an introduction to GPU/parallel computing, programming with CUDA, GPU libraries, tools for debugging and profiling, and performance optimizations.An advanced course with more involved and specific topics is available as an individual entry.
T2  - JSC - as part of the Training Programme of Forschungszentrum Jülich
CY  - 17 Apr 2023 - 19 Apr 2023, Jülich (Germany)
Y2  - 17 Apr 2023 - 19 Apr 2023
M2  - Jülich, Germany
LB  - PUB:(DE-HGF)17
DO  - DOI:10.34734/FZJ-2023-05176
UR  - https://juser.fz-juelich.de/record/1019123
ER  -