TY  - GEN
AU  - Herten, Andreas
AU  - Meinke, Jan
AU  - Kreutz, Jochen
AU  - Kraus, Jiri
TI  - GPU Programming with CUDA
M1  - FZJ-2019-06710
PY  - 2019
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 an NVIDIA GPU. The course covers basic 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.
T2  - PRACE Training Course
CY  - 1 Apr 2019 - 3 Apr 2019, Jülich (Germany)
Y2  - 1 Apr 2019 - 3 Apr 2019
M2  - Jülich, Germany
LB  - PUB:(DE-HGF)17
UR  - https://juser.fz-juelich.de/record/868123
ER  -