%0 Generic
%A Herten, Andreas
%A Meinke, Jan
%A Kreutz, Jochen
%A Kraus, Jiri
%T GPU Programming with CUDA
%M FZJ-2019-06710
%D 2019
%X 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.
%B PRACE Training Course
%C 1 Apr 2019 - 3 Apr 2019, Jülich (Germany)
Y2 1 Apr 2019 - 3 Apr 2019
M2 Jülich, Germany
%F PUB:(DE-HGF)17
%9 Lecture
%U https://juser.fz-juelich.de/record/868123