%0 Generic
%A Herten, Andreas
%A Hater, Thorsten
%A Haghighi Mood, Kaveh
%A Kraus, Jiri
%A Hrywniak, Markus
%T Directive-based GPU programming with OpenACC
%M FZJ-2022-05791
%D 2022
%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 the GPU. The course covered basic aspects of GPU architectures and programming. Focus was on the usage of the directive-based OpenACC programming model, which allows for portable application development. Examples of increasing complexity were used to demonstrate optimization and tuning of scientific applications. Topics covered:    Introduction to GPU/Parallel computing,    Programming model OpenACC,    Interoperability of OpenACC with GPU libraries (like cuBLAS and cuFFT) and CUDA,    Multi-GPU Programming with MPI and OpenACC,    Tools for debugging and profiling,    Performance optimization. The course consists of lectures and interactive hands-on sessions in C or Fortran (the attendee’s choice).
%B PRACE Training Course at JSC
%C 26 Oct 2022 - 28 Oct 2022, online (Germany)
Y2 26 Oct 2022 - 28 Oct 2022
M2 online, Germany
%F PUB:(DE-HGF)17
%9 Lecture
%U https://juser.fz-juelich.de/record/915928