TY  - GEN
AU  - Herten, Andreas
AU  - Hater, Thorsten
AU  - Haghighi Mood, Kaveh
AU  - Kraus, Jiri
AU  - Hrywniak, Markus
TI  - Directive-based GPU programming with OpenACC
M1  - FZJ-2022-05791
PY  - 2022
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 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).
T2  - PRACE Training Course at JSC
CY  - 26 Oct 2022 - 28 Oct 2022, online (Germany)
Y2  - 26 Oct 2022 - 28 Oct 2022
M2  - online, Germany
LB  - PUB:(DE-HGF)17
UR  - https://juser.fz-juelich.de/record/915928
ER  -