TY  - GEN
AU  - Herten, Andreas
AU  - Meinke, Jan
AU  - Haghighi Mood, Kaveh
AU  - Kraus, Jiri
AU  - Hrywniak, Markus
TI  - GPU Programming with CUDA
M1  - FZJ-2022-05803
PY  - 2022
N1  - Online course within the PRACE and FZJ training program.
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/C++ which allows maximum control of NVIDIA GPU hardware. Examples of increasing complexity are used to demonstrate optimization and tuning of scientific applications. Topics covered will include:    Introduction to GPU/Parallel computing;    Programming model CUDA;    GPU libraries like CuBLAS and CuFFT;    Tools for debugging and profiling;    Performance optimizations;    Advanced GPU programming model;    CUDA Fortran in a nutshell.This course is a PRACE training course.
T2  - PRACE Training Course at JSC
CY  - 25 Apr 2022 - 29 Apr 2022, online ()
Y2  - 25 Apr 2022 - 29 Apr 2022
M2  - online, 
LB  - PUB:(DE-HGF)17
UR  - https://juser.fz-juelich.de/record/915940
ER  -