%0 Generic
%A Herten, Andreas
%A Meinke, Jan
%A Haghighi Mood, Kaveh
%A Kraus, Jiri
%A Hrywniak, Markus
%T GPU Programming with CUDA
%M FZJ-2022-05803
%D 2022
%Z Online course within the PRACE and FZJ training program.
%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/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.
%B PRACE Training Course at JSC
%C 25 Apr 2022 - 29 Apr 2022, online ()
Y2 25 Apr 2022 - 29 Apr 2022
M2 online, 
%F PUB:(DE-HGF)17
%9 Lecture
%U https://juser.fz-juelich.de/record/915940