%0 Generic
%A Herten, Andreas
%A Meinke, Jan
%A Haghighi Mood, Kaveh
%A Kraus, Jiri
%A Hrywniak, Markus
%T GPU Programming Part 1: Foundations
%M FZJ-2024-07560
%D 2024
%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 a GPU.The course will cover 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.This course is a basic course covering the foundations of GPU programming including an introduction to GPU/parallel computing, programming with CUDA, GPU libraries, tools for debugging and profiling, and performance optimizations.Topics covered will include    Introduction to GPUs and GPU computing,    programming model CUDA,    tools for debugging and profiling,    GPU libraries (like cuBLAS, cuFFT), and    introduction to nulti-GPU programming.
%B JSC - as part of the Training Programme of Forschungszentrum Jülich
%C 8 Apr 2024 - 10 Apr 2024, Jülich (Germany)
Y2 8 Apr 2024 - 10 Apr 2024
M2 Jülich, Germany
%F PUB:(DE-HGF)17
%9 Lecture
%R 10.34734/FZJ-2024-07560
%U https://juser.fz-juelich.de/record/1034807