Lecture (Other)

FZJ-2019-06710

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png GPU Programming with CUDA

Herten, A. (Corresponding author)FZJ* ; Meinke, J.FZJ* ; Kreutz, J.FZJ* ; Kraus, J.FZJ*

2019

Abstract: 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 which allows maximum control of NVIDIA GPU hardware. Examples of increasing complexity are used to demonstrate optimization and tuning of scientific applications.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 511 - Computational Science and Mathematical Methods (POF3-511) (POF3-511)
2. 513 - Supercomputer Facility (POF3-513) (POF3-513)

Appears in the scientific report 2019

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