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@MISC{Herten:903617,
author = {Herten, Andreas and Meinke, Jan and Haghighi Mood, Kaveh
and Hrywniak, Markus and Kraus, Jiri},
title = {{PRACE} {T}raining {C}ourse: {GPU} {P}rogramming with
{CUDA}},
reportid = {FZJ-2021-05271},
year = {2021},
note = {Online course within the PRACE and FZJ training program.},
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 will cover
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.Topics
covered include: Introduction to GPU/Parallel computing
Programming model CUDA GPU libraries like CuBLAS and CuFFT
Tools for debugging and profiling Performance
optimizationsThis course is a PRACE training course.},
month = {Apr},
date = {2021-04-26},
organization = {, 26 Apr 2021 - 30 Apr 2021},
subtyp = {Other},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5121 - Supercomputing $\&$ Big Data Facilities (POF4-512) /
5122 - Future Computing $\&$ Big Data Systems (POF4-512) /
5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
(SDLs) and Research Groups (POF4-511) / ATML-X-DEV - ATML
Accelerating Devices (ATML-X-DEV)},
pid = {G:(DE-HGF)POF4-5121 / G:(DE-HGF)POF4-5122 /
G:(DE-HGF)POF4-5111 / G:(DE-Juel-1)ATML-X-DEV},
typ = {PUB:(DE-HGF)17},
url = {https://juser.fz-juelich.de/record/903617},
}