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@INPROCEEDINGS{Badwaik:1030182,
author = {Badwaik, Jayesh and Herten, Andreas and Veneva, Milena},
title = {{O}ptimizing an {LBM} {A}pplication {U}sing {CUDA}
{G}raphs},
reportid = {FZJ-2024-05240},
year = {2023},
abstract = {With increasing focus on scalability and performance of
high performance computing applications, it has become
important for the simulation softwares to be able to utilize
the underlying hardware as comprehensively to its maximum
performance. waLBerla is a multiphysics software framework
that has achieved high scalability and performance. It
achieves this excellent performance due to architecture
specific code generation algorithms combined with efficient
communication and parallel data structures like BlockForest.
In this work, we attempt to improve the GPU utilization of
an Lattice-Boltzmann Method (LBM) software.},
month = {May},
date = {2023-05-22},
organization = {ISC High Performance 2023, Hamburg
(Germany), 22 May 2023 - 25 May 2023},
subtyp = {Other},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511) / SCALABLE - SCAlable LAttice
Boltzmann Leaps to Exascale (956000) / ATML-X-DEV - ATML
Accelerating Devices (ATML-X-DEV)},
pid = {G:(DE-HGF)POF4-5112 / G:(EU-Grant)956000 /
G:(DE-Juel-1)ATML-X-DEV},
typ = {PUB:(DE-HGF)24},
doi = {10.34734/FZJ-2024-05240},
url = {https://juser.fz-juelich.de/record/1030182},
}