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@INPROCEEDINGS{Mateevitsi:1026000,
author = {Mateevitsi, Victor A. and Bode, Mathis and Ferrier, Nicola
and Fischer, Paul and Göbbert, Jens Henrik and Insley,
Joseph A. and Lan, Yu-Hsiang and Min, Misun and Papka,
Michael E. and Patel, Saumil and Rizzi, Silvio and
Windgassen, Jonathan},
title = {{S}caling {C}omputational {F}luid {D}ynamics: {I}n {S}itu
{V}isualization of {N}ek{RS} using {SENSEI}},
address = {New York, USA},
publisher = {Association for Computing Machinery},
reportid = {FZJ-2024-03256},
isbn = {9798400707858},
pages = {862–867},
year = {2023},
comment = {Proceedings of the SC '23 Workshops of The International
Conference on High Performance Computing, Network, Storage,
and Analysis - ACM New York, NY, USA, 2023},
booktitle = {Proceedings of the SC '23 Workshops of
The International Conference on High
Performance Computing, Network,
Storage, and Analysis - ACM New York,
NY, USA, 2023},
abstract = {In the realm of Computational Fluid Dynamics (CFD), the
demand for memory and computation resources is extreme,
necessitating the use of leadership-scale computing
platforms for practical domain sizes. This intensive
requirement renders traditional checkpointing methods
ineffective due to the significant slowdown in simulations
while saving state data to disk. As we progress towards
exascale and GPU-driven High-Performance Computing (HPC) and
confront larger problem sizes, the choice becomes
increasingly stark: to compromise data fidelity or to reduce
resolution. To navigate this challenge, this study advocates
for the use of in situ analysis and visualization
techniques. These allow more frequent data "snapshots" to be
taken directly from memory, thus avoiding the need for
disruptive checkpointing. We detail our approach of
instrumenting NekRS, a GPU-focused thermal-fluid simulation
code employing the spectral element method (SEM), and
describe varied in situ and in transit strategies for data
rendering. Additionally, we provide concrete scientific
use-cases and report on runs performed on Polaris, Argonne
Leadership Computing Facility’s (ALCF) 44 Petaflop
supercomputer and Jülich Wizard for European Leadership
Science (JUWELS) Booster, Jülich Supercomputing Centre’s
(JSC) 71 Petaflop High Performance Computing (HPC) system,
offering practical insight into the implications of our
methodology.},
month = {Nov},
date = {2023-11-12},
organization = {Workshops of The International
Conference on High Performance
Computing, Network, Storage, and
Analysis, Denver, CO (USA), 12 Nov 2023
- 17 Nov 2023},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511) / CoEC - Center of Excellence
in Combustion (952181)},
pid = {G:(DE-HGF)POF4-5112 / G:(EU-Grant)952181},
typ = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
doi = {10.1145/3624062.3624159},
url = {https://juser.fz-juelich.de/record/1026000},
}