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Exploring the Ultimate Regime of Turbulent Rayleigh–Bénard Convection Through Unprecedented Spectral-Element Simulations
KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.ORCID iD: 0000-0002-5020-1631
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0000-0003-3374-8093
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Fluid Mechanics and Engineering Acoustics.ORCID iD: 0000-0001-5204-8549
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Fluid Mechanics and Engineering Acoustics.ORCID iD: 0000-0002-2195-8408
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2023 (English)In: SC '23: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, Association for Computing Machinery (ACM) , 2023, p. 1-9, article id 5Conference paper, Published paper (Refereed)
Abstract [en]

We detail our developments in the high-fidelity spectral-element code Neko that are essential for unprecedented large-scale direct numerical simulations of fully developed turbulence. Major inno- vations are modular multi-backend design enabling performance portability across a wide range of GPUs and CPUs, a GPU-optimized preconditioner with task overlapping for the pressure-Poisson equation and in-situ data compression. We carry out initial runs of Rayleigh–Bénard Convection (RBC) at extreme scale on the LUMI and Leonardo supercomputers. We show how Neko is able to strongly scale to 16,384 GPUs and obtain results that are not pos- sible without careful consideration and optimization of the entire simulation workflow. These developments in Neko will help resolv- ing the long-standing question regarding the ultimate regime in RBC. 

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2023. p. 1-9, article id 5
National Category
Computer Sciences Fluid Mechanics and Acoustics
Identifiers
URN: urn:nbn:se:kth:diva-340333DOI: 10.1145/3581784.3627039Scopus ID: 2-s2.0-85179549233OAI: oai:DiVA.org:kth-340333DiVA, id: diva2:1816621
Conference
SC: The International Conference for High Performance Computing, Networking, Storage, and Analysis, NOV 12–17 DENVER, CO, USA
Funder
Swedish Research Council, 2019-04723Swedish e‐Science Research CenterEU, Horizon 2020, 101093393, 101092621, 956748
Note

Part of ISBN 9798400701092

QC 20231204

Available from: 2023-12-04 Created: 2023-12-04 Last updated: 2024-03-18Bibliographically approved

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Jansson, NiclasKarp, MartinPerez, AdalbertoMukha, TimofeyLiu, JiahuiPall, SzilardLaure, ErwinWeinkauf, TinoSchlatter, PhilippMarkidis, Stefano

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Jansson, NiclasKarp, MartinPerez, AdalbertoMukha, TimofeyLiu, JiahuiPall, SzilardLaure, ErwinWeinkauf, TinoSchlatter, PhilippMarkidis, Stefano
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Centre for High Performance Computing, PDCComputational Science and Technology (CST)Fluid Mechanics and Engineering Acoustics
Computer SciencesFluid Mechanics and Acoustics

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