Efficient Computation of Large-Scale Statistical Solutions to Incompressible Fluid Flows
dc.contributor.author
Rohner, Tobias
dc.contributor.author
Mishra, Siddhartha
dc.date.accessioned
2024-02-19T07:20:06Z
dc.date.available
2024-02-08T11:04:25Z
dc.date.available
2024-02-19T07:20:06Z
dc.date.issued
2024-01
dc.identifier.uri
http://hdl.handle.net/20.500.11850/658457
dc.description.abstract
This work presents the development, performance analysis and subsequent optimization of a GPU-based spectral hyperviscosity solver for turbulent flows described by the three dimensional incompressible Navier-Stokes equations. The method solves for the fluid velocity fields directly in Fourier space, eliminating the need to solve a large-scale linear system of equations in order to find the pressure field. Special focus is put on the communication intensive transpose operation required by the Fast Fourier transform when using distributed memory parallelism. After multiple iterations of benchmarking and improving the code, the simulation achieves close to optimal performance on the Piz Daint supercomputer cluster, even outperforming the Cray MPI implementation on Piz Daint in its communication routines. This optimal performance enables the computation of large-scale statistical solutions of incompressible fluid flows in three space dimensions.
en_US
dc.language.iso
en
en_US
dc.publisher
Seminar for Applied Mathematics, ETH Zurich
en_US
dc.subject
Computational fluid dynamics
en_US
dc.subject
Direct numerical simulation
en_US
dc.subject
GPU accelerated simulation
en_US
dc.title
Efficient Computation of Large-Scale Statistical Solutions to Incompressible Fluid Flows
en_US
dc.type
Report
ethz.journal.title
SAM Research Report
ethz.journal.volume
2024-04
en_US
ethz.size
12 p.
en_US
ethz.grant
Computation and analysis of statistical solutions of fluid flow
en_US
ethz.publication.place
Zurich
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02501 - Seminar für Angewandte Mathematik / Seminar for Applied Mathematics::03851 - Mishra, Siddhartha / Mishra, Siddhartha
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02501 - Seminar für Angewandte Mathematik / Seminar for Applied Mathematics::03851 - Mishra, Siddhartha / Mishra, Siddhartha
en_US
ethz.identifier.url
https://math.ethz.ch/sam/research/reports.html?id=1086
ethz.grant.agreementno
770880
ethz.grant.fundername
EC
ethz.grant.funderDoi
10.13039/501100000780
ethz.grant.program
H2020
ethz.date.deposited
2024-02-08T11:04:25Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.identifier.internal
https://math.ethz.ch/sam/research/reports.html?id=1086
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2024-02-19T07:20:07Z
ethz.rosetta.lastUpdated
2025-02-14T08:02:41Z
ethz.rosetta.versionExported
true
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