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Paper

Efficient Computation of Large-Scale Statistical Solutions to Incompressible Fluid Flows

Tuesday, June 4, 2024
14:00
-
14:30
CEST
Climate, Weather and Earth Sciences
Climate, Weather and Earth Sciences
Climate, Weather and Earth Sciences
Chemistry and Materials
Chemistry and Materials
Chemistry and Materials
Computer Science and Applied Mathematics
Computer Science and Applied Mathematics
Computer Science and Applied Mathematics
Humanities and Social Sciences
Humanities and Social Sciences
Humanities and Social Sciences
Engineering
Engineering
Engineering
Life Sciences
Life Sciences
Life Sciences
Physics
Physics
Physics

Presenter

Tobias
Rohner
-
ETH Zurich

I did my bachelor and master degree in Computational Science and Engineering (CSE) at ETH Zürich with a specialization in physics and fluid mechanics. Since then, I continued by pursuing a PhD mainly doing research on statistical solutions of the incompressible Euler equations and employing them to investigate the behavior of turbulent flows.

Description

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.

Authors