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

by T. Rohner and S. Mishra

(Report number 2024-04)

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.

Keywords: Computational Fluid Dynamics, Direct Numerical Simulation, GPU accelerated simulation

@Techreport{RM24_1086,
  author = {T. Rohner and S. Mishra},
  title = {Efficient Computation of Large-Scale Statistical Solutions to Incompressible Fluid Flows},
  institution = {Seminar for Applied Mathematics, ETH Z{\"u}rich},
  number = {2024-04},
  address = {Switzerland},
  url = {https://www.sam.math.ethz.ch/sam_reports/reports_final/reports2024/2024-04.pdf },
  year = {2024}
}

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