gNek: A GPU Accelerated Incompressible Navier Stokes Solver

Date
2013-09-16
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Abstract

This thesis presents a GPU accelerated implementation of a high order splitting scheme with a spectral element discretization for the incompressible Navier Stokes (INS) equations. While others have implemented this scheme on clusters of processors using the Nek5000 code, to my knowledge this thesis is the first to explore its performance on the GPU. This work implements several of the Nek5000 algorithms using OpenCL kernels that efficiently utilize the GPU memory architecture, and achieve massively parallel on chip computations. These rapid computations have the potential to significantly enhance computational fluid dynamics (CFD) simulations that arise in areas such as weather modeling or aircraft design procedures. I present convergence results for several test cases including channel, shear, Kovasznay, and lid-driven cavity flow problems, which achieve the proven convergence results.

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Degree
Master of Arts
Type
Thesis
Keywords
Incompressible Navier Stokes, Computational fluid dynamics, GPU, Accelerated, Fluid flow, Spectral element method, Projection method, Splitting method, Domain decomposition
Citation

Stilwell, Nichole. "gNek: A GPU Accelerated Incompressible Navier Stokes Solver." (2013) Master’s Thesis, Rice University. https://hdl.handle.net/1911/72043.

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