GPU acceleration of FEM solver with applications to Geotechnical Engineering

Master thesis (2022)

Authors

J.R. Hoofwijk Electrical Engineering, Mathematics and Computer Science

Contributors

Cornelis Vuik Numerical Analysis - EEMCS (supervisor 1)
Sandro Brasile Plaxis (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Jorn Hoofwijk
Finite Element Method Conjugate Gradient GPU Deflation Preconditioning Krylov solvers
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Published Date

28-01-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

In finite element software one has to solve a system of non-linear equations, which is commonly simplified to a sequence of linear system. We research the possibility to solve these systems on a GPU to improve the solve time. We are particularly interested in systems arising from geotechnical models. We compare several combinations of Krylov methods, parallel preconditioners and deflation methods and present a suitable combination. This solver is then compared with existing CPU based solvers in PLAXIS 3D. We show that compared to the current iterative solver, the iteration time can be reduced by 50% up to 85% depending on the problem. While compared to the current direct solver, the memory consumption and initialization time can be reduced significantly.