Evidence map›Paper›PMID 39391269›Full record

ArticleAIMS mathematics2024

Efficient numerical approaches with accelerated graphics processing unit (GPU) computations for Poisson problems and Cahn-Hilliard equations.

Saulo Orizaga, Maurice Fabien, Michael Millard

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Article in AIMS mathematics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Saulo OrizagaDepartment of Mathematics, New Mexico Tech, 801 Leroy Place, Socorro, NM 87801, USA.
Maurice FabienDepartment of Mathematics, University of Wisconsin-Madison,Van Vleck Hall, 213, 480 Lincoln Dr, Madison, WI 53706, USA.
Michael MillardDepartment of Mathematics, New Mexico Tech, 801 Leroy Place, Socorro, NM 87801, USA.

Funding

NM-INBRE Sequencing and Bioinformatics CoreP20GM103451 · NIGMS · NEW MEXICO STATE UNIVERSITY LAS CRUCES · PI Charlotte C. Gard · 2012 to 2026
$61.2M
NIGMS NIH HHS P20 GM103451
6 · The paper itself

Abstract

In this computational paper, we focused on the efficient numerical implementation of semi-implicit methods for models in materials science. In particular, we were interested in a class of nonlinear higher-order parabolic partial differential equations. The Cahn-Hilliard (CH) equation was chosen as a benchmark problem for our proposed methods. We first considered the Cahn-Hilliard equation with a convexity-splitting (CS) approach coupled with a backward Euler approximation of the time derivative and tested the performance against the bi-harmonic-modified (BHM) approach in terms of accuracy, order of convergence, and computation time. Higher-order time-stepping techniques that allow for the methods to increase their accuracy and order of convergence were then introduced. The proposed schemes in this paper were found to be very efficient for 2D computations. Computed dynamics in 2D and 3D are presented to demonstrate the energy-decreasing property and overall performance of the methods for longer simulation runs with a variety of initial conditions. In addition, we also present a simple yet powerful way to accelerate the computations by using MATLAB built-in commands to perform GPU implementations of the schemes. We show that it is possible to accelerate computations for the CH equation in 3D by a factor of 80, provided the hardware is capable enough.

Indexed as

65M9965T50Cahn-Hilliard equationefficient numerical methodsGPU computationphase-field modelsthin-film equation

Identifiers

PMID39391269
PMCPMC11466300

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