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A highly accurate GPU Lattice Boltzmann method with directional interpolation for the probability distribution functions
Author(s) -
DelgadoGutiérrez Arturo,
Marzocca Pier,
Cárdenas Diego,
Probst Oliver
Publication year - 2020
Publication title -
international journal for numerical methods in fluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 112
eISSN - 1097-0363
pISSN - 0271-2091
DOI - 10.1002/fld.4848
Subject(s) - computer science , interpolation (computer graphics) , computational science , lattice boltzmann methods , algorithm , general purpose computing on graphics processing units , graphics processing unit , cuda , benchmark (surveying) , opengl , mathematical optimization , parallel computing , graphics , computer graphics (images) , mathematics , artificial intelligence , animation , visualization , physics , geodesy , quantum mechanics , geography
Summary In this article, a highly accurate and graphics processing unit (GPU)‐accelerated Lattice Boltzmann Method (LBM) is presented. The methodology is derived from a combination of conventional and recent LBM algorithms, mainly focusing on reducing the computational time, memory allocation, and complexity of existing algorithms. The general implementation focuses on accelerating the overall methodology using GPGPU technology based on Compute Shaders from OpenGL and avoids the storage of the distribution function components to reduce the memory allocation size. Furthermore, an efficient spatial interpolation of the probability distribution function components is described, based on a directional interpolation, without unnecessary control points for the reconstruction of virtual nodes data. The present methodology, tested for spatial accuracy via two‐ and three‐dimensional Lid‐Driven Cavity benchmark cases, shows excellent agreement with the results reported in the literature. Additionally, time efficiency is analyzed by comparing different configurations for the construction of virtual streaming points.