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A GPU-accelerated implicit meshless method for compressible flows

delete2018-05-01
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OA
AI
J
Jiale Zhang
Z
Zhihua Ma
陈红全 (Hongquan Chen) *
C
Cheng Cao
DOI:10.1016/j.jcp.2018.01.037delete
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Abstract

Abstract

En 中文
This paper develops a recently proposed GPU based two-dimensional explicit meshless method (Ma et al., 2014) by devising and implementing an efficient parallel LU-SGS implicit algorithm to further improve the computational efficiency. The capability of the original 2D meshless code is extended to deal with 3D complex compressible flow problems. To resolve the inherent data dependency of the standard LU-SGS method, which causes thread-racing conditions destabilizing numerical computation, a generic rainbow coloring method is presented and applied to organize the computational points into different groups by painting neighboring points with different colors. The original LU-SGS method is modified and parallelized accordingly to perform calculations in a color-by-color manner. The CUDA Fortran programming model is employed to develop the key kernel functions to apply boundary conditions, calculate time steps, evaluate residuals as well as advance and update the solution in the temporal space. Aseries of two- and three-dimensional test cases including compressible flows over single-and multi-element airfoils and a M6 wing are carried out to verify the developed code. The obtained solutions agree well with experimental data and other computational results reported in the literature. Detailed analysis on the performance of the developed code reveals that the developed CPU based implicit meshless method is at least four to eight times faster than its explicit counterpart. The computational efficiency of the implicit method could be further improved by ten to fifteen times on the GPU. (c) 2018 Elsevier Inc. All rights reserved.
Keywords:
Implicit meshless
GPU computing
LU-SGS
Rainbow coloring
Euler equations
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Journal

Journal of Computational Physics cover
Journal of Computational Physics
IF:
3.8
Papers:
1.5W
Citations:
7.4W

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M
Manchester Metropolitan University
Scholars:
4.4K
Papers: 5.0K
Citations: 6