Year: 2014
Author: Chunsheng Feng, Shi Shu, Jinchao Xu, Chen-Song Zhang
Advances in Applied Mathematics and Mechanics, Vol. 6 (2014), Iss. 1 : pp. 1–23
Abstract
The geometric multigrid method (GMG) is one of the most efficient solving techniques for discrete algebraic systems arising from elliptic partial differential equations. GMG utilizes a hierarchy of grids or discretizations and reduces the error at a number of frequencies simultaneously. Graphics processing units (GPUs) have recently burst onto the scientific computing scene as a technology that has yielded substantial performance and energy-efficiency improvements. A central challenge in implementing GMG on GPUs, though, is that computational work on coarse levels cannot fully utilize the capacity of a GPU. In this work, we perform numerical studies of GMG on CPU-GPU heterogeneous computers. Furthermore, we compare our implementation with an efficient CPU implementation of GMG and with the most popular fast Poisson solver, Fast Fourier Transform, in the cuFFT library developed by NVIDIA.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/aamm.2013.m87
Advances in Applied Mathematics and Mechanics, Vol. 6 (2014), Iss. 1 : pp. 1–23
Published online: 2014-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 23
Keywords: High-performance computing CPU–GPU heterogeneous computers multigrid method fast Fourier transform partial differential equations.
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