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. © 2014 Global Science Press.
Original language | English (US) |
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Pages (from-to) | 1-23 |
Number of pages | 23 |
Journal | Advances in Applied Mathematics and Mechanics |
Volume | 6 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2014 |
Externally published | Yes |
Bibliographical note
Generated from Scopus record by KAUST IRTS on 2023-02-15ASJC Scopus subject areas
- Applied Mathematics
- Mechanical Engineering