Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

GPU-accelerated Exponential Time Difference Method for Parabolic Equations with Stiffness

Authors
Xueyun Xie, Liyong Zhu
Corresponding Author
Xueyun Xie
Available Online June 2016.
DOI
https://doi.org/10.2991/mecs-17.2017.80How to use a DOI?
Keywords
GPU acceleration technique, parabolic equations with stiffness, Runge-Kutta exponential time difference method, cuFFT.
Abstract
In this work, we present a Graphics Processing Unit (GPU) accelerated Runge-Kutta exponential time difference (RKETD) method for parabolic equations with stiffness based on CUDA (Computed Unified Device Architecture). In the proposed method, the cuFFT library developed by NVIDIA is employed to compute discrete Fast Fourier Transforms (FFTs) which is the key part in the RKETD method on GPU. Several CUDA code optimization skills are used to improve the speedup performance. The comparison of the numerical results of CUDA-implemented RKETD method on GPU and original RKETD method on CPU demonstrates that the former can obtain good speedup performance. Numerical experiments demonstrate effectiveness and accuracy of the GPU acceleration for typical nonlinear parabolic problem with stiffness.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
978-94-6252-352-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/mecs-17.2017.80How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Xueyun Xie
AU  - Liyong Zhu
PY  - 2016/06
DA  - 2016/06
TI  - GPU-accelerated Exponential Time Difference Method for Parabolic Equations with Stiffness
BT  - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecs-17.2017.80
DO  - https://doi.org/10.2991/mecs-17.2017.80
ID  - Xie2016/06
ER  -