CUDA-based solver for large-scale groundwater flow simulation

This article presents a parallel simulation solver for groundwater flow on CUDA. Preconditioned conjugate gradient (PCG) algorithm is used to solve the large linear systems arising from the finite-difference discretization of three-dimensional groundwater flow problems. CUDA implementing methods for...

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Veröffentlicht in:	Engineering with computers Jg. 28; H. 1; S. 13 - 19
Hauptverfasser:	Ji, Xiaohui, Cheng, Tangpei, Wang, Qun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer-Verlag 01.01.2012 Springer Nature B.V
Schlagworte:	CAE) and Design Calculus of Variations and Optimal Control; Optimization Classical Mechanics Computer Science Computer simulation Computer-Aided Engineering (CAD Control Discretization Finite difference method Groundwater Linear systems Math. Applications in Chemistry Mathematical analysis Mathematical and Computational Engineering Original Article Solvers Systems Theory Vectors (mathematics) CUDA Groundwater simulation Preconditioned conjugate gradient algorithm GPU
ISSN:	0177-0667, 1435-5663
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Abstract	This article presents a parallel simulation solver for groundwater flow on CUDA. Preconditioned conjugate gradient (PCG) algorithm is used to solve the large linear systems arising from the finite-difference discretization of three-dimensional groundwater flow problems. CUDA implementing methods for the two most time-consuming operations in PCG, sparse matrix–vector multiplication and vector inner-product, are given. The experimental results show that CUDA can speed up the solving process of the groundwater simulation significantly. 1.8–3.7 speedup can be achieved with different GPUs for a transient groundwater flow problem.
AbstractList	This article presents a parallel simulation solver for groundwater flow on CUDA. Preconditioned conjugate gradient (PCG) algorithm is used to solve the large linear systems arising from the finite-difference discretization of three-dimensional groundwater flow problems. CUDA implementing methods for the two most time-consuming operations in PCG, sparse matrix-vector multiplication and vector inner-product, are given. The experimental results show that CUDA can speed up the solving process of the groundwater simulation significantly. 1.8-3.7 speedup can be achieved with different GPUs for a transient groundwater flow problem. This article presents a parallel simulation solver for groundwater flow on CUDA. Preconditioned conjugate gradient (PCG) algorithm is used to solve the large linear systems arising from the finite-difference discretization of three-dimensional groundwater flow problems. CUDA implementing methods for the two most time-consuming operations in PCG, sparse matrix-vector multiplication and vector inner-product, are given. The experimental results show that CUDA can speed up the solving process of the groundwater simulation significantly. 1.8-3.7 speedup can be achieved with different GPUs for a transient groundwater flow problem.[PUBLICATION ABSTRACT]
Author	Ji, Xiaohui Wang, Qun Cheng, Tangpei
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Cites_doi	10.1016/S0898-1221(98)00031-5 10.1007/s11227-008-0251-8 10.1111/j.1745-6584.2009.00598.x 10.1137/1.9781611971538 10.1016/S0309-1708(02)00006-4 10.1145/882262.882364 10.1088/1742-6596/78/1/012051 10.1109/JPROC.2008.917757
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SubjectTerms	CAE) and Design Calculus of Variations and Optimal Control; Optimization Classical Mechanics Computer Science Computer simulation Computer-Aided Engineering (CAD Control Discretization Finite difference method Groundwater Linear systems Math. Applications in Chemistry Mathematical analysis Mathematical and Computational Engineering Original Article Solvers Systems Theory Vectors (mathematics)
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Title	CUDA-based solver for large-scale groundwater flow simulation
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