GPU-based parallel computation for discontinuous deformation analysis (DDA) method and its application to modelling earthquake-induced landslide

Graphic Processing Unit (GPU), as a computing device, has upgraded from single-subject graphical processors to multi-core processors with tremendous computational horsepower. This paper proposes to accelerate the DDA using parallel Jacobi Preconditioned Conjugate Gradient (JPCG) technique on GPUs. B...

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Bibliographic Details
Published in:Computers and geotechnics Vol. 86; pp. 80 - 94
Main Authors: Song, Yixiang, Huang, Da, Zeng, Bin
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.06.2017
Elsevier BV
Subjects:
Computation
Computer applications
Computer peripherals
Daguangbao landslide
DDA
Deformation
Deformation analysis
Earthquakes
GPU
Graphics processing units
Horsepower
Jacobi Preconditioned Conjugate Gradient
Landslides
Landslides & mudslides
Mathematical models
Microprocessors
Modelling
Parallel processing
Processors
Seismic activity
Seismic engineering
Seismic response
Solvers
Topography
Topography (geology)
China
DDA
Daguangbao landslide
GPU
Jacobi Preconditioned Conjugate Gradient
ISSN:0266-352X, 1873-7633
Online Access:Get full text
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Summary:Graphic Processing Unit (GPU), as a computing device, has upgraded from single-subject graphical processors to multi-core processors with tremendous computational horsepower. This paper proposes to accelerate the DDA using parallel Jacobi Preconditioned Conjugate Gradient (JPCG) technique on GPUs. Based on the results of two numerical examples, the calculation accuracies of the DDA with serial and parallel solvers are validated, and we found that the DDA with parallel solvers exhibits a much higher execution efficiency. The movement process of Daguangbao landslide triggered by the Wenchuan earthquake is replicated and the modeled deposit pattern coincides well with the actual topography after earthquake.
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ISSN:0266-352X
1873-7633
DOI:10.1016/j.compgeo.2017.01.001