Computationally Efficient Tsunami Modeling on Graphics Processing Units (GPUs)

Amouzgar, Reza; Liang, Qiuhua; Clarke, Peter J.; Yasuda, Tomohiro; Mase, Hajime

doi:10.17736/ijope.2016.ak10

Cited by 17 publications

(9 citation statements)

References 23 publications

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“…GPU acceleration has been applied to tsunami models in the past, although primarily on grids with fixed spatial resolution, including those of Acuña and Aoki (), Lastra et al (), De La Asunción et al (), Brodtkorb et al (), de la Asunción et al (), Smith and Liang (), Amouzgar et al (), and De La Asunción et al (). A recent application to an AMR code is presented by de la Asunción and Castro () for a landslide‐generated tsunami, and GPU acceleration of other AMR algorithms have been pursued in other communities, particularly in astrophysics (e.g., Schive et al, ; Wang et al, ).…”

Section: Related Work and Other Approachesmentioning

confidence: 99%

Accelerating an Adaptive Mesh Refinement Code for Depth‐Averaged Flows Using GPUs

Qin

LeVeque

Motley

2019

J Adv Model Earth Syst

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Solving the shallow water equations efficiently is critical to the study of natural hazards induced by tsunami and storm surge, since it provides more response time in an early warning system and allows more runs to be done for probabilistic assessment where thousands of runs may be required. Using adaptive mesh refinement speeds up the process by greatly reducing computational demands while accelerating the code using the graphics processing unit (GPU) does so through using faster hardware. Combining both, we present an efficient CUDA implementation of GeoClaw, an open source Godunov‐type high‐resolution finite volume numerical scheme on adaptive grids for shallow water system with varying topography. The use of adaptive mesh refinement and spherical coordinates allows modeling transoceanic tsunami simulation. Numerical experiments on the 2011 Japan tsunami and a local tsunami triggered by a hypothetical Mw 7.3 earthquake on the Seattle Fault illustrate the correctness and efficiency of the code, which implements a simplified dimensionally split version of the algorithms. Both numerical simulations are conducted on subregions on a sphere with adaptive grids that adequately resolve the propagating waves. The implementation is shown to be accurate and faster than the original when using Central Processing Units (CPUs) alone. The GPU implementation, when running on a single GPU, is observed to be 3.6 to 6.4 times faster than the original model running in parallel on a 16‐core CPU. Three metrics are proposed to evaluate relative performance of the model, which shows efficient usage of hardware resources.

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Section: Related Work and Other Approachesmentioning

confidence: 99%

Accelerating an Adaptive Mesh Refinement Code for Depth‐Averaged Flows Using GPUs

Qin

LeVeque

Motley

2019

J Adv Model Earth Syst

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“…Detailed implementation of the numerical scheme can be found in Liang and Borthwick (2009) and Liang (2010). In order to substantially improve its computational efficiency for large-scale tsunami modeling, the model is implemented for GPU high-performance computing using the NVIDIA CUDA programing framework, which can be up to 40 times faster than its counterpart running on a standard CPU (refer to Amouzgar et al (2016) for more details).…”

Section: High-performance Hydrodynamic Tsunami Modelmentioning

confidence: 99%

“…Particularly, GPUs have been used to improve the computational performance of hydrodynamic models that solve the shallow water equations (SWEs), which can be applied in tsunami modelling. Brodtkorb A similar numerical scheme has also been implemented on GPUs using the CUDA programming framework for whole-process tsunami modelling from wave propagation in deep water to flood inundation in dry lands (Amouzgar et al, 2016), which was then further extended to quantify the impacting forces induced by surge waves on structures at the laboratory scale (Xiong et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

A deterministic approach for assessing tsunami-induced building damage through quantification of hydrodynamic forces

Xiong

Liang

Park

et al. 2019

Coastal Engineering

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In certain coastal areas across the globe, tsunamis pose a great threat to buildings, infrastructure and people's lives. The prevailing approaches for assessing building damage are based on probabilistic analysis. This paper introduces a new deterministic approach to assess large-scale building damage through quantifying lateral loading on structures induced by tsunami waves. A depth-averaged hydrodynamic model is adopted to simulate tsunami propagation and inundation and calculate the induced pressures and forces on structures. The model solves the 2D nonlinear shallow water equations (SWEs) using a finite volume shock-capturing numerical scheme and is implemented on Graphics Processing Units (GPUs) to achieve high-performance computing for large-scale applications. A new model component is included to calculate pressures and forces using the predicted flow variables, i.e. water depth and velocities. The output maximum tsunami forces are combined with a lateral force resisting system on each building to estimate the damage states. This new approach is developed by taking advantages of a similar damage assessment method and the corresponding coefficients for quantifying earthquake impact on buildings, due to the similarity between the horizontal force systems induced by the tsunami waves and earthquake motions. After being successfully validated against three experimental cases related to flow hydrodynamics, pressures and forces, the model is used to simulate a hypothetical 1000-year tsunami event in the City of Seaside, Oregon, USA. The resulting damage states are then classified for each of the urban buildings in the area, taking into account different building types. The predicted results are consistent with those obtained using alternative approaches, confirming the potential of the proposed approach for practical engineering applications.

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“…Detailed implementation of the numerical scheme can be found in Liang and Borthwick [30] and Liang [33]. GPU (Graphics Processing Unit)-based parallelization is implemented via the NVIDIA CUDA framework to improve the computational efficiency [34].…”

Section: Finite Volume Godunov-type Swe Modelmentioning

confidence: 99%

Simulation of Hydraulic Structures in 2D High-Resolution Urban Flood Modeling

Cui

Liang

Wang

et al. 2019

Water

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Urban flooding as a result of inadequate drainage capacity, failure of flood defenses, etc. is usually featured with highly transient hydrodynamics. Reliable and efficient prediction and forecasting of these urban flash floods is still a great technical challenge. Meanwhile, in urban environments, the flooding hydrodynamics and process may be influenced by flow regulation and flood protection hydraulic infrastructure systems, such as sluice gates, which should be effectively taken into account in an urban flood model. However, direct simulation of hydraulic structures is not a current practice in 2D urban flood modeling. This work aims to develop a robust numerical approach to directly simulate the effects of gate structures in a 2D high-resolution urban flood model. A new modeling component is developed and fully coupled to a finite volume Godunov-type shock-capturing shallow water model, to directly simulate the highly transient flood waves through hydraulic structures. Different coupling approaches, i.e., flux term coupling and source term coupling, are implemented and compared. A numerical experiment conducted for an analytical dam-break test indicates that the flux term coupling approach may lead to more accurate results, with the calculated RMSE against water level 28%–38% less than that produced by the source term coupling approach. The flux term coupling approach is therefore adopted to improve the current urban flood model, and it is further tested by reproducing the laboratory experiments of flood routing in a flume with partially open sluice gates, conducted in the hydraulic laboratory at the Zhejiang Institute of Hydraulics and Estuary, China. The numerical results are compared favorably with experimental measurements, with a maximum RMSE of 0.0851 for all the individual tests. The satisfactory results demonstrate that the flood model implemented with the flux coupling approach is able to accurately simulate the flow through hydraulic structures, with enhanced predictive capability for urban flood modeling.

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Computationally Efficient Tsunami Modeling on Graphics Processing Units (GPUs)

Cited by 17 publications

References 23 publications

Accelerating an Adaptive Mesh Refinement Code for Depth‐Averaged Flows Using GPUs

Accelerating an Adaptive Mesh Refinement Code for Depth‐Averaged Flows Using GPUs

A deterministic approach for assessing tsunami-induced building damage through quantification of hydrodynamic forces

Simulation of Hydraulic Structures in 2D High-Resolution Urban Flood Modeling

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