TRITON: A Multi-GPU open source 2D hydrodynamic flood model

Morales-Hernändez, Mario; Sharif, Bulbul; Kalyanapu, Alfred J.; Ghafoor, Sheikh; Dullo, T. T.; Gangrade, Sudershan; Kao, Shih‐Chieh; Norman, Matthew R.; Evans, Katherine J

doi:10.1016/j.envsoft.2021.105034

Cited by 60 publications

(30 citation statements)

References 55 publications

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“…The global time step t is found by calculating the minimum value across all elements using an OpenMP reduction. The same parallelisation strategy is already adopted in existing LISFLOOD-FP solvers (Neal et al, 2009) because it is straightforward to implement with minimal code changes for any explicit numerical scheme involving local, element-wise operations. While some LISFLOOD-FP solvers implement more sophisticated OpenMP parallelisation and dry cell optimisation (Neal et al, 2018), this can introduce additional code complexity and runtime overhead (Morales-Hernández et al, 2020), so it has not been adopted for the new LISFLOOD-DG2-CPU solver.…”

Section: Openmp Parallelisation For Multi-core Cpusmentioning

confidence: 99%

“…Parallelisation is the next step towards making DG2 flood modelling operational on large-scale, high-resolution do-mains. Existing LISFLOOD-FP solvers are parallelised using OpenMP for multi-core CPUs, which have been tested on domains with up to 23 million elements on a 16-core CPU (Neal et al, 2009(Neal et al, , 2018. But as flood models are applied to increasingly large domains at increasingly fine resolutions, a greater degree of parallelism can be achieved using GPU accelerators (Brodtkorb et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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LISFLOOD-FP 8.0: the new discontinuous Galerkin shallow-water solver for multi-core CPUs and GPUs

et al. 2021

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Abstract. LISFLOOD-FP 8.0 includes second-order discontinuous Galerkin (DG2) and first-order finite-volume (FV1) solvers of the two-dimensional shallow-water equations for modelling a wide range of flows, including rapidly propagating, supercritical flows, shock waves or flows over very smooth surfaces. The solvers are parallelised on multi-core CPU and Nvidia GPU architectures and run existing LISFLOOD-FP modelling scenarios without modification. These new, fully two-dimensional solvers are available alongside the existing local inertia solver (called ACC), which is optimised for multi-core CPUs and integrates with the LISFLOOD-FP sub-grid channel model. The predictive capabilities and computational scalability of the new DG2 and FV1 solvers are studied for two Environment Agency benchmark tests and a real-world fluvial flood simulation driven by rainfall across a 2500 km2 catchment. DG2's second-order-accurate, piecewise-planar representation of topography and flow variables enables predictions on coarse grids that are competitive with FV1 and ACC predictions on 2–4 times finer grids, particularly where river channels are wider than half the grid spacing. Despite the simplified formulation of the local inertia solver, ACC is shown to be spatially second-order-accurate and yields predictions that are close to DG2. The DG2-CPU and FV1-CPU solvers achieve near-optimal scalability up to 16 CPU cores and achieve greater efficiency on grids with fewer than 0.1 million elements. The DG2-GPU and FV1-GPU solvers are most efficient on grids with more than 1 million elements, where the GPU solvers are 2.5–4 times faster than the corresponding 16-core CPU solvers. LISFLOOD-FP 8.0 therefore marks a new step towards operational DG2 flood inundation modelling at the catchment scale. LISFLOOD-FP 8.0 is freely available under the GPL v3 license, with additional documentation and case studies at https://www.seamlesswave.com/LISFLOOD8.0 (last access: 2 June 2021).

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Section: Openmp Parallelisation For Multi-core Cpusmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

LISFLOOD-FP 8.0: the new discontinuous Galerkin shallow-water solver for multi-core CPUs and GPUs

et al. 2021

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“…The ensemble inundation modeling was performed using TRITON, which is a computationally enhanced version of Flood2D-GPU (Kalyanapu et al, 2011). TRITON allows parallel computing using multiple graphics processing units (GPUs) through a hybrid Message Passing Interface (MPI) and Compute Unified Device Architecture (CUDA) (Morales-Hernández et al, 2021). TRITON solves the nonlinear hyperbolic shallow water equations using an explicit upwind finite-volume scheme, based on Roe's linearization.…”

Section: Inundation Modelingmentioning

confidence: 99%

“…TRITON solves the nonlinear hyperbolic shallow water equations using an explicit upwind finite-volume scheme, based on Roe's linearization. The shallow water equations are a simplified version of the Navier-Stokes equations in which the horizontal momentum and continuity equations are integrated in the vertical direction (see Morales-Hernández et al, 2021, for further model details). An evaluation of TRITON performance for the CRW is presented and discussed in Sect.…”

Section: Inundation Modelingmentioning

confidence: 99%

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Assessing climate-change-induced flood risk in the Conasauga River watershed: an application of ensemble hydrodynamic inundation modeling

Dullo

Darkwah

Gangrade

et al. 2021

Nat. Hazards Earth Syst. Sci.

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Abstract. This study evaluates the impact of potential future climate change on flood regimes, floodplain protection, and electricity infrastructures across the Conasauga River watershed in the southeastern United States through ensemble hydrodynamic inundation modeling. The ensemble streamflow scenarios were simulated by the Distributed Hydrology Soil Vegetation Model (DHSVM) driven by (1) 1981–2012 Daymet meteorological observations and (2) 11 sets of downscaled global climate models (GCMs) during the 1966–2005 historical and 2011–2050 future periods. Surface inundation was simulated using a GPU-accelerated Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON) hydrodynamic model. A total of 9 out of the 11 GCMs exhibit an increase in the mean ensemble flood inundation areas. Moreover, at the 1 % annual exceedance probability level, the flood inundation frequency curves indicate a ∼ 16 km2 increase in floodplain area. The assessment also shows that even after flood-proofing, four of the substations could still be affected in the projected future period. The increase in floodplain area and substation vulnerability highlights the need to account for climate change in floodplain management. Overall, this study provides a proof-of-concept demonstration of how the computationally intensive hydrodynamic inundation modeling can be used to enhance flood frequency maps and vulnerability assessment under the changing climatic conditions.

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Intersecting Near-Real Time Fluvial and Pluvial Inundation Estimates with Sociodemographic Vulnerability to Quantify a Household Flood Impact Index

Preisser

Passalacqua

Bixler

et al. 2022

Preprint

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TRITON: A Multi-GPU open source 2D hydrodynamic flood model

Cited by 60 publications

References 55 publications

LISFLOOD-FP 8.0: the new discontinuous Galerkin shallow-water solver for multi-core CPUs and GPUs

LISFLOOD-FP 8.0: the new discontinuous Galerkin shallow-water solver for multi-core CPUs and GPUs

Assessing climate-change-induced flood risk in the Conasauga River watershed: an application of ensemble hydrodynamic inundation modeling

Intersecting Near-Real Time Fluvial and Pluvial Inundation Estimates with Sociodemographic Vulnerability to Quantify a Household Flood Impact Index

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