High-performance computing in water resources hydrodynamics

Morales-Hernändez, Mario; Sharif, Md Bulbul; Gangrade, Sudershan; Dullo, T. T.; Kao, Shih‐Chieh; Kalyanapu, Alfred J.; Ghafoor, Sheikh; Evans, Katherine J.; Madadi-Kandjani, Ehsan; Hodges, Ben R.

doi:10.2166/hydro.2020.163

Cited by 39 publications

(23 citation statements)

References 15 publications

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“…For example, García-Feal et al (2018) compared Iber+ hydrodynamic model runs on a GPU against a 16-core CPU and obtained a 4-15-fold speed-up depending on the test case. Running in a multi-GPU configuration, the TRITON model has been applied on a 6800 km 2 domain with 68 million elements to simulate a 10 d storm event in under 30 min (Morales-Hernández et al, 2021), and the HiPIMS model was applied on a 2500 km 2 domain with 100 million elements to simulate a 4 d storm event in 1.5 d (Xia et al, 2019).…”

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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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: 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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“…For parallel computing, the advantage of AC is that it replaces the global solution of an elliptic matrix inversion with local hyperbolic wave propagation. This "local" limitation means that communication between processors is readily predicted and controlled-A critical issue today because the death of Moore's law for computer clock speed [69] implies that high-performance computing on large problems is limited by the communication bandwidth between processors rather than the number of floating point operations [70]. Indeed, The rapid increase in parallel computing has also seen a resurgence of interest in AC methods since 2004, e.g., [71][72][73].…”

Section: Recent Development Of the Artificial Compressibility Methodsmentioning

confidence: 99%

“…Consistent with this goal, the method uses "no-neighbour" spatial interpolation, which ensures that a computational element only needs to know values on its adjacent faces and the faces only need to know the adjacent elements; i.e., the discretization of an element does not include a neighbour element and the discretization of a face does not include a neighbour face [31]. The no-neighbour approach inherently limits a code to 1st and 2nd-order spatial discretizations, but reduces the communication burden associated with decomposing a system for parallel computing [70]. Arguably, the PipeAC method could be improved in its ability to handle abrupt transitions by inclusion of higher-order discretization methods, but that would increase the communication burden in the parallel network model that is under development.…”

Section: Implications For Large-scale Network Modelsmentioning

confidence: 99%

An Artificial Compressibility Method for 1D Simulation of Open-Channel and Pressurized-Pipe Flow

Hodges

2020

Water

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Piping systems (e.g., storm sewers) that transition between free-surface flow and surcharged flow are challenging to model in one-dimensional (1D) networks as the continuity equation changes from hyperbolic to elliptic as the water surface reaches the pipe ceiling. Previous network models are known to have poor mass conservation or unpredictable convergence behavior at such transitions. To address this problem, a new algorithm is developed for simulating unsteady 1D flow in closed conduits with both free-surface and surcharged flow. The shallow-water (hydrostatic) approximation is used as the governing equations. The artificial compressibility (AC) method is implemented as a dual-time-stepping discretization for a finite-volume solver with timescale interpolation used for face reconstruction. A new formulation for the AC celerity parameter is proposed such that the AC celerity matches the equivalent gravity wave speed for the local hydraulic head—which has some similarities to the classic Preissmann Slot used to approximate pressurized flow in conduits. The new approach allows the AC celerity to be set locally by the flow (i.e., non-uniform in space) and removes it as a free parameter of the AC solution method. The derivation of the AC method provides for only a minor change in the form of the solution equations when a computational element switches from free-surface to surcharged. The new solver is tested for both unsteady free-surface (supercritical, subcritical) and surcharged flow transitions in a circular pipe and is implemented in an open-source Python code available under the name “PipeAC.” The results are compared to laboratory experiments that include rapid flow changes due to opening/closing of gates. Results show that the new algorithm is satisfactory for 1D representation of unsteady transition behavior with two caveats: (i) sufficient grid resolution must be applied, and (ii) the shallow-water equation approximations (hydrostatic, single-fluid) limit the accuracy of the solution with regards to the celerity of the turbulent unsteady bore that propagates upstream. This research might benefit any piping network model that must smoothly handle unsteady transitions from free surface to surcharged flow.

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“…Again, one main challenge is associated with the high computational costs to effectively transform ensemble streamflow projections into ensemble surface inundation projections through hydrodynamic models. With the enhanced inundation models and high performance computing (HPC) capabilities (Morales-Hernández et al, 2020a), this challenge can be gradually overcome for more spatially explicit flood vulnerability assessment.…”

Section: Introductionmentioning

confidence: 99%

“…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 (seeMorales-Hernández et al, (2020b), for further model details).An evaluation of TRITON performance for the CRW is presented and discussed in Section 3.3. TRITON's input data includes digital elevation model (DEM), surface roughness, initial depths, flow hydrographs, and inflow source locations(Kalyanapu et al, 2011;Marshall et al, 2018;Morales-Hernández et al, 2020a;Morales-Hernández et al, 2020b). In this study, the hydraulic and geometric parameters from the flood model evaluation section (Section 3.3) were used in the flood simulation.…”

mentioning

confidence: 99%

Assessing Climate Change-Induced Flood Risk in the Conasauga River Watershed: An Application of Ensemble Hydrodynamic Inundation Modeling

Dullo¹,

Gangrade²,

Morales-Hernändez³

et al. 2020

Preprint

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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) eleven 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. Nine out of the eleven 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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High-performance computing in water resources hydrodynamics

Cited by 39 publications

References 15 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

An Artificial Compressibility Method for 1D Simulation of Open-Channel and Pressurized-Pipe Flow

Assessing Climate Change-Induced Flood Risk in the Conasauga River Watershed: An Application of Ensemble Hydrodynamic Inundation Modeling

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