Integration of FULLSWOF2D and PeanoClaw: Adaptivity and Local Time-Stepping for Complex Overland Flows

Unterweger, Kristof; Wittmann, R.; Neumann, Philipp; Weinzierl, Tobias; Bungartz, Hans‐Joachim

doi:10.1007/978-3-319-22997-3_11

Cited by 9 publications

(14 citation statements)

References 13 publications

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“…Popinet [33] demonstrates that adaptivity even lowers the overall complexity of simulations, as the number of cells only grows as ∆ −1.4 with the mesh size ∆. Benefits of adaptivity were also shown for the case of storm surges [22] and overland flooding [40], which may also be modelled via the shallow water equations.…”

Section: Related Workmentioning

confidence: 91%

“…Similarly, top-down approaches that combine octree-type grids with regularly refined patches as leaves of the tree have become attractive. Examples include the packages ForestClaw [9] and Peano [40], for which performance improvements via patches are especially discussed in [43]. The framework Daino offers octree AMR with patches on heterogeneous GPU platforms [42].…”

Section: Related Workmentioning

confidence: 99%

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Load Balancing and Patch-Based Parallel Adaptive Mesh Refinement for Tsunami Simulation on Heterogeneous Platforms Using Xeon Phi Coprocessors

Ferreira

Bäder

2017

Proceedings of the Platform for Advanced Scientific Computing Conference

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We present a patch-based approach for tsunami simulation with parallel adaptive mesh refinement on the Salomon supercomputer. The special architecture of Salomon, with two Intel Xeon CPUs (Haswell architecture) and two Intel Xeon Phi coprocessors (Knights Corner) per compute node, suggests truly heterogeneous load balancing instead of offload approaches, because host and accelerator achieve comparable performance for our simulations. We use a tree-structured mesh refinement strategy resulting from newest-vertex bisection of triangular grid cells, but introduce small uniform grid patches into the leaves of the tree to allow vectorisation of the Finite Volume solver over grid cells. In particular, we implemented vectorised versions of the approximate Riemann solvers, exploiting Fortran's array notations where possible. While large patches increase computational performance due to vectorisation, improved memory access and reduced meshing overhead, they also increase the overall number of processed cells. Thus, a trade-off must be found regarding the patch size. We experimented with different patch sizes in a study of the time-to-solution of a simulation of the 2011 Tohoku tsunami, and found that relatively small patches with 8 2 cells resulted in the smallest execution times. We use the Xeon Phis in symmetric mode and apply heterogeneous load balancing between hosts and coprocessors, identifying the relative load distribution either from on-the-fly runtime measurements or from a priori exhaustive testing. Both approaches perform better than homogeneous load balancing and better than using only the CPUs or only the Xeon Phi coprocessors in native mode. In all setups , however, the absolute speedups are impeded by the slow MPI communication between Xeon Phi coprocessors. CCS CONCEPTS • Mathematics of computing → Mathematical software performance; Partial differential equations; • Computing methodologies → Massively parallel and high-performance simulations; Vector / streaming algorithms; • Applied computing → Earth and atmospheric sciences;

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Section: Related Workmentioning

confidence: 91%

Section: Related Workmentioning

confidence: 99%

Load Balancing and Patch-Based Parallel Adaptive Mesh Refinement for Tsunami Simulation on Heterogeneous Platforms Using Xeon Phi Coprocessors

Ferreira

Bäder

2017

Proceedings of the Platform for Advanced Scientific Computing Conference

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“…where R (m/s) is the rainfall intensity; I (m/s) is the infiltration rate; h (m) is the cell water height (depth); z (m) is the cell topography elevation; u (m/s) and v (m/s) are the cell depth-averaged velocities in x and y directions, respectively; S fx and S fy are the cell friction slopes in x and y directions, respectively; g (m/s 2 ) is gravity acceleration; t (s) is time. The FullSWOF_2D program fully solves SWEs on a structured mesh in two space dimensions using the finite volume method (FVM) which ensures mass conservation compared to the finite difference method (FDM) [34]. A well-balanced scheme was adapted to guarantee the positivity of water depth and the preservation of steady states for specific hydrological features such as during wet-dry transitions and tiny water depth [30,35].…”

Section: Shallow Water Equations (Swes) and Fullswof_2dmentioning

confidence: 99%

“…The parallelization strategies of FullSWOF_2D were also examined to improve its simulation efficiency dealing with large-scale cases [35]. A modified bi-layer (crust-and soil-layer) Green-Ampt (GA) infiltration model [36] to calculate I for Equation (1) was coupled in the FullSWOF_2D [34] which enables the program to simulate overland flow on impervious and pervious surfaces.…”

Section: Shallow Water Equations (Swes) and Fullswof_2dmentioning

confidence: 99%

Estimating Time of Concentration for Overland Flow on Pervious Surfaces by Particle Tracking Method

Fang

et al. 2018

Water

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The particle tracking method (PTM) module was added into the open source Full Shallow-Water equations for Overland Flow in a two-dimensional (FullSWOF_2D) program, which has coupled rainfall-runoff and infiltration modules to determine the time of concentration (T c ) for impervious (T ci ) and pervious (T cp ) surfaces. The updated program FullSWOF-PTM was tested using observed rainfall events with Nash-Sutcliffe efficiencies ranging from 0.60 to 0.95 (average of 0.75) for simulated runoff hydrographs. More than 400 impervious modeling cases with different surface slope (S 0 ), roughness coefficient (n), length (L), and rainfall intensity (i) combinations were developed and simulated to obtain the T ci for developing the regression equation of T ci as a function of the four input parameters. More than 700 pervious modeling cases with different combinations of S 0 , n, L, i, and infiltration parameters including the saturated hydraulic conductivity, suction head, and moisture deficit were simulated to estimate the T cp based on the travel time of 85% of particles arriving at the outlet and the ponding time. The regression equation of T cp was developed as the sum of T ci and additional travel time as a function of infiltration parameters and i. The T cp equation can be applied to wide ranges of input parameters in comparison to Akan's equation.

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“…Adaptive mesh refinement (AMR) is a key ingredient in many application domains [6,8,10,12,15,16,22]. It allows to resolve "areas of interest", such as wave fronts, shocks or (moving) boundaries with a fine mesh while allowing a Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.…”

Section: Introductionmentioning

confidence: 99%

Asagi

Rettenberger

Meister

Bäder

et al. 2016

Proceedings of the Exascale Applications and Software Conference 2016

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We present ASAGI, an open-source library with a simple interface to access Cartesian material and geographic datasets in massively parallel simulations with dynamically adaptive mesh refinement (AMR). ASAGI distributes geographic datasets over all compute nodes storing only a portion of the dataset on each node. An automatic replication mechanism copies the data between nodes to assure fast local access even after load migration in the application. We demonstrate ASAGI's preparedness for up-to-petascale simulations in three use cases. We simulate a Tsunami on 512 cores and a porous media flow on up to 8,192 cores of SuperMUC with the AMR framework sam(oa) 2. We also run an earthquake simulation with SeiSol on 65,536 cores. For all applications, ASAGI provides large complex 3D material datasets required for the realistic scenarios. The NUMA-awareness of ASAGI turned out to be especially useful for the hybrid MPI+OpenMP parallelization of both codes. CCS Concepts •Computing methodologies → Massively parallel and high-performance simulations; •Applied computing → Earth and atmospheric sciences; •Theory of computation → Massively parallel algorithms;

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Integration of FULLSWOF2D and PeanoClaw: Adaptivity and Local Time-Stepping for Complex Overland Flows

Cited by 9 publications

References 13 publications

Load Balancing and Patch-Based Parallel Adaptive Mesh Refinement for Tsunami Simulation on Heterogeneous Platforms Using Xeon Phi Coprocessors

Load Balancing and Patch-Based Parallel Adaptive Mesh Refinement for Tsunami Simulation on Heterogeneous Platforms Using Xeon Phi Coprocessors

Estimating Time of Concentration for Overland Flow on Pervious Surfaces by Particle Tracking Method

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