scholarly journals A high-performance integrated hydrodynamic modelling system for urban flood simulations

2015 ◽  
Vol 17 (4) ◽  
pp. 518-533 ◽  
Author(s):  
Qiuhua Liang ◽  
Luke S. Smith
Keyword(s):  
High Resolution ◽  
Graphics Processing Units ◽  
High Performance ◽  
Large Scale ◽  
Surface Flow ◽  
Source Surface ◽  
Hydrodynamic Modelling ◽  
Flood Inundation ◽  
Urban Flood ◽  
Modelling System

A new High-Performance Integrated hydrodynamic Modelling System (Hi-PIMS) is tested for urban flood simulation. The software solves the two-dimensional shallow water equations using a first-order accurate Godunov-type shock-capturing scheme incorporated with the Harten, Lax and van Leer approximate Riemann solver with the contact wave restored (HLLC) for flux evaluation. The benefits of modern graphics processing units are explored to accelerate large-scale high-resolution simulations. In order to test its performance, the tool is applied to predict flood inundation due to rainfall and a point source surface flow in Glasgow, Scotland, and a hypothetical inundation event at different spatial resolutions in Thamesmead, England, caused by embankment failure. Numerical experiments demonstrate potential benefits for high-resolution modelling of urban flood inundation, and a much-improved level of performance without compromising result quality.

scholarly journals A lightweight approach to performance portability with targetDP

2016 ◽  
Vol 32 (2) ◽  
pp. 288-301
Author(s):  
Alan Gray ◽  
Kevin Stratford
Keyword(s):  
Particle Physics ◽  
Message Passing ◽  
Graphics Processing Units ◽  
High Performance ◽  
Large Scale ◽  
Message Passing Interface ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Performance Portability ◽  
Graphics Processing

Leading high performance computing systems achieve their status through use of highly parallel devices such as NVIDIA graphics processing units or Intel Xeon Phi many-core CPUs. The concept of performance portability across such architectures, as well as traditional CPUs, is vital for the application programmer. In this paper we describe targetDP, a lightweight abstraction layer which allows grid-based applications to target data parallel hardware in a platform agnostic manner. We demonstrate the effectiveness of our pragmatic approach by presenting performance results for a complex fluid application (with which the model was co-designed), plus separate lattice quantum chromodynamics particle physics code. For each application, a single source code base is seen to achieve portable performance, as assessed within the context of the Roofline model. TargetDP can be combined with Message Passing Interface (MPI) to allow use on systems containing multiple nodes: we demonstrate this through provision of scaling results on traditional and graphics processing unit-accelerated large scale supercomputers.

scholarly journals Retrospective Dynamic Inundation Mapping of Hurricane Harvey Flooding in the Houston Metropolitan Area Using High-Resolution Modeling and High-Performance Computing

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 597 ◽  
Author(s):  
Seong Noh ◽  
Jun-Hak Lee ◽  
Seungsoo Lee ◽  
Dong-Jun Seo
Keyword(s):  
High Resolution ◽  
Metropolitan Area ◽  
High Performance ◽  
Extreme Rainfall ◽  
Extreme Weather Events ◽  
Urban Flood ◽  
Precipitation Estimates ◽  
Inundation Extent ◽  
Quantitative Precipitation Estimates ◽  
Houston Metropolitan Area

Hurricane Harvey was one of the most extreme weather events to occur in Texas, USA; there was a huge amount of urban flooding in the city of Houston and the adjoining coastal areas. In this study, we reanalyze the spatiotemporal evolution of inundation during Hurricane Harvey using high-resolution two-dimensional urban flood modeling. This study’s domain includes the bayou basins in and around the Houston metropolitan area. The flood model uses the dynamic wave method and terrain data of 10-m resolution. It is forced by radar-based quantitative precipitation estimates. To evaluate the simulated inundation, on-site photos and water level observations were used. The inundation extent and severity are estimated by combining the retrieved water depths, images collected from the impacted area, and high-resolution terrain data. The simulated maximum inundation extent, which is frequently found outside of the designated flood zones, points out the importance of capturing multi-scale hydrodynamics in the built environment under extreme rainfall for effective flood risk and emergency management.

High-performance computing for computational modelling in built environment-related studies – a scientometric review

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emmanuel Imuetinyan Aghimien ◽  
Lerato Millicent Aghimien ◽  
Olutomilayo Olayemi Petinrin ◽  
Douglas Omoregie Aghimien
Keyword(s):  
High Performance Computing ◽  
Graphics Processing Units ◽  
High Performance ◽  
Large Scale ◽  
Computational Models ◽  
Computational Modelling ◽  
Scientometric Analysis ◽  
Content Type ◽  
Performance Computing ◽  
Aec Industry

Purpose This paper aims to present the result of a scientometric analysis conducted using studies on high-performance computing in computational modelling. This was done with a view to showcasing the need for high-performance computers (HPC) within the architecture, engineering and construction (AEC) industry in developing countries, particularly in Africa, where the use of HPC in developing computational models (CMs) for effective problem solving is still low. Design/methodology/approach An interpretivism philosophical stance was adopted for the study which informed a scientometric review of existing studies gathered from the Scopus database. Keywords such as high-performance computing, and computational modelling were used to extract papers from the database. Visualisation of Similarities viewer (VOSviewer) was used to prepare co-occurrence maps based on the bibliographic data gathered. Findings Findings revealed the scarcity of research emanating from Africa in this area of study. Furthermore, past studies had placed focus on high-performance computing in the development of computational modelling and theory, parallel computing and improved visualisation, large-scale application software, computer simulations and computational mathematical modelling. Future studies can also explore areas such as cloud computing, optimisation, high-level programming language, natural science computing, computer graphics equipment and Graphics Processing Units as they relate to the AEC industry. Research limitations/implications The study assessed a single database for the search of related studies. Originality/value The findings of this study serve as an excellent theoretical background for AEC researchers seeking to explore the use of HPC for CMs development in the quest for solving complex problems in the industry.

High-resolution glacial lake outburst flood impact evaluation using high-performance hydrodynamic modelling and open-source data

2020 ◽  
Author(s):  
Huili Chen ◽  
Qiuhua Liang ◽  
Jiaheng Zhao ◽  
Xilin Xia
Keyword(s):  
High Resolution ◽  
Open Source ◽  
Impact Evaluation ◽  
High Performance ◽  
Glacial Lake ◽  
Hydrodynamic Modelling ◽  
Glacial Lakes ◽  
Open Source Data ◽  
Source Data ◽  
Simulation Results

<p>Glacial lake outburst floods (GLOFs) are one of the major natural hazards in certain populated mountainous areas, e.g. the Himalayan region, which may lead to catastrophic consequences including fatalities. Evaluating the potential socio-economic impact of GLOFs is essential for mitigating the risk of GLOFs and enhancing community resilience. Yet in most of the cases, the impact evaluation of potential GLOFs is confronted with limited data availability and inaccessibility to most of the glacial lakes in the high-altitude areas. This study aims to exploit recent advances in Earth Observation (EO), open-source data from different sources, and high-performance hydrodynamic modelling to innovate an approach for GLOF risk and impact assessment. GLOF scenarios of different glacier dam breach width and depth are designed according to high-resolution aerial imagery and terrain data acquired from unmanned aerial vehicle surveying. High-performance hydrodynamic model supported by open-source multi-resolution data from the latest EO technologies is used to simulate the flood hydrodynamics to provide spatial and temporal flood characteristics. Detailed information on communities and infrastructure systems is collected and processed from multiple sources including OpenStreetMap, Google Earth, and global data products to support impact analysis. The evaluation framework is applied to Tsho Rolpa glacial lake in Nepal, which has been identified as one of the potentially dangerous glacial lakes that may create GLOFs to threaten the downstream communities and infrastructure. According to the simulation results, the worst GLOF scenario can potentially inundate 27 villages, 583 buildings and 20.8 km<sup>2</sup> of agricultural areas, and pose high risk to 1 airport, 1 hydro power plant, 3 bus stations, and 21 bridges. Additionally, the spatial and temporal flood simulation results, including water depth, flow velocity and flood arrival time may help identify impacted sites and objects, which would be valuable for the development of evacuation plans and early warning systems.</p>

scholarly journals High-performance computing in water resources hydrodynamics

2020 ◽  
Vol 22 (5) ◽  
pp. 1217-1235 ◽  
Author(s):  
M. Morales-Hernández ◽  
M. B. Sharif ◽  
S. Gangrade ◽  
T. T. Dullo ◽  
S.-C. Kao ◽  
...  
Keyword(s):  
Water Resources ◽  
High Performance Computing ◽  
Graphics Processing Units ◽  
High Performance ◽  
Large Scale ◽  
Test Case ◽  
Processing Unit ◽  
Central Processing ◽  
Graphics Processing ◽  
Performance Computing

Abstract This work presents a vision of future water resources hydrodynamics codes that can fully utilize the strengths of modern high-performance computing (HPC). The advances to computing power, formerly driven by the improvement of central processing unit processors, now focus on parallel computing and, in particular, the use of graphics processing units (GPUs). However, this shift to a parallel framework requires refactoring the code to make efficient use of the data as well as changing even the nature of the algorithm that solves the system of equations. These concepts along with other features such as the precision for the computations, dry regions management, and input/output data are analyzed in this paper. A 2D multi-GPU flood code applied to a large-scale test case is used to corroborate our statements and ascertain the new challenges for the next-generation parallel water resources codes.

scholarly journals High-Performance Integrated hydrodynamic Modelling of Storm Induced Floods at a Catchment Scale

10.29007/tt1x ◽  
2018 ◽  
Author(s):  
Xilin Xia ◽  
Qiuhua Liang ◽  
Xiaodong Ming
Keyword(s):  
Real Time ◽  
High Performance ◽  
Large Scale ◽  
Hydrodynamic Modelling ◽  
Hydrological Models ◽  
Graphic Processing Units ◽  
Catchment Scale ◽  
Promising Tool ◽  
Inundation Extent ◽  
The Uk

Flooding is one of the most common types of natural hazards. The current practice of large-scale fluvial flood modelling relies on the use of hydrological models to predict upstream discharge hydrograph to drive inundation modelling at downstream. However, the oversimplified representation of both catchment topographies and hydraulics make hydrological models heavily rely on model parameterisation and calibration. This makes the modelling strategy unsuitable for prediction of extreme events featured with highly transient hydraulic processes, for which high-quality hydrological data is commonly missing to support model parameterisation and calibration. In this paper, the High-Performance Integrated hydrodynamic Modelling System (HiPIMS) has been adapted and applied to the whole 2500 km2 Eden catchment in the UK to reproduce the flood event caused by Storm Desmond in December, 2015. Without necessity of intensive calibration and using hydrographs as boundary conditions, satisfactory results have been obtained for both inundation extent and water level time series in channels, in comparison with observations. Accelerated by multiple modern graphic processing units (GPUs), the model runs more than 20 times faster than real time for the simulation of the whole catchment at 20m resolution. The results successfully demonstrate HiPIMS as a promising tool for real-time flood forecasting and flood risk assessment.

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