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Title: Analysis of the performance of a hybrid CPU/GPU 1D2D coupled model for real flood cases

Abstract

Coupled 1D2D models emerged as an efficient solution for a two-dimensional (2D) representation of the floodplain combined with a fast one-dimensional (1D) schematization of the main channel. At the same time, high-performance computing (HPC) has appeared as an efficient tool for model acceleration. In this work, a previously validated 1D2D Central Processing Unit (CPU) model is combined with an HPC technique for fast and accurate flood simulation. Due to the speed of 1D schemes, a hybrid CPU/GPU model that runs the 1D main channel on CPU and accelerates the 2D floodplain with a Graphics Processing Unit (GPU) is presented. Since the data transfer between sub-domains and devices (CPU/GPU) may be the main potential drawback of this architecture, the test cases are selected to carry out a careful time analysis. Here, the results reveal the speed-up dependency on the 2D mesh, the event to be solved and the 1D discretization of the main channel. Additionally, special attention must be paid to the time step size computation shared between sub-models. In spite of the use of a hybrid CPU/GPU implementation, high speed-ups are accomplished in some cases.

Authors:
 [1]; ORCiD logo [2];  [3];  [3]
  1. Universidad de Zaragoza (Spain); Hydronia Europe, Madrid (Spain)
  2. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
  3. Universidad de Zaragoza (Spain)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1669740
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Hydroinformatics
Additional Journal Information:
Journal Volume: 22; Journal Issue: 5; Journal ID: ISSN 1464-7141
Country of Publication:
United States
Language:
English
Subject:
Coupled model; flood; hybrid GPU; shallow water; simulation

Citation Formats

Echeverribar, Isabel, Morales-Hernández, Mario, Brufau, Pilar, and García-Navarro, Pilar. Analysis of the performance of a hybrid CPU/GPU 1D2D coupled model for real flood cases. United States: N. p., 2020. Web. doi:10.2166/hydro.2020.032.
Echeverribar, Isabel, Morales-Hernández, Mario, Brufau, Pilar, & García-Navarro, Pilar. Analysis of the performance of a hybrid CPU/GPU 1D2D coupled model for real flood cases. United States. doi:10.2166/hydro.2020.032.
Echeverribar, Isabel, Morales-Hernández, Mario, Brufau, Pilar, and García-Navarro, Pilar. Thu . "Analysis of the performance of a hybrid CPU/GPU 1D2D coupled model for real flood cases". United States. doi:10.2166/hydro.2020.032.
@article{osti_1669740,
title = {Analysis of the performance of a hybrid CPU/GPU 1D2D coupled model for real flood cases},
author = {Echeverribar, Isabel and Morales-Hernández, Mario and Brufau, Pilar and García-Navarro, Pilar},
abstractNote = {Coupled 1D2D models emerged as an efficient solution for a two-dimensional (2D) representation of the floodplain combined with a fast one-dimensional (1D) schematization of the main channel. At the same time, high-performance computing (HPC) has appeared as an efficient tool for model acceleration. In this work, a previously validated 1D2D Central Processing Unit (CPU) model is combined with an HPC technique for fast and accurate flood simulation. Due to the speed of 1D schemes, a hybrid CPU/GPU model that runs the 1D main channel on CPU and accelerates the 2D floodplain with a Graphics Processing Unit (GPU) is presented. Since the data transfer between sub-domains and devices (CPU/GPU) may be the main potential drawback of this architecture, the test cases are selected to carry out a careful time analysis. Here, the results reveal the speed-up dependency on the 2D mesh, the event to be solved and the 1D discretization of the main channel. Additionally, special attention must be paid to the time step size computation shared between sub-models. In spite of the use of a hybrid CPU/GPU implementation, high speed-ups are accomplished in some cases.},
doi = {10.2166/hydro.2020.032},
journal = {Journal of Hydroinformatics},
number = 5,
volume = 22,
place = {United States},
year = {2020},
month = {7}
}

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