High-performance computing in water resources hydrodynamics

M. Morales-Hernández; M. B. Sharif; S. Gangrade; T. T. Dullo; S. C. Kao; A. Kalyanapu; S. K. Ghafoor; K. J. Evans; E. Madadi-Kandjani; B. R. Hodges

doi:10.2166/hydro.2020.163

High-performance computing in water resources hydrodynamics

M. Morales-Hernández, M. B. Sharif, S. Gangrade, T. T. Dullo, S. C. Kao, A. Kalyanapu, S. K. Ghafoor, K. J. Evans, E. Madadi-Kandjani, B. R. Hodges

Research output: Contribution to journal › Article › peer-review

33 Scopus citations

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.

Original language	English
Pages (from-to)	1217-1235
Number of pages	19
Journal	Journal of Hydroinformatics
Volume	22
Issue number	5
DOIs	https://doi.org/10.2166/hydro.2020.163
State	Published - Sep 1 2020

Funding

co-authors are employees of the Oak Ridge National Laboratory, managed by UT Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. The publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript or allow others to do so, for U.S. Government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/ doe-public-access-plan). This article was supported by the U.S. Air Force Numerical Weather Modeling Program to the Oak Ridge National Laboratory (M.M.-H., M.B.S., S.G., T.T.D., S.C.K., A.K., S.K.G., and K.J.E.), as well as by the U.S. Environmental Protection Agency (EPA) under Cooperative Agreement No. 83595001 awarded the University of Texas at Austin (E.M.-K. and B.R.H.). This article has not been formally reviewed by the EPA.

Funders	Funder number
U.S. Department of Energy
U.S. Environmental Protection Agency	83595001
Battelle	DE-AC05-00OR22725
Oak Ridge National Laboratory
U.S. Air Force
University of Texas at Austin

Keywords

GPU
HPC
Parallel codes
Water resources hydrodynamics

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10.2166/hydro.2020.163

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AU - Kalyanapu, A.

AU - Ghafoor, S. K.

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AU - Madadi-Kandjani, E.

AU - Hodges, B. R.

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AB - 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.

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High-performance computing in water resources hydrodynamics

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