Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures

Md Bulbul Sharif; Sheikh K. Ghafoor; Thomas M. Hines; Mario Morales-Hernändez; Katherine J. Evans; Shih Chieh Kao; Alfred J. Kalyanapu; Tigstu T. Dullo; Sudershan Gangrade

doi:10.1145/3394277.3401852

Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures

Md Bulbul Sharif, Sheikh K. Ghafoor, Thomas M. Hines, Mario Morales-Hernändez, Katherine J. Evans, Shih Chieh Kao, Alfred J. Kalyanapu, Tigstu T. Dullo, Sudershan Gangrade

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

This paper describes the implementation of a two-dimensional hydrodynamic flood model with two different numerical schemes on heterogeneous high-performance computing architectures. Both schemes were able to solve the nonlinear hyperbolic shallow water equations using an explicit upwind first-order approach on finite differences and finite volumes, respectively, and were conducted using MPI and CUDA. Four different test cases were simulated on the Summit supercomputer at Oak Ridge National Laboratory. Both numerical schemes scaled up to 128 nodes (768 GPUs) with a maximum 98.2x speedup of over 1 GPU. The lowest run time for the 10 day Hurricane Harvey event simulation at 5 meter resolution (272 million grid cells) was 50 minutes. GPUDirect communication proved to be more convenient than the standard communication strategy. Both strong and weak scaling are shown.

Original language	English
Title of host publication	Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450379939
DOIs	https://doi.org/10.1145/3394277.3401852
State	Published - Jun 29 2020
Event	7th Annual Platform for Advanced Scientific Computing Conference, PASC 2020 - Geneva, Switzerland Duration: Jun 29 2020 → Jul 1 2020

Publication series

Name	Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020

Conference

Conference	7th Annual Platform for Advanced Scientific Computing Conference, PASC 2020
Country/Territory	Switzerland
City	Geneva
Period	06/29/20 → 07/1/20

Funding

This research was supported by the US Air Force Numerical Weather Modeling Program and the Center of Management, Utilization, and Protection of Water Resources at Tennessee Technological University. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory. Some of the co-authors are employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy. Accordingly, the US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript or allow others to do so, for US 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).

Keywords

2D flood model
CUDA
Flood simulation
GPU programming
High-performance computing
Multi-GPU

Access to Document

10.1145/3394277.3401852

Cite this

Sharif, M. B., Ghafoor, S. K., Hines, T. M., Morales-Hernändez, M., Evans, K. J., Kao, S. C., Kalyanapu, A. J., Dullo, T. T., & Gangrade, S. (2020). Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures. In Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020 (Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020). Association for Computing Machinery. https://doi.org/10.1145/3394277.3401852

Sharif, Md Bulbul ; Ghafoor, Sheikh K. ; Hines, Thomas M. et al. / Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures. Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020. Association for Computing Machinery, 2020. (Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020).

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title = "Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures",

abstract = "This paper describes the implementation of a two-dimensional hydrodynamic flood model with two different numerical schemes on heterogeneous high-performance computing architectures. Both schemes were able to solve the nonlinear hyperbolic shallow water equations using an explicit upwind first-order approach on finite differences and finite volumes, respectively, and were conducted using MPI and CUDA. Four different test cases were simulated on the Summit supercomputer at Oak Ridge National Laboratory. Both numerical schemes scaled up to 128 nodes (768 GPUs) with a maximum 98.2x speedup of over 1 GPU. The lowest run time for the 10 day Hurricane Harvey event simulation at 5 meter resolution (272 million grid cells) was 50 minutes. GPUDirect communication proved to be more convenient than the standard communication strategy. Both strong and weak scaling are shown.",

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author = "Sharif, \{Md Bulbul\} and Ghafoor, \{Sheikh K.\} and Hines, \{Thomas M.\} and Mario Morales-Hern{\"a}ndez and Evans, \{Katherine J.\} and Kao, \{Shih Chieh\} and Kalyanapu, \{Alfred J.\} and Dullo, \{Tigstu T.\} and Sudershan Gangrade",

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year = "2020",

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doi = "10.1145/3394277.3401852",

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Sharif, MB, Ghafoor, SK, Hines, TM, Morales-Hernändez, M, Evans, KJ , Kao, SC, Kalyanapu, AJ, Dullo, TT & Gangrade, S 2020, Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures. in Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020. Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020, Association for Computing Machinery, 7th Annual Platform for Advanced Scientific Computing Conference, PASC 2020, Geneva, Switzerland, 06/29/20. https://doi.org/10.1145/3394277.3401852

Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures. / Sharif, Md Bulbul; Ghafoor, Sheikh K.; Hines, Thomas M. et al.
Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020. Association for Computing Machinery, 2020. (Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Evans, Katherine J.

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AU - Gangrade, Sudershan

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AB - This paper describes the implementation of a two-dimensional hydrodynamic flood model with two different numerical schemes on heterogeneous high-performance computing architectures. Both schemes were able to solve the nonlinear hyperbolic shallow water equations using an explicit upwind first-order approach on finite differences and finite volumes, respectively, and were conducted using MPI and CUDA. Four different test cases were simulated on the Summit supercomputer at Oak Ridge National Laboratory. Both numerical schemes scaled up to 128 nodes (768 GPUs) with a maximum 98.2x speedup of over 1 GPU. The lowest run time for the 10 day Hurricane Harvey event simulation at 5 meter resolution (272 million grid cells) was 50 minutes. GPUDirect communication proved to be more convenient than the standard communication strategy. Both strong and weak scaling are shown.

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Sharif MB, Ghafoor SK, Hines TM, Morales-Hernändez M, Evans KJ , Kao SC et al. Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures. In Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020. Association for Computing Machinery. 2020. (Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2020). doi: 10.1145/3394277.3401852

Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures

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