A GPU-Accelerated Full 2D Shallow Water Model Using an Edge Loop Method on Unstructured Meshes: Implementation and Performance Analysis

Liping Ma, Jijian Lian, Jingming Hou, Dawei Zhang and Xiaoqun Wang ()
Additional contact information
Liping Ma: Tianjin University
Jijian Lian: Tianjin University
Jingming Hou: Xi’an University of Technology
Dawei Zhang: China Institute of Water Resources and Hydropower Research
Xiaoqun Wang: Tianjin University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2024, vol. 38, issue 2, No 17, 733-752

Abstract: Abstract Flood-induced disasters can cause significant harm and economic losses. Using numerical simulations to provide real-time predictions of flood events is an effective method to address this issue. To develop a high-efficiency and adaptable tool for fast flood prediction in complex terrains, this work utilizes Graphic Processing Units (GPUs) to accelerate a full 2D shallow water model on unstructured meshes. Furthermore, a novel Edge Loop Method (ELM) based on the winged-edge data structure is applied to the model to improve the computational efficiency of solving fluxes. A benchmark test and a real-world dam-break case were simulated to verify the accuracy and performance of the current model. The results demonstrate that the ELM accelerates the model by 2.51 and 4.08 times compared to the eight-core CPU-based model, and 14.97 and 19.84 times compared to the single-core CPU-based model in two cases. Notably, when compared to the GPU-based model using the Cell Loop Method (CLM), the computational efficiency of the ELM is improved by 18.34% and 24.29%, respectively. In particular, a quantitative analysis of the performance explains the advantage of the ELM from the perspective of its implementation mechanism, further demonstrating that the ELM exhibits higher computational efficiency as the total number of cells increases. Based on the advantages of high efficiency in the GPU-based model using the ELM, the proposed model can effectively forecast real-world flood events in regions characterized by complex terrains.

Keywords: 2D hydrodynamic model; Edge loop method; Unstructured meshes; GPU; Fast flood forecasts (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11269-023-03696-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:38:y:2024:i:2:d:10.1007_s11269-023-03696-6

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-023-03696-6

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().