The multi-GPU Wetland DEM Ponding Model

IF 4.2 2区 地球科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Geosciences Pub Date : 2025-03-11 DOI:10.1016/j.cageo.2025.105912
Tonghe Liu , Sean J. Trim , Seok-Bum Ko , Raymond J. Spiteri
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引用次数: 0

Abstract

The Wetland DEM (Digital Elevation Model) Ponding Model (WDPM) is software that simulates how runoff water is distributed across the Canadian Prairies. Previous versions of the WDPM are able to run in parallel with a single CPU or GPU. Now that multi-device parallel computing has become an established method to increase computational throughput and efficiency, this study extends WDPM to a multi-GPU parallel algorithm with efficient data transmission methods via overlapping communication with computation. The new implementation is evaluated from several perspectives. First, the output summary and system are compared with the previous implementation to verify correctness and demonstrate convergence. Second, the multi-GPU code is profiled, showing that the algorithm carries out efficient data synchronization through optimized techniques. Finally, the new implementation was tested experimentally and showed improved performance and good scaling. Specifically, a speedup of 2.39 was achieved when using four GPUs compared to using one GPU.
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来源期刊
Computers & Geosciences
Computers & Geosciences 地学-地球科学综合
CiteScore
9.30
自引率
6.80%
发文量
164
审稿时长
3.4 months
期刊介绍: Computers & Geosciences publishes high impact, original research at the interface between Computer Sciences and Geosciences. Publications should apply modern computer science paradigms, whether computational or informatics-based, to address problems in the geosciences.
期刊最新文献
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