The multi-GPU Wetland DEM Ponding Model

IF 4.1 2区 地球科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Geosciences Pub Date : 2025-05-01 Epub 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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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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多gpu湿地DEM池塘模型
湿地DEM(数字高程模型)池塘模型(WDPM)是一个模拟径流水如何分布在加拿大大草原上的软件。以前版本的WDPM能够与单个CPU或GPU并行运行。现在多设备并行计算已经成为提高计算吞吐量和效率的一种既定方法,本研究将WDPM扩展为一种多gpu并行算法,通过与计算的重叠通信,具有高效的数据传输方法。新的实现将从几个角度进行评估。首先,将输出摘要和系统与之前的实现进行比较,验证其正确性和收敛性。其次,对多gpu代码进行了分析,表明该算法通过优化技术实现了高效的数据同步。最后,对新实现进行了实验测试,显示出性能的提高和良好的可扩展性。具体来说,与使用一个GPU相比,使用四个GPU的速度提高了2.39。
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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.
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