A highly scalable high-performance Lagrangian transport and diffusion model for marine pollutants assessment

R. Montella, D. Di Luccio, Ciro Giuseppe de Vita, Gennaro Mellone, M. Lapegna, Gloria Ortega, L. Marcellino, E. Zambianchi, G. Giunta
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Abstract

While using High-Performance Computing (HPC) for precise and accurate air quality forecasts is a common issue, similar services devoted to marine pollution in coastal areas remain challenging. This paper presents Water quality Community Model Plus Plus (WaComM++) leveraging a parallelization schema enabling the users to run it on heterogeneous parallel architectures. We evaluated the proposed model under several execution approaches using a real-world application for pollutants forecast in the Gulf of Napoli (Campania, Italy). As a result, WaComM++ has produced results 657K times faster than the sequential run (taking into account the Particles' Outer Cycle and not considering the particle domain distribution) when using distributed and shared memory with multi-GPUs dealing with about 25 million particles.
用于海洋污染物评估的高可扩展高性能拉格朗日输运和扩散模型
虽然使用高性能计算(HPC)进行精确和准确的空气质量预报是一个普遍的问题,但致力于沿海地区海洋污染的类似服务仍然具有挑战性。本文介绍了水质社区模型Plus Plus (wacom++),它利用了一种并行模式,使用户能够在异构并行架构上运行它。我们利用那不勒斯湾(意大利坎帕尼亚)污染物预测的实际应用,在几种执行方法下评估了所提出的模型。因此,当使用分布式和共享内存以及多gpu处理大约2500万个粒子时,WaComM++产生的结果比顺序运行快657K倍(考虑到粒子的外部周期而不考虑粒子域分布)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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