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.
A highly scalable high-performance Lagrangian transport and diffusion model for marine pollutants assessment / Montella, R.; Di Luccio, D.; De Vita, C. G.; Mellone, G.; Lapegna, M.; Ortega, G.; Marcellino, L.; Zambianchi, E.; Giunta, G.. - (2023), pp. 17-26. ( 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2023 Naples; Italy ) [10.1109/PDP59025.2023.00012].
A highly scalable high-performance Lagrangian transport and diffusion model for marine pollutants assessment
Zambianchi E.;
2023
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.| File | Dimensione | Formato | |
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