In this paper, the Shoreline Alert Model (SAM) is presented as a component of a computation platform based on workflows dedicated to extreme weather/marine event simulation. The model aims to mitigate the effects of global change by providing decision-makers, scientists, and engineers with a novel, next-generation tool set for facing extreme weather events and implementing related management or emergency responses. SAM uses a parallelization schema, allowing users to run it on heterogeneous parallel architectures. As a result, SAM produces approximately 24 times faster results than the baseline when using shared memory with distributed memory and dealing with about 20,000 transects along the Campania coastline. The system is based on the algorithms of the open-source numerical models WRF (Weather Research and Forecasting) and WW3 (Wave-watch III) implemented with refraction and shoaling routines together with run-up equations to form the modeling chain used for coastal flooding assessment.
Parallel and hierarchically-distributed Shoreline Alert Model (SAM) / De Vita, C. G.; Mellone, G.; Florio, A.; Charles, C. A. T.; Di Luccio, D.; Lapegna, M.; Benassai, G.; Budillon, G.; Montella, R.. - (2023), pp. 109-113. (Intervento presentato al convegno 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2023 tenutosi a Napoli nel 1-3 marzo 2023) [10.1109/PDP59025.2023.00024].
Parallel and hierarchically-distributed Shoreline Alert Model (SAM)
Di Luccio D.;Lapegna M.;Budillon G.;
2023
Abstract
In this paper, the Shoreline Alert Model (SAM) is presented as a component of a computation platform based on workflows dedicated to extreme weather/marine event simulation. The model aims to mitigate the effects of global change by providing decision-makers, scientists, and engineers with a novel, next-generation tool set for facing extreme weather events and implementing related management or emergency responses. SAM uses a parallelization schema, allowing users to run it on heterogeneous parallel architectures. As a result, SAM produces approximately 24 times faster results than the baseline when using shared memory with distributed memory and dealing with about 20,000 transects along the Campania coastline. The system is based on the algorithms of the open-source numerical models WRF (Weather Research and Forecasting) and WW3 (Wave-watch III) implemented with refraction and shoaling routines together with run-up equations to form the modeling chain used for coastal flooding assessment.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
