A CUDA Fortran GPU-parallelised hydrodynamic tool for high-resolution and long-term eco-hydraulic modelling

Eco-hydraulic models are wide extended tools to assess physical habitat suitability on aquatic environments. Currently, the application of these tools is limited to short river stretches and steady flow simulations. However, this limitation can be overcome with the application of a high-performance...

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Veröffentlicht in:Environmental modelling & software : with environment data news 2023-03, Vol.161, p.105628, Article 105628
Hauptverfasser: Sanz-Ramos, Marcos, López-Gómez, David, Bladé, Ernest, Dehghan-Souraki, Danial
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Sprache:eng
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Zusammenfassung:Eco-hydraulic models are wide extended tools to assess physical habitat suitability on aquatic environments. Currently, the application of these tools is limited to short river stretches and steady flow simulations. However, this limitation can be overcome with the application of a high-performance computing technique: graphics processing unit (GPU) computing. R-Iber is a GPU-based hydrodynamic code parallelised in CUDA Fortran that, with the integration of a biological module, performs as an eco-hydraulic numerical tool. R-Iber was validated and applied to real cases by using an optimised instream flow incremental methodology in long river reaches and long-term simulations. R-Iber reduces the computation time considerably, reaching speed-ups of two orders of magnitude compared to traditional computing. R-Iber allows for overcoming the current limitations of the eco-hydraulic tools with the simulation of high-resolution numerical models calculated in a reasonable computation timeframe, which provides a better representation of the hydrodynamics and the physical habitat. •A hydrodynamic HPC-based model for fish habitat assessment.•Code parallelisation with CUDA Fortran programming language.•Code optimization for multi-GPU computing reaching speed-ups above 100-times.•Integration, improve and assessment of the IFIM (WUA-Q relation) in a single model.•High-resolution and long-term habitat modelling in long river reaches.
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2023.105628