Parallelization of a Large-Scale Watersheds Hydrological Model using CPU and GPU
ResumoHydrological models are commonly employed to calculate water flows on rivers and watersheds for the analysis of extreme events in nature. Computations in these models can grow depending on the numerical method, and also on the spatial and temporal resolutions, thus affecting the model efficiency and utility. This work parallelizes the MGB hydrological model on either CPU with OpenMP or GPU with OpenACC, respectively, aiming at the improvement in performance by employing computing resources of an HPC system. An analysis of the sequential and parallel executions is presented together with the runtime, speedup, efficiency, and load balance achieved.
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