Abstract

This paper presents the MPI-based parallelization of the three-dimensional hydrodynamic model SHYFEM (System of HydrodYnamic Finite Element Modules). The original sequential version of the code was parallelized in order to reduce the execution time of high-resolution configurations using state-of-the-art HPC systems. A distributed memory approach was used, based on the message passing interface (MPI). Optimized numerical libraries were used to partition the unstructured grid (with a focus on load balancing) and to solve the sparse linear system of equations in parallel in the case of semi-to-fully implicit time stepping. The parallel implementation of the model was validated by comparing the outputs with those obtained from the sequential version. The performance assessment demonstrates a good level of scalability with a realistic configuration used as benchmark.

Highlights

  • Ocean sciences are significantly supported by numerical modeling, which help to understand physical phenomena or provide predictions both in the short term or from a climate perspective

  • 350 We ran our experiments to assess the correctness of message passing interface (MPI) implementation on the Southern Adriatic Northern Ionian coastal Forecasting System (SANIFS) configuration, which has a horizontal resolution of 500m near the coast of up to 3-4km in open waters

  • The parallel code was validated using a realistic configuration as a benchmark

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Summary

Introduction

Ocean sciences are significantly supported by numerical modeling, which help to understand physical phenomena or provide predictions both in the short term or from a climate perspective. The reliability of ocean prediction is strictly linked to the ability of numerical models to capture the relevant physical processes. The coastal scale is rich in features driven by the interaction between the regional scale dynamics and the complex morphology typical of shelf areas, tidal flats, estaurines and straits. In both large-scale and coastal modeling, the spatial resolution is a key factor

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