Taking advantage of HPC techniques in the operational forecast of the Río de la Plata

In this paper we address the use of high performance computing techniques with the aim of accelerating the runtime of a numerical model for the South Atlantic Ocean. This numerical model is a component of a larger system, that includes higher precision models to compute the hidrodynamics of the Río de la Plata river. Our work includes, in a first stage, a thorough study of the use of traditional HPC techniques on the CPU, and in a second stage we perform a preliminar study about the use of GPUs to accelerate the optimized version of the model. Specifically, for the first stage we made a profiling of the original model to identify the routines with larger computational cost. After that, we design and implement some variants for the three most expensive ones. Finally, we validate the proposals with an experimental evaluation. The results obtained show important acceleration values for the routines (up to 11 x), and these accelerations impact in the whole model with a runtime reduction of more than three times. Finally, we migrated one of the most costly routines of the optimized version to the GPU as a proof of concept.