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The Computational Fluid Dynamics (CFD), is a method of analysis which scientists and engineers are using to build high complexity models. One of the most important side problems of CFD is the cost of operating the computational infrastructure, that is increasing along with the models.
This work tries to contribute a technique of building high resolution CFD models along with reducing these operational costs. We try to rise the awareness to an understated part of the parallelization process: the mapping phase, when the bulk computing load is distributed towards the individual computing cores of a computing cluster.