Parallel computational fluid dynamics grid mapping optimization and simulation

Computational Fluid Dynamics (CFD) are an important software algorithmic tool used in the design and analysis of objects that move in a fluid environment. However, due to the large computational times required for CFD problems, parallel CFD grid mapping optimization and simulation are useful tools. These algorithms have been developed to minimize the computational times for these CFD problems and also to provide an approximation of the times required for those problems.

The optimization algorithm, which uses Simulated Annealing to find an mapping of grids to processors which is close to optimum, results in a decrease in execution time ranging from 4-97%. Furthermore, although the problem is NP-Hard, our polynomial-time heuristic found an optimal mapping for the cases tried. The simulation algorithm shows good accuracy at approximating the run times of CFD problems, with under a 7% erгог.

The results of this study warrant the application of these techniques to other parallel CFD flow solvers.