For that purpose, we have implemented an optimized version of the algorithm on the CPU and Xeon Phi (based on OpenMP, vectorization, and the Intel MKL library) and on the GPU (based on CUDA and the MAGMA library). In this paper we evaluate the performance of such an optimization algorithm on modern accelerators (more specifically, the Intel Xeon Phi 7120 and the NVIDIA K80). Consequently, for low-speed aerodynamics, panel methods are most often used as the inner solver. However, these algorithms require the computation of aerodynamic properties for a significant number of airfoil geometries. In this context genetic algorithms have enjoyed some success as they are able to explore the search space without getting stuck in local optima. ![]() ![]() To optimize the geometry of airfoils for a specific application is an important engineering problem.
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