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We present a GPU-based algorithm for optimizing the shape of elements in tetrahedral volume meshes. To exploit the massive parallelism available in modern GPU hardware, optimization occurs on a per-vertex basis using only local neighborhood information. A classical derivative-free numerical optimization method is employed to optimize the minimum dihedral(More)
We describe a parallel algorithmic framework for optimizing the shape of elements in a simplicial volume mesh. Using fine-grained parallelism and asymmetric multiprocessing on multi-core CPU and modern graphics processing unit hardware simultaneously, we achieve speedups of more than tenfold over current state-of-the-art serial methods. In addition,(More)
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