Abstract
In this paper we develop a common framework to explore the scalability of three improvement strategies for unstructured meshes: adaptive refinement, vertex smoothing, and edge flipping. We give a general parallel algorithm for these strategies based on defining, for each algorithm, an elemental operation and a task graph. By choosing the correct task graph, we can ensure the correct parallel execution of the algorithms independent of implementation. Finally, we present experimental results obtained on an IBM SP system and use these results to investigate, in practice, the scaling and relative costs of these algorithms.
The work of the first and third authors is supported by the Mathematical, Information, and Computational Sciences Division subprogram of the Office of Computational and Technology Research, U.S. Department of Energy, under Contract W-31-109-Eng38. The work of the second author is supported by National Science Foundation grants ASC-9501583, CDA-9529459, and ASC-9411394.
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Freitag, L.A., Jones, M.T., Plassmann, P.E. (1999). The Scalability of Mesh Improvement Algorithms. In: Heath, M.T., Ranade, A., Schreiber, R.S. (eds) Algorithms for Parallel Processing. The IMA Volumes in Mathematics and its Applications, vol 105. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1516-5_9
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DOI: https://doi.org/10.1007/978-1-4612-1516-5_9
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