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Abstract : |
Abstract. The efficient solution of many large-scale scientific calculations depends on unstructured mesh strategies. For example, problems where the solution changes rapidly in small regions of the domain require an adaptive mesh strategy. In this paper we discuss the main algorithmic issues to be addressed with an integrated approach to solving these problems on massively parallel architectures. We review new parallel algorithms to solve two significant problems that arise in this context: the generation of the adaptive mesh and the mesh partitioning. The gist of our refinement algorithm is the identification of independent sets of elements that can be refined in parallel. The objective of our partitioning heuristic is to construct partitions with good aspect ratios. We present running time bounds and computational results obtained on the Intel DELTA for these algorithms used in solving an optimization problem to determine the vortex structure in a high-temperature superconductor. These results demonstrate that the algorithms exhibit scalable performance and have runtimes small in comparison with other aspects of the computation. 1. Introduction. Unstructured, |
