Abstract
The combination of adaptive refinement, multigrid and parallel computing for solving partial differential equations is considered. In the full domain partition approach, each processor contains a partition of the grid plus the minimum number of additional coarse elements required to cover the whole domain. A parallel adaptive refinement algorithm using the full domain partition is presented. The method is a small modification of a sequential adaptive refinement algorithm, and uses no interprocessor communication during the refinement process. The only communication is one global reduction before refinement and three all-to-all communication steps for synchronization after the refinement is completed. Numerical computations on a network of up to 4 workstations show that parallel efficiency rates of 85% to near 100% can be obtained.
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Mitchell, W.F. (1999). The Full Domain Partition Approach to Parallel Adaptive Refinement. In: Bern, M.W., Flaherty, J.E., Luskin, M. (eds) Grid Generation and Adaptive Algorithms. The IMA Volumes in Mathematics and its Applications, vol 113. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1556-1_9
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DOI: https://doi.org/10.1007/978-1-4612-1556-1_9
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