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- W2247289636 abstract "In the past decade, several data distribution strategies for the parallel, distributed-memory Multilevel Fast Multipole Algorithm (MLFMA) have been introduced. The common goal is to distribute the computations in the MLFMA uniformly over the different parallel processes, while minimizing dependencies and data communication between them. However, as clusters with thousands of CPU cores are becoming increasingly available, the asymptotic behavior of algorithms for a very large number of processes P and problem size N (weak scaling analysis) starts to play a dominant role. Parallel MLFMA implementations based on a hierarchical distribution of boxes and radiation pattern sampling points that exhibit excellent weak scaling behavior appear to be attractive candidates to tackle even larger problems on future hardware clusters." @default.
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- W2247289636 date "2014-01-01" @default.
- W2247289636 modified "2023-10-17" @default.
- W2247289636 title "Weak scaling analysis for the parallel MLFMA: the quest for ever larger simulations" @default.
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