Reducing MLFMA memory with out-of-core implementation and data-structure parallelization
CEM'13 Computational Electromagnetics International Workshop
34 - 37
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We present two memory-reduction methods for the parallel multilevel fast multipole algorithm (MLFMA). The first method implements out-of-core techniques and the second method parallelizes the pre-processing data structures. Together, these methods decrease parallel MLFMA memory bottlenecks, and hence fast and accurate solutions can be achieved for largescale electromagnetics problems.
Multi level fast multipole algorithms (MLFMA)