Reducing MLFMA memory with out-of-core implementation and data-structure parallelization

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 henc...

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Bibliographic Details
Main Authors: Hidayetoglu, Mert, Karaosmanoglu, Bariscan, Gurel, Levent
Format: Conference Proceeding
Language:English
Subjects:
Complexity theory
Data structures
Geometry
Memory management
MLFMA
Program processors
Scattering
Online Access:Request full text
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Summary: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 large-scale electromagnetics problems.
DOI:10.1109/CEM.2013.6617124