Reducing MLFMA memory with out-of-core implementation and data-structure parallelization
CEM 2013 - Computational Electromagnetics International Workshop
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/27883
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. © 2013 IEEE.
- Conference Paper