TY - GEN
T1 - A Ternary Parallelization Approach of MLFMA for Solving Problems with Billions of Unknowns
AU - Yang, Ming Lin
AU - Liu, Rui Qing
AU - Gao, Hong Wei
AU - Sheng, Xin Qing
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - A flexible ternary parallelization approach of the multilevel fast multipole algorithm (MLFMA) is presented for the efficient solution of extremely large 3D scattering problems. In the ternary parallelization approach, the MLFMA tree is categorized into plane-wave partitioning, hierarchical-structure partitioning and box partitioning levels. A grouped transition level is specially designed to switch partitions on the intermediate level between the hierarchical-structure partitioning and box partitioning levels. The ternary strategy can achieve as high parallel efficiency as the hierarchical partitioning strategy while maintaining flexibility in choosing the number of processes. The accuracy of the solutions is demonstrated by comparing radar cross section (RCS) of a sphere with 2400 wavelengths diameter and 4,231,421,328 unknowns calculated by MLFMA and mie series. Furthermore, the solution of complicated objects with length 6131 wavelengths and 4,739,139,936 unknowns is also presented, which is the largest problem solved by MLFMA to date.
AB - A flexible ternary parallelization approach of the multilevel fast multipole algorithm (MLFMA) is presented for the efficient solution of extremely large 3D scattering problems. In the ternary parallelization approach, the MLFMA tree is categorized into plane-wave partitioning, hierarchical-structure partitioning and box partitioning levels. A grouped transition level is specially designed to switch partitions on the intermediate level between the hierarchical-structure partitioning and box partitioning levels. The ternary strategy can achieve as high parallel efficiency as the hierarchical partitioning strategy while maintaining flexibility in choosing the number of processes. The accuracy of the solutions is demonstrated by comparing radar cross section (RCS) of a sphere with 2400 wavelengths diameter and 4,231,421,328 unknowns calculated by MLFMA and mie series. Furthermore, the solution of complicated objects with length 6131 wavelengths and 4,739,139,936 unknowns is also presented, which is the largest problem solved by MLFMA to date.
KW - Multilevel fast multipole algorithm
KW - extremely large-scale problems
KW - parallelization
KW - scattering problems
KW - surface integral equations
UR - http://www.scopus.com/inward/record.url?scp=85070518493&partnerID=8YFLogxK
U2 - 10.1109/COMPEM.2019.8779193
DO - 10.1109/COMPEM.2019.8779193
M3 - Conference contribution
AN - SCOPUS:85070518493
T3 - 2019 IEEE International Conference on Computational Electromagnetics, ICCEM 2019 - Proceedings
BT - 2019 IEEE International Conference on Computational Electromagnetics, ICCEM 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE International Conference on Computational Electromagnetics, ICCEM 2019
Y2 - 20 March 2019 through 22 March 2019
ER -