The conjugate gradient-fast multipole method (CG-FMM) is one of the powerful methods for analysis of large-scale electromagnetic problems. It is also known that CPU time and computer memory can be reduced by CG-FMM but such computational cost of CG-FMM depends on shape and electrical properties of an analysis model. In this paper, relation between the number of multipoles and number of segments in each group is derived from dimension of segment arrangement in four typical wiregrid models. Based on the relation and numerical results for these typical models, the CPU time per iteration and computer memory are quantitatively discussed. In addition, the number of iteration steps, which is related to condition number of impedance matrix and analysis model, is also considered from a physical point of view.
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Keisuke KONNO, Qiang CHEN, Kunio SAWAYA, "Quantitative Evaluation for Computational Cost of CG-FMM on Typical Wiregrid Models" in IEICE TRANSACTIONS on Communications,
vol. E93-B, no. 10, pp. 2611-2618, October 2010, doi: 10.1587/transcom.E93.B.2611.
Abstract: The conjugate gradient-fast multipole method (CG-FMM) is one of the powerful methods for analysis of large-scale electromagnetic problems. It is also known that CPU time and computer memory can be reduced by CG-FMM but such computational cost of CG-FMM depends on shape and electrical properties of an analysis model. In this paper, relation between the number of multipoles and number of segments in each group is derived from dimension of segment arrangement in four typical wiregrid models. Based on the relation and numerical results for these typical models, the CPU time per iteration and computer memory are quantitatively discussed. In addition, the number of iteration steps, which is related to condition number of impedance matrix and analysis model, is also considered from a physical point of view.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E93.B.2611/_p
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@ARTICLE{e93-b_10_2611,
author={Keisuke KONNO, Qiang CHEN, Kunio SAWAYA, },
journal={IEICE TRANSACTIONS on Communications},
title={Quantitative Evaluation for Computational Cost of CG-FMM on Typical Wiregrid Models},
year={2010},
volume={E93-B},
number={10},
pages={2611-2618},
abstract={The conjugate gradient-fast multipole method (CG-FMM) is one of the powerful methods for analysis of large-scale electromagnetic problems. It is also known that CPU time and computer memory can be reduced by CG-FMM but such computational cost of CG-FMM depends on shape and electrical properties of an analysis model. In this paper, relation between the number of multipoles and number of segments in each group is derived from dimension of segment arrangement in four typical wiregrid models. Based on the relation and numerical results for these typical models, the CPU time per iteration and computer memory are quantitatively discussed. In addition, the number of iteration steps, which is related to condition number of impedance matrix and analysis model, is also considered from a physical point of view.},
keywords={},
doi={10.1587/transcom.E93.B.2611},
ISSN={1745-1345},
month={October},}
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TY - JOUR
TI - Quantitative Evaluation for Computational Cost of CG-FMM on Typical Wiregrid Models
T2 - IEICE TRANSACTIONS on Communications
SP - 2611
EP - 2618
AU - Keisuke KONNO
AU - Qiang CHEN
AU - Kunio SAWAYA
PY - 2010
DO - 10.1587/transcom.E93.B.2611
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E93-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2010
AB - The conjugate gradient-fast multipole method (CG-FMM) is one of the powerful methods for analysis of large-scale electromagnetic problems. It is also known that CPU time and computer memory can be reduced by CG-FMM but such computational cost of CG-FMM depends on shape and electrical properties of an analysis model. In this paper, relation between the number of multipoles and number of segments in each group is derived from dimension of segment arrangement in four typical wiregrid models. Based on the relation and numerical results for these typical models, the CPU time per iteration and computer memory are quantitatively discussed. In addition, the number of iteration steps, which is related to condition number of impedance matrix and analysis model, is also considered from a physical point of view.
ER -