Fast analysis for large-scale electromagnetic scattering problems by a hybrid approach

2017 ◽  
Vol 31 (8) ◽  
pp. 808-819 ◽  
Author(s):  
Chenlu Li ◽  
Yufa Sun ◽  
Guohua Wang ◽  
Zhonggen Wang
2012 ◽  
Vol 182-183 ◽  
pp. 893-897
Author(s):  
Zhi Xun Gong ◽  
Wei Qin Tong ◽  
Ying Li

In this paper, we propose an automatic load-balanced partitioning strategy for parallel multilevel fast multipole algorithm(MLFMA) based on distributed-memory architectures to solve the large scale electromagnetic scattering problems. We focus on the automatic load-balancing partitioning strategy because that our original scheme requires that users input the transition level, which is usually determined on the users’ experience and sometimes lead to a bad load-balancing partition. By introducing the automatic load-balancing algorithm to our pervious partitioning technique, our implementation can automatically achieve the best load-balancing and consequently attain better parallel efficiency. To present the effectiveness of the new strategy, we analyze results of the previous implementation according to different inputs of transition level and compare them with the result of implementation using the new algorithm.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 127640-127647
Author(s):  
Meng Kong ◽  
Mingsheng Chen ◽  
Xinyuan Cao ◽  
Liang Zhang ◽  
Qi Qi ◽  
...  

2015 ◽  
Vol 719-720 ◽  
pp. 881-885
Author(s):  
Jia Qi Chen ◽  
Yue Yuan Zhang

A novel efficient hybrid accelerated method is proposed for the fast analysis of the monostatic electromagnetic scattering problems arising from volume-surface integral equations (VSIE) formulation. In the first step, by utilizing the low rank property, several largest eigenvalues and corresponding eigenvectors of the multiple right hand sides can be computed and saved efficiently by adaptive cross approximation (ACA) algorithm. The iterative solution of linear equations is required at these principle eigenvectors. Compared with solving linear equations at each angle repeatedly, the proposed method is able to greatly reduce the number of equations. In the second step, a disturbed symmetric successive over-relaxation (D-SSOR) preconditioner is constructed to speed up the convergence rate of iterative methods. Numerical results demonstrate that the present method can reduce the computational time significantly for monostatic VSIE calculation with high accuracy.


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