Parallelization of multilevel fast multipole algorithm with open MPI for scattering by large scale targets

2009 ◽  
Author(s):  
Fangjing Hu ◽  
Zaiping Nie ◽  
Bin Wen ◽  
Jun Hu
Keyword(s):  
Large Scale ◽  
Fast Multipole ◽  
Multilevel Fast Multipole Algorithm ◽  
Fast Multipole Algorithm ◽  
Open Mpi

Inplementation of an Efficient Parallel Multilevel Fast Multipole Algorithm

2012 ◽  
Vol 433-440 ◽  
pp. 4268-4272
Author(s):  
You Feng Chen ◽  
Dong Lin Su ◽  
Xiao Ying Zhao ◽  
Dan Dan Guo ◽  
Li Peng Deng
Keyword(s):  
Shared Memory ◽  
High Frequency ◽  
Large Scale ◽  
Memory System ◽  
Method Of Moment ◽  
Fast Multipole ◽  
Multilevel Fast Multipole Algorithm ◽  
Shared Memory System ◽  
Fast Multipole Algorithm

This paper is concerned with the implementation of the parallel multilevel fast multipole algorithm(MLFMA) for large scale electromagnetics simulation on shared-memory system. The algorithm is implemented on a method of moment discretisation of the electromagnetics scattering problems.The developed procesure is validated by compared to benchmarks defined by Electromagnetics Code Consortium(EMCC) .The procesure can evaluate large problemssuch as electromagnetics scattering of aircraft at high-frequency with up to several millions of unknowns.

Automatic Load-Balanced Partitioning Strategy in Parallel Multilevel Fast Multipole Algorithm

2012 ◽  
Vol 182-183 ◽  
pp. 893-897
Author(s):  
Zhi Xun Gong ◽  
Wei Qin Tong ◽  
Ying Li
Keyword(s):  
Load Balancing ◽  
Electromagnetic Scattering ◽  
Large Scale ◽  
Fast Multipole ◽  
Scattering Problems ◽  
Multilevel Fast Multipole Algorithm ◽  
Transition Level ◽  
Fast Multipole Algorithm ◽  
Partitioning Strategy ◽  
Load Balanced

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.

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