A Scalable Parallel Wideband MLFMA for Efficient Electromagnetic Simulations on Large Scale Clusters

被引:40
作者
Melapudi, Vikram [1 ]
Shanker, Balasubramaniam [1 ]
Seal, Sudip [2 ]
Aluru, Srinivas [3 ]
机构
[1] Michigan State Univ, Dept Elect & Comp Engn, E Lansing, MI 48824 USA
[2] Oak Ridge Natl Lab, Modeling & Simulat Grp, Computat Sci & Engn Div, Oak Ridge, TN 37831 USA
[3] Iowa State Univ, Dept Elect & Comp Engn, Ames, IA 50011 USA
基金
美国国家科学基金会;
关键词
Accelerated Cartesian expansion (ACE); Cartesian expansions; fast multipole method (FMM); fast solvers; integral equation (IE); multipole methods; parallel multilevel fast multipole algorithm (MLFMA); scattering; self-similar tree; wideband MLFMA; FAST MULTIPOLE METHOD; ACCELERATED CARTESIAN EXPANSIONS; HELMHOLTZ-EQUATION; INTEGRAL-EQUATIONS; ERROR ANALYSIS; SCATTERING; ALGORITHM; FORMS;
D O I
10.1109/TAP.2011.2152311
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The development of the multilevel fast multipole algorithm (MLFMA) and its multiscale variants have enabled the use of integral equation (IE) based solvers to compute scattering from complicated structures. Development of scalable parallel algorithms, to extend the reach of these solvers, has been a topic of intense research for about a decade. In this paper, we present a new algorithm for parallel implementation of IE solver that is augmented with a wideband MLFMA and scalable on large number of processors. The wideband MLFMA employed here, to handle multiscale problems, is a hybrid combination of the accelerated Cartesian expansion (ACE) and the classical MLFMA. The salient feature of the presented parallel algorithm is that it is implicitly load balanced and exhibits higher performance. This is achieved by developing a strategy to partition the MLFMA tree, and hence the associated computations, in a self-similar fashion among the parallel processors. As detailed in the paper, the algorithm employs both spatial and direction partitioning approaches in a flexible manner to ensure scalable performance. Plethora of results are presented here to exhibit the scalability of this algorithm on 512 and more processors.
引用
收藏
页码:2565 / 2577
页数:13
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