Parallelization of double higher order FEM and MoM techniques

Manic, Ana B.; Chobanyan, Elene; Notaroš, Branislav M.; Ilić, Milan M.

doi:10.1109/aps.2014.6905135

Cited by 1 publication

(3 citation statements)

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“…The parallelization strategy of the HSS-MoM-SIE method is adapted from [34] for construction, factorization, and solution, and from [44] for MoM-SIE matrix filling. The communication methods between the processes are designed to fit with the communication layer of the state-of-the-art dense linear algebra libraries ScaLAPACK [45] and basic linear algebra communication subprograms (BLACS) [46].…”

Section: Parallelization Strategymentioning

confidence: 99%

“…MoM-SIE matrix filling is done as described in Section II, where the parallel matrix filling builds on top of the geometrical processing as modified from [44]. If the total number of processes running the simulation is N procs , then the number of mesh groups used to partition the mesh during preprocessing is N g = N procs .…”

Section: Parallelization Strategymentioning

confidence: 99%

“…Fig. 10 shows the monostatic scattering computations of the DHO model of the PEC almond obtained by the HSS-MoM-SIE method and validated by the full-storage direct solver using ScaLAPACK LU decomposition [44] simulation of the same model, as well as against the LO modeling results [40]. The normalized monostatic RCS is calculated for 361 different directions, in the z = 0 plane, with the polarization of the incident electric field along the z-axis.…”

Section: B Example 2: Nasa Almondmentioning

confidence: 99%

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Efficient Scalable Parallel Higher Order Direct MoM-SIE Method With Hierarchically Semiseparable Structures for 3-D Scattering

Manic

Smull

Rouet

et al. 2017

IEEE Trans. Antennas Propagat.

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Abstract-A novel fast scalable parallel algorithm is proposed for the solution of large 3-D scattering problems based on: 1) the double (geometrical and current-approximation) higher order (DHO) method of moments (MoM) in the surface integral equation (SIE) formulation and 2) a direct solver for dense linear systems utilizing hierarchically semiseparable (HSS) structures. Namely, an HSS matrix representation is used for compression, factorization, and solution of the system matrix. In addition, a rank-revealing QR decomposition for memory compression is used, with a stopping criterion in terms of the relative rank tolerance value. A method for geometrical preprocessing of the scatterers based on the cobblestone distance sorting technique is employed in order to enhance the HSS algorithm accuracy and parallelization. Numerical examples show how the accuracy of the DHO HSS-MoM-SIE method is easily controllable by using the relative tolerance for the matrix compression. Moreover, the examples demonstrate low memory consumption, as well as much faster simulation time, when compared to the direct LU decomposition. The method enables dramatically faster monostatic scattering computations than iterative solvers and reduced number of unknowns when compared to low-order discretizations. Finally, great scalability of the algorithm is demonstrated on more than one thousand processes.Index Terms-Curved parametric elements, direct solvers, fast solvers, hierarchically semiseparable (HSS) structures, higher order (HO) modeling, low-rank matrix approximation, method of moments (MoM), multilevel matrix compression, numerical algorithms, parallelization, polynomial basis functions, scalability, scattering, surface integral equation (SIE).

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Section: Parallelization Strategymentioning

confidence: 99%

Section: Parallelization Strategymentioning

confidence: 99%