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Title: Parallel Hierarchical Matrices with Adaptive Cross Approximation on Symmetric Multiprocessing Clusters
Authors: Ida, Akihiro
Iwashita, Takeshi
Mifune, Takeshi  kyouindb  KAKEN_id
Takahashi, Yasuhito
Author's alias: 伊田, 明弘
Keywords: boundary element method
matrix approximation
hierarchical matrices
adaptive cross approximation
parallel scalability
symmetric multiprocessing clusters
Issue Date: Oct-2014
Publisher: Information Processing Society of Japan
Journal title: Journal of Information Processing
Volume: 22
Issue: 4
Start page: 642
End page: 650
Abstract: We discuss a scheme for hierarchical matrices with adaptive cross approximation on symmetric multiprocessing clusters. We propose a set of parallel algorithms that are applicable to hierarchical matrices. The proposed algorithms are implemented using the flat-MPIand hybrid MPI+OpenMP programming models. The performance of these implementations is evaluated using an electric field analysis computed on two symmetric multiprocessing cluster systems. Although the flat-MPI version gives better parallel scalability when constructing hierarchical matrices, the speed-up reaches a limit in the hierarchical matrix-vector multiplication. We succeeded in developing a hybrid MPI+OpenMP version to improve the parallel scalability. In numerical experiments, the hybrid version exhibits a better parallel speed-up for the hierarchical matrix-vector multiplication up to 256 cores.
Rights: © 2014 by the Information Processing Society of Japan
DOI(Published Version): 10.2197/ipsjjip.22.642
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