Parallel Hierarchical Matrices with Adaptive Cross Approximation on Symmetric Multiprocessing Clusters (Preprint)

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概要

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• 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-MPI and 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.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.22(2014) No.4 (online)------------------------------

• 2014-09-15

著者

• Akihiro Ida

  ACCMS, Kyoto University|JST CREST

• Takeshi Mifune

  JST CREST|Department of Electrical Engineering, Kyoto University

• Yasuhito Takahashi

  JST CREST|Department of Electrical Engineering, Doshisha University

• Takeshi Iwashita

  JST CREST|Information Initiative Center, Hokkaido University

関連論文

• Parallel Hierarchical Matrices with Adaptive Cross Approximation on Symmetric Multiprocessing Clusters (Preprint)

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