Improvement of Hierarchical Matrices with Adaptive Cross Approximation for Large-scale Simulation

• Item type: Trans(1)
• 公開日: 2015-03-26
• タイトル: Improvement of Hierarchical Matrices with Adaptive Cross Approximation for Large-scale Simulation
• タイトル / 言語: en
• タイトル: Improvement of Hierarchical Matrices with Adaptive Cross Approximation for Large-scale Simulation
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [数値アルゴリズム] low-rank approximation, hierarchical matrices, adaptive cross approximation, integral equation method, earthquake cycle simulation
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: ACCMS, Kyoto University／JST CREST
• 著者所属: JST CREST／Information Initiative Center, Hokkaido University
• 著者所属: Graduate School of Science, Kyoto University
• 著者所属: JST CREST／Graduate School of Science, Kyoto University
• 著者所属(英): en
• 著者所属(英): ACCMS, Kyoto University / JST CREST
• 著者所属(英): en
• 著者所属(英): JST CREST / Information Initiative Center, Hokkaido University
• 著者所属(英): en
• 著者所属(英): Graduate School of Science, Kyoto University
• 著者所属(英): en
• 著者所属(英): JST CREST / Graduate School of Science, Kyoto University
• 著者名: Akihiro, Ida; Takeshi, Iwashita; Makiko, Ohtani; Kazuro, Hirahara
• 著者名(英): Akihiro, Ida; Takeshi, Iwashita; Makiko, Ohtani; Kazuro, Hirahara
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: We propose an improved method for hierarchical-matrices (H-matrices) using adaptive cross approximation (ACA) as the low-rank approximation. The improvement consists of a kind of normalization and a new stopping criterion for the ACA. By using the proposed method, we can avoid the trouble that ranks of approximated matrices increase rapidly as the matrix size increases when the conventional H-matrices with ACA are employed to an integral equation whose kernel function has high-order singularities. In particular, application of the proposed method enables us to perform large-scale simulations such that the conventional H-matrices with ACA fail to construct the low-rank approximation. Applicability of the proposed method is confirmed through numerical experiments on an earthquake cycle simulation.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.23(2015) No.3 (online); ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: We propose an improved method for hierarchical-matrices (H-matrices) using adaptive cross approximation (ACA) as the low-rank approximation. The improvement consists of a kind of normalization and a new stopping criterion for the ACA. By using the proposed method, we can avoid the trouble that ranks of approximated matrices increase rapidly as the matrix size increases when the conventional H-matrices with ACA are employed to an integral equation whose kernel function has high-order singularities. In particular, application of the proposed method enables us to perform large-scale simulations such that the conventional H-matrices with ACA fail to construct the low-rank approximation. Applicability of the proposed method is confirmed through numerical experiments on an earthquake cycle simulation.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.23(2015) No.3 (online); ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA11833852
• 書誌情報: 情報処理学会論文誌コンピューティングシステム（ACS）; 巻 8, 号 1, 発行日 2015-03-26
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7829
• 出版者 / 言語: ja
• 出版者: 情報処理学会