{"updated":"2025-01-19T19:28:02.313601+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00206298","sets":["1164:2735:10153:10283"]},"path":["10283"],"owner":"44499","recid":"206298","title":["大規模行列の特異値分解へのOQDS法の適用"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-07-20"},"_buckets":{"deposit":"8a218f09-0c8d-4c61-907b-b7907969b9c0"},"_deposit":{"id":"206298","pid":{"type":"depid","value":"206298","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"大規模行列の特異値分解へのOQDS法の適用","author_link":["512782","512781","512786","512784","512787","512783","512785"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"大規模行列の特異値分解へのOQDS法の適用"},{"subitem_title":"Application of the Orthogonal QD algorithm with Shift to Singular Value Decomposition for Large Matrices","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2020-07-20","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"京都大学"},{"subitem_text_value":"KIOXIA"},{"subitem_text_value":"KIOXIA"},{"subitem_text_value":"KIOXIA"},{"subitem_text_value":"奈良女子大学"},{"subitem_text_value":"福井大学"},{"subitem_text_value":"京都大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kyoto University","subitem_text_language":"en"},{"subitem_text_value":"KIOXIA Corporation","subitem_text_language":"en"},{"subitem_text_value":"KIOXIA Corporation","subitem_text_language":"en"},{"subitem_text_value":"KIOXIA Corporation","subitem_text_language":"en"},{"subitem_text_value":"Nara Women's University","subitem_text_language":"en"},{"subitem_text_value":"University of Fukui","subitem_text_language":"en"},{"subitem_text_value":"Kyoto University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/206298/files/IPSJ-MPS20129003.pdf","label":"IPSJ-MPS20129003.pdf"},"date":[{"dateType":"Available","dateValue":"2022-07-20"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS20129003.pdf","filesize":[{"value":"743.3 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"04d61693-2c6c-44de-94d7-10126c89a719","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2020 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"田中, 博基"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"木村, 泰己"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松縄, 哲明"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"三本木, 省次"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"髙田, 雅美"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"木村, 欣司"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中村, 佳正"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8833","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"半導体製造において,リソグラフィシミュレーションモデルが重要である.このモデルを構築する際,大規模密行列の部分特異値分解が必要となる.部分特異値分解のための方法として,AIRLB(augmented implicitly restarted Lanczos bidiagonalization)アルゴリズムがある.本稿では,大規模密行列の部分特異値分解のために,AIRLB アルゴリズムの改良を行う.改良法では,計算途中で必要となる小さな行列の特異値分解のために,QR アルゴリズムではなく,OQDS(orthogonal-qd-with-shift)アルゴリズムを適用する.これにより,高精度な特異値を持つ特異値分解が行われる.数値実験の結果,既存の QR アルゴリズムを用いる AIRLB アルゴリズムと比較して,提案した改良が有効に機能していることが確認できる.精密な議論を行うため, 大規模疎行列と大規模密行列の両方を実験の対象としている.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決(MPS)"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2020-07-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"2020-MPS-129"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:08:22.215161+00:00","id":206298,"links":{}}