{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00028645","sets":["1164:2240:2241:2243"]},"path":["2243"],"owner":"1","recid":"28645","title":["ハウスホルダーQR分解のためのAllReduceアルゴリズムの性能と精度"],"pubdate":{"attribute_name":"公開日","attribute_value":"2008-10-08"},"_buckets":{"deposit":"7ec144e1-c996-4887-8505-6acfa276e01a"},"_deposit":{"id":"28645","pid":{"type":"depid","value":"28645","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"ハウスホルダーQR分解のためのAllReduceアルゴリズムの性能と精度","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ハウスホルダーQR分解のためのAllReduceアルゴリズムの性能と精度"},{"subitem_title":"Performance and accuracy of the AllReduce algorithm for the Householder QR factorization","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2008-10-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"名古屋大学大学院工学研究科計算理工学専攻"},{"subitem_text_value":"名古屋大学大学院工学研究科計算理工学専攻"},{"subitem_text_value":"名古屋大学大学院工学研究科計算理工学専攻"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Computational Science and Engineering, Graduate School of Engineering, Nagoya University","subitem_text_language":"en"},{"subitem_text_value":"Department of Computational Science and Engineering, Graduate School of Engineering, Nagoya University","subitem_text_language":"en"},{"subitem_text_value":"Department of Computational Science and Engineering, Graduate School of Engineering, Nagoya 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/28645/files/IPSJ-HPC08117005.pdf"},"date":[{"dateType":"Available","dateValue":"2010-10-08"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-HPC08117005.pdf","filesize":[{"value":"747.8 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":"14"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"1287c052-d042-4309-84d4-a14e755d33b5","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2008 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"森, 大介"},{"creatorName":"山本, 有作"},{"creatorName":"張紹良"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Daisuke, Mori","creatorNameLang":"en"},{"creatorName":"Yusaku, Yamamoto","creatorNameLang":"en"},{"creatorName":"Shao-Liang, Zhang","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10463942","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_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"従来， QR 分解を計算するに当たって，直交性の高い Q が得られることからハウスホルダー変換が用いられてきた．しかし，並列計算によって高速化を図る際に，アルゴリズムの強い遂次性から十分な並列性能が発揮できたとは言えない．そこヘ近年，並列粒度の高い AllReduce アルゴリズムが提案された．このアルゴリズムは行列を上下に分割してそれぞれに対して QR 分解を行うことにより，並列粒度の増大を可能としている． AllReduce アルゴリズムは様々な QR 分解手法に適用できるが，本稿ではハウスホルダー変換による手法に言及し，従来の手法と AllReduce アルゴリズムを用いた手法の性能の比較ならびに精度の比較を行う．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Up to now, the Householder QR algorithm has been one of preferred methods for QR factorization because of its high orthogonality of Q. However, due to its strong sequential nature, it is not straightforward to accelerate the algorithm by parallel computation. Recently the AllRedece algorithm, which has large grain size, was proposed. This algorithm makes it possible to increase the grain size by dividing the target matrix into the upper and the lower submatrices and performing the QR factorization of each submatrix independently. While the AllReduce algorithm is applicable to various QR factorization methods, we focus on application to the Householder QR algorithm in this report. We will compare the performance and the accuracy of the conventional method and the AllReduce algorithm. ","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"29","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告ハイパフォーマンスコンピューティング（HPC）"}],"bibliographicPageStart":"25","bibliographicIssueDates":{"bibliographicIssueDate":"2008-10-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"99(2008-HPC-117)","bibliographicVolumeNumber":"2008"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"id":28645,"updated":"2025-01-22T17:58:41.297231+00:00","links":{},"created":"2025-01-18T22:58:42.205434+00:00"}