{"updated":"2025-01-19T20:25:12.523028+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00203858","sets":["1164:2240:10178:10179"]},"path":["10179"],"owner":"44499","recid":"203858","title":["SX-Aurora TSUBASAによるSLIMの高速化"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-03-09"},"_buckets":{"deposit":"56ef1bde-87ee-402d-bd99-02e4c40edff7"},"_deposit":{"id":"203858","pid":{"type":"depid","value":"203858","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"SX-Aurora TSUBASAによるSLIMの高速化","author_link":["503760","503759","503758"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"SX-Aurora TSUBASAによるSLIMの高速化"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"計算アルゴリズム","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2020-03-09","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"NECデータサイエンス研究所"},{"subitem_text_value":"NECデータサイエンス研究所"},{"subitem_text_value":"NECデータサイエンス研究所"}]},"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/203858/files/IPSJ-HPC20173015.pdf","label":"IPSJ-HPC20173015.pdf"},"date":[{"dateType":"Available","dateValue":"2022-03-09"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-HPC20173015.pdf","filesize":[{"value":"4.1 MB"}],"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":"ab2983ee-571a-469c-82c6-604384edf0e7","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":"井手口, 裕太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大野, 善之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石坂, 一久"}],"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_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8841","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Top-N 推薦のための高精度かつ高速なアルゴリズムである SLIM のベクトル演算を用いた高速化手法を提案する．Top-N 推薦は，過去の購入履歴などを学習することでユーザーに推薦するアイテムを決定する問題であるが，膨大なデータを利用する学習時間の短縮が求めらている．SLIM はスレッド並列化が考慮されたアルゴリズムであるが，高性能ベクトルコンピュータ SX-Aurora TSUBASA で高速化するには，効率的なベクトル演算手法を開発する必要があった．本稿では，SLIM の主要処理に対するベクトル演算手法を提案し，SX-Aurora を用いた高速化を可能とする．Top-N 推薦でよく利用される MovieLens データセットを用いた評価では，提案する SX-Aurora を用いた SLIM は，2 ソケット Xeon に比べて 3.3 倍の高速であることを確認した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告ハイパフォーマンスコンピューティング（HPC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2020-03-09","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"15","bibliographicVolumeNumber":"2020-HPC-173"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:06:11.579169+00:00","id":203858,"links":{}}