{"created":"2025-01-18T23:46:40.117664+00:00","updated":"2025-01-21T11:28:22.920068+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00100990","sets":["1164:1579:7406:7573"]},"path":["7573"],"owner":"11","recid":"100990","title":["Hadoopクラスタの動的構成変更による低電力化手法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2014-05-07"},"_buckets":{"deposit":"f51ef280-a6ee-4895-96fa-54b18e7aba65"},"_deposit":{"id":"100990","pid":{"type":"depid","value":"100990","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"Hadoopクラスタの動的構成変更による低電力化手法の提案","author_link":["0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Hadoopクラスタの動的構成変更による低電力化手法の提案"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"省電力","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2014-05-07","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"株式会社富士通研究所"},{"subitem_text_value":"株式会社富士通研究所"},{"subitem_text_value":"株式会社富士通研究所"}]},"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/100990/files/IPSJ-ARC14210002.pdf"},"date":[{"dateType":"Available","dateValue":"2016-05-07"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ARC14210002.pdf","filesize":[{"value":"369.5 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":"16"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"4848659d-cfef-437d-b2e2-424e3f3f38b1","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2014 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小野貴継"},{"creatorName":"谷本輝夫"},{"creatorName":"三吉貴史"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10096105","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":"Hadoop 上で実行される機械学習プログラムには，CPU 性能やメモリ容量を必要としない Transfer Phase と，高い CPU 性能と大容量のメモリを必要とする Analysis Phase がある．Transfer Phase は低電力な CPU を搭載したサーバで実行し，Analysis Phase は高性能な CPU を搭載したサーバで実行することで消費電力を削減する手法を提案する．フェーズごとに構成が異なるサーバで実行するためには，サーバ間でデータを移動する必要がある．本稿では，著者らが開発を進めている Disk Area Network（DAN） を用いてデータの移動を実現する．DAN を介して HDD を低電力サーバへ接続しておき，Transfer Phase を実行する．次に DAN の機能を利用して低電力サーバから HDD の接続を解除し，高性能サーバへ接続して Analysis Phase を実行する．本手法により，高性能サーバのみを用いてプログラムを実行した場合と比較して実行時間の増加は 4.3%に抑制しつつ，Transfer Phase の消費電力を約 28%削減可能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":"7","bibliographic_titles":[{"bibliographic_title":"研究報告計算機アーキテクチャ（ARC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2014-05-07","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2014-ARC-210"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":100990,"links":{}}