{"id":195537,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00195537","sets":["1164:2036:9683:9785"]},"path":["9785"],"owner":"44499","recid":"195537","title":["メモ化と簡略乗算を用いたアプロキシメートコンピューティング手法の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-05-08"},"_buckets":{"deposit":"57e9317c-4c08-4dd1-ae5e-8250be2e5361"},"_deposit":{"id":"195537","pid":{"type":"depid","value":"195537","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"メモ化と簡略乗算を用いたアプロキシメートコンピューティング手法の検討","author_link":["465910","465911","465912","465909"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"メモ化と簡略乗算を用いたアプロキシメートコンピューティング手法の検討"},{"subitem_title":"Approximate Computing Technique Using Memoization and Simplified Multiplication","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2019-05-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"芝浦工業大学大学院理工学研究科電気電子情報工学専攻"},{"subitem_text_value":"芝浦工業大学工学部情報工学科／芝浦工業大学グリーンイノベーション研究センター"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Engineering and Science, Shibaura Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Information Science and Engineering, Shibarua Institue of Technology / Research Center for Green Innovation, SIT Research Laboratories Computer Architecture Lab.,","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/195537/files/IPSJ-SLDM19188003.pdf","label":"IPSJ-SLDM19188003.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLDM19188003.pdf","filesize":[{"value":"1.7 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"10"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"3cd5446a-2b40-4e17-b798-6076a4fabdc3","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小野, 義基"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"宇佐美, 公良"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yoshinori, Ono","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kimiyoshi, Usami","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11451459","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":"2188-8639","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"演算を近似化することで，多少の誤差を許容しつつ実行時間や消費エネルギーを削減する「アプロキシメートコンピューテイング（Approximate Computing:AC）」が，盛んに研究されている．今回我々は，AC 手法の一つである「メモ化を用いた AC（Fuzzy Memoization）」に注目した．そして，「メモ化を用いた AC」に簡略乗算を適用して改良し，出力の正確さを保ちつつ，実行時間や消費エネルギーを削減する手法を考案した．ARM ベースのプロセッサと FPGA を組み合わせた System on a Chip の一種である Zynq を用いて，この手法を用いたカラー画像のグレースケール変換アプリケーションを開発し，評価を行った．その結果，出力誤差をほとんど抑えた状態で，最大 28％ の実行時間の短縮と，最大 11％ の消費エネルギーの削減を達成した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In embedded systems, approximate computing can strongly promote reduction of execution time and energy consumption in exchange for some output errors. We focused on \"Fuzzy memoization\", which is one of the approximate computing techniques. We improved it by using simplifying multiplication. By this improvement, we have developed a novel technique to reduce execution time and energy consumption while keeping output precision. Then, we implemented an application for grayscale filters on the Zynq system that contains ARM-based processor and field-programmable gate array (FPGA). As a result, this system could reduce the execution time by up to 28% and reduce the energy consumption by 11% in spite of very high-quality output images.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告システムとLSIの設計技術（SLDM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2019-05-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"2019-SLDM-188"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T23:03:32.039962+00:00","created":"2025-01-19T01:00:27.617084+00:00","links":{}}