{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00217103","sets":["1164:1579:10818:10892"]},"path":["10892"],"owner":"44499","recid":"217103","title":["CNNのクラスタリングによる圧縮と推論アクセラレータの検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-03-03"},"_buckets":{"deposit":"a6dc1d44-b51e-43a4-a67c-43adbdfc079a"},"_deposit":{"id":"217103","pid":{"type":"depid","value":"217103","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"CNNのクラスタリングによる圧縮と推論アクセラレータの検討","author_link":["561779","561780"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"CNNのクラスタリングによる圧縮と推論アクセラレータの検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ニューラルネットワーク","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-03-03","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学大学院情報理工学系研究科"},{"subitem_text_value":"東京大学大学院情報理工学系研究科"}]},"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/217103/files/IPSJ-ARC22248015.pdf","label":"IPSJ-ARC22248015.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ARC22248015.pdf","filesize":[{"value":"1.8 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"16"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"5894fd95-9104-4ec2-b31b-13532abf6e28","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 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":"空閑, 康太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"高前田, 伸也"}],"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_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8574","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"畳み込みニューラルネットワーク (CNN) はコンピュータビジョンの分野で頻出である．近年は IoT デバイスの普及により組込みシステムでの需要も高い．FPGA 実装も多く試みられているが，CNN のパラメタ数は膨大なため，限られたリソース下ではパラメタをオフチップメモリに格納し，計算で必要となるたびに取得することがほとんどである．本稿では，量子化後のカーネルが類似することに着目し，畳み込み演算を組み合わせ回路として展開する，外部メモリアクセス不要なアーキテクチャについて検討を行った．また，このアーキテクチャに適した，クラスタリ ングと量子化を含む圧縮アルゴリズムを提案，評価し，精度と圧縮のトレードオフを明らかにした．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告システム・アーキテクチャ（ARC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-03-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"15","bibliographicVolumeNumber":"2022-ARC-248"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":217103,"updated":"2025-01-19T15:37:17.217331+00:00","links":{},"created":"2025-01-19T01:17:36.560949+00:00"}