{"id":228906,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00228906","sets":["1164:2036:11089:11372"]},"path":["11372"],"owner":"44499","recid":"228906","title":["ニューラルネットワークの入出力レンジ最適化による低ビットCiMベース推論器の設計手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-11-10"},"_buckets":{"deposit":"6d696979-19db-464a-be52-8e06e90d5faa"},"_deposit":{"id":"228906","pid":{"type":"depid","value":"228906","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ニューラルネットワークの入出力レンジ最適化による低ビットCiMベース推論器の設計手法","author_link":["614686","614688","614687","614685"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ニューラルネットワークの入出力レンジ最適化による低ビットCiMベース推論器の設計手法"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"シミュレーション","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2023-11-10","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学大学院工学系研究科"},{"subitem_text_value":"東京大学大学院工学系研究科"},{"subitem_text_value":"東京大学大学院工学系研究科"},{"subitem_text_value":"東京大学大学院工学系研究科"}]},"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/228906/files/IPSJ-SLDM23204039.pdf","label":"IPSJ-SLDM23204039.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLDM23204039.pdf","filesize":[{"value":"1.5 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"10"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"6adeb19f-0fb5-49a4-8084-c74c880b4b14","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 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":"山田, 歩"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"三澤, 奈央子"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松井, 千尋"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"竹内, 健"}],"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":"本研究では，ReRAM Computation-in-Memory（CiM）によるニューラルネットワークアクセラレータの更なる高効率化のため，高推論精度を保ちつつ入出力コンバータの低ビット化・レンジの自動設計を可能にする学習アルゴリズム LIORAT を提案する．LIORAT による低ビット化・ニューラルネットワークの各層についての適切なレンジ決定は look-up table（LUT）ベースの活性化関数計算を可能にする．さらに，LUT の書き換え可能性を応用することでメモリの書き込みばらつき等を含む，不可避なデバイスエラーへの耐性向上が見込まれることを報告する．シミュレーションによる評価は ResNet-32，CIFAR-10 データセットで行った．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"2","bibliographic_titles":[{"bibliographic_title":"研究報告システムとLSIの設計技術（SLDM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2023-11-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"39","bibliographicVolumeNumber":"2023-SLDM-204"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T11:40:36.352682+00:00","created":"2025-01-19T01:28:02.320669+00:00","links":{}}