{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00231141","sets":["934:1119:11299:11377"]},"path":["11377"],"owner":"44499","recid":"231141","title":["Numerical Behavior of Mixed Precision Iterative Refinement Using the BiCGSTAB Method"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-11-29"},"_buckets":{"deposit":"587722e8-ee5d-4f09-8c40-75a3fee7af00"},"_deposit":{"id":"231141","pid":{"type":"depid","value":"231141","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Numerical Behavior of Mixed Precision Iterative Refinement Using the BiCGSTAB Method","author_link":["623534","623530","623532","623535","623531","623533"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Numerical Behavior of Mixed Precision Iterative Refinement Using the BiCGSTAB Method"},{"subitem_title":"Numerical Behavior of Mixed Precision Iterative Refinement Using the BiCGSTAB Method","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"sparse linear solver, iterative refinement, low precision computing, mixed precision algorithm, BiCGSTAB method","subitem_subject_scheme":"Other"}]},"item_type_id":"3","publish_date":"2023-11-29","item_3_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Technology, Hokkaido University"},{"subitem_text_value":"Information Initiative Center, Hokkaido University"},{"subitem_text_value":"Information Initiative Center, Hokkaido University"}]},"item_3_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Technology, Hokkaido University","subitem_text_language":"en"},{"subitem_text_value":"Information Initiative Center, Hokkaido University","subitem_text_language":"en"},{"subitem_text_value":"Information Initiative Center, Hokkaido University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/231141/files/IPSJ-TACS1602002.pdf","label":"IPSJ-TACS1602002.pdf"},"date":[{"dateType":"Available","dateValue":"2025-11-29"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-TACS1602002.pdf","filesize":[{"value":"797.1 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"16"},{"tax":["include_tax"],"price":"0","billingrole":"11"},{"tax":["include_tax"],"price":"0","billingrole":"14"},{"tax":["include_tax"],"price":"0","billingrole":"15"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"946f7ef2-e6e5-4789-a6dc-b6b1c7e8b255","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_3_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yingqi, Zhao"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Fukaya"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Iwashita"}],"nameIdentifiers":[{}]}]},"item_3_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yingqi, Zhao","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Fukaya","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Iwashita","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11833852","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_3_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7829","subitem_source_identifier_type":"ISSN"}]},"item_3_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Mixed precision numerical methods using low precision computing have attracted much attention under recent computational hardware trends. In this research, we focus on solving large, sparse, and non-symmetric linear systems, and consider developing a numerical method based on a mixed precision variant of the iterative refinement scheme (MP-IR), in which we can exploit low precision computing and provide a computed solution with the same accuracy as that obtained by conventional methods without low precision computing. We employ the BiCGSTAB solver with FP32 as an inner solver of MP-IR and investigate its numerical behavior through numerical experiments. From the analyses on the obtained results including a comparison with MP-IR using GMRES(m), which is also known as MP-GMRES(m) and has been widely studied, the potential of MP-IR using BiCGSTAB has been confirmed. Together with other obtained results, this paper provides insights that are helpful in developing an efficient mixed precision linear solver for practical applications.\n------------------------------\nThis is a preprint of an article intended for publication Journal of\nInformation Processing(JIP). This preprint should not be cited. This\narticle should be cited as: Journal of Information Processing Vol.31(2023) (online)\n------------------------------","subitem_description_type":"Other"}]},"item_3_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Mixed precision numerical methods using low precision computing have attracted much attention under recent computational hardware trends. In this research, we focus on solving large, sparse, and non-symmetric linear systems, and consider developing a numerical method based on a mixed precision variant of the iterative refinement scheme (MP-IR), in which we can exploit low precision computing and provide a computed solution with the same accuracy as that obtained by conventional methods without low precision computing. We employ the BiCGSTAB solver with FP32 as an inner solver of MP-IR and investigate its numerical behavior through numerical experiments. From the analyses on the obtained results including a comparison with MP-IR using GMRES(m), which is also known as MP-GMRES(m) and has been widely studied, the potential of MP-IR using BiCGSTAB has been confirmed. Together with other obtained results, this paper provides insights that are helpful in developing an efficient mixed precision linear solver for practical applications.\n------------------------------\nThis is a preprint of an article intended for publication Journal of\nInformation Processing(JIP). This preprint should not be cited. This\narticle should be cited as: Journal of Information Processing Vol.31(2023) (online)\n------------------------------","subitem_description_type":"Other"}]},"item_3_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌コンピューティングシステム（ACS）"}],"bibliographicIssueDates":{"bibliographicIssueDate":"2023-11-29","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"16"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:31:17.374181+00:00","updated":"2025-01-19T10:52:19.558666+00:00","id":231141}