{"created":"2025-01-19T01:46:25.549337+00:00","updated":"2025-01-19T07:34:55.375922+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00241679","sets":["1164:1579:11464:11813"]},"path":["11813"],"owner":"44499","recid":"241679","title":["並列化した多倍長精度疎行列・ベクトル乗算の性能評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-12-09"},"_buckets":{"deposit":"dc9c7585-5d79-4c75-bd20-646e2528118c"},"_deposit":{"id":"241679","pid":{"type":"depid","value":"241679","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"並列化した多倍長精度疎行列・ベクトル乗算の性能評価","author_link":["665783"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"並列化した多倍長精度疎行列・ベクトル乗算の性能評価"},{"subitem_title":"Performance evaluation of parallelized multiple-precision sparse matrix-vector multiplication","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"性能評価","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-12-09","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"静岡理工科大学"}]},"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/241679/files/IPSJ-ARC24259014.pdf","label":"IPSJ-ARC24259014.pdf"},"date":[{"dateType":"Available","dateValue":"2026-12-09"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ARC24259014.pdf","filesize":[{"value":"2.6 MB"}],"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":"5ddf81e4-f4b1-4193-870c-4ca86654ef11","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"幸谷, 智紀"}],"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":"BNCmatmul は倍精度ベースのマルチコンポーネント方式の多倍長精度と，整数ベースの任意精度方式の多倍長精度をサポートした，基本線形計算ライブラリである．SIMD 演算とOpenMP による並列化を取り入れた高速化を行っており，既存の MPLAPACK/MPBLAS と同等の多倍長精度線形計算を x86 CPU上で高速に実行することができる．本報告では，BNCmatmul に取り入れた SIMD 化した疎行列-ベクトル乗算 (SpMV) を並列化した実数 SpMV と，実数 SpMV をベースに実装した複素 SpMV の性能評価を行うとともに，Krylov 部分空間法に適用した結果について述べる．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"BNCmatmul is a basic linear algebra subprogram (BLAS) library that supports multiple-precision calculation based on both binary64-based multi-component-way and integer-based arbitrary precision floating-point arithmetic. It accelerates computations by incorporating SIMD operations and parallelization using OpenMP, enabling high-speed execution of multiple-precision linear calculations on x86 CPUs, comparable to the existing MPLAPACK/MPBLAS. In this report, we evaluate the performance of parallelized, SIMDized real sparse matrix-vector multiplication (SpMV) and the complex SpMV implementation based on the real SpMV. Additionally, we discuss its application to the Krylov subspace method.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告システム・アーキテクチャ（ARC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-12-09","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"14","bibliographicVolumeNumber":"2024-ARC-259"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":241679,"links":{}}