{"_buckets": {"deposit": "6d6da140-2473-4494-926b-9b13879d41f3"}, "_deposit": {"id": "24870", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "24870"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00024870", "sets": ["314"]}, "author_link": ["73986", "73987", "73988", "73989", "73990"], "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2017-09-01", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "9", "bibliographicPageEnd": "2673", "bibliographicPageStart": "2663", "bibliographicVolumeNumber": "28", "bibliographic_titles": [{"bibliographic_title": "IEEE Transactions on Parallel and Distributed Systems", "bibliographic_titleLang": "en"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "The problem of scaling out relational join performance for large data sets in the database management system (DBMS) has been studied for years. Although in-memory DBMS engines can reduce load times by storing data in the main memory, join queries still remain computationally expensive. Modern graphics processing units (GPUs) provide massively parallel computing and may enhance the performance of such join queries; however, it is not clear yet in what condition relational joins perform well on GPUs. In this paper, we identify the performance characteristics of GPU computing for relational joins by implementing several well-known GPU-based join algorithms under various configurations. Experimental results indicate that the speedup ratio of GPU-based relational joins to CPU-based counterparts depends on the number of compute cores, the size of data sets, join conditions, and join algorithms. In the best case, the speedup ratios are up to 6.67 times for non-index joins, 9.41 times for sort index joins, and 2.55 times for hash joins. The execution time of GPU-based implementation for index joins, on the other hand, is only about 0.696 times less than the execution time of the CPU’s counterparts.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "DOI", "subitem_identifier_uri": "http://doi.org/10.1109/TPDS.2017.2677451"}, {"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/27090"}]}, "item_10_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "IEEE", "subitem_publisher_language": "en"}]}, "item_10_relation_11": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type": "isVersionOf", "subitem_relation_type_id": {"subitem_relation_type_id_text": "https://doi.org/10.1109/TPDS.2017.2677451", "subitem_relation_type_select": "DOI"}}]}, "item_10_rights_12": {"attribute_name": "権利", "attribute_value_mlt": [{"subitem_rights": "“© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”", "subitem_rights_language": "en"}]}, "item_10_select_15": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_select_item": "author"}]}, "item_10_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "1045-9219", "subitem_source_identifier_type": "PISSN"}]}, "item_1615787544753": {"attribute_name": "出版タイプ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_ab4af688f83e57aa", "subitem_version_type": "AM"}]}, "item_access_right": {"attribute_name": "アクセス権", "attribute_value_mlt": [{"subitem_access_right": "open access", "subitem_access_right_uri": "http://purl.org/coar/access_right/c_abf2"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Makoto, Yabuta", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "73986", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Anh, Nguyen", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "73987", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Shinpei, Kato", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "73988", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Masato, Edahiro", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "73989", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Hideyuki, Kawashima", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "73990", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2018-02-22"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "Relational_Joins_on_GPUs_A_Closer_Look.pdf", "filesize": [{"value": "6.7 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_note", "mimetype": "application/pdf", "size": 6700000.0, "url": {"label": "Relational_Joins_on_GPUs_A_Closer_Look.pdf", "objectType": "fulltext", "url": "https://nagoya.repo.nii.ac.jp/record/24870/files/Relational_Joins_on_GPUs_A_Closer_Look.pdf"}, "version_id": "40a8a389-f4ea-49c5-bc4d-b053d1eff89f"}]}, "item_keyword": {"attribute_name": "キーワード", "attribute_value_mlt": [{"subitem_subject": "Graphics processors", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Query processing", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Parallelism and concurrency", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "Relational Joins on GPUs: A Closer Look", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Relational Joins on GPUs: A Closer Look", "subitem_title_language": "en"}]}, "item_type_id": "10", "owner": "1", "path": ["314"], "permalink_uri": "http://hdl.handle.net/2237/27090", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2017-11-09"}, "publish_date": "2017-11-09", "publish_status": "0", "recid": "24870", "relation": {}, "relation_version_is_last": true, "title": ["Relational Joins on GPUs: A Closer Look"], "weko_shared_id": -1}