{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:20:31Z","timestamp":1742912431652,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030594183"},{"type":"electronic","value":"9783030594190"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-59419-0_23","type":"book-chapter","created":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T16:57:43Z","timestamp":1600707463000},"page":"372-388","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["HEGJoin: Heterogeneous CPU-GPU Epsilon Grids for Accelerated Distance Similarity Join"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9716-1502","authenticated-orcid":false,"given":"Benoit","family":"Gallet","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0826-6204","authenticated-orcid":false,"given":"Michael","family":"Gowanlock","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,22]]},"reference":[{"unstructured":"Alam, S., Albareti, F., Prieto, C., et al.: The eleventh and twelfth data releases of the sloan digital sky survey: final data from SDSS-III. Astrophys. J. Suppl. Ser. 219, 12 (2015)","key":"23_CR1"},{"doi-asserted-by":"crossref","unstructured":"Awad, M.A., Ashkiani, S., Johnson, R., Farach-Colton, M., Owens, J.D.: Engineering a High-performance GPU B-Tree. In: Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming, pp. 145\u2013157 (2019)","key":"23_CR2","DOI":"10.1145\/3293883.3295706"},{"issue":"3","key":"23_CR3","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1007\/BF00288683","volume":"1","author":"R Bayer","year":"1972","unstructured":"Bayer, R., McCreight, E.M.: Organization and maintenance of large ordered indexes. Acta Informatica 1(3), 173\u2013189 (1972)","journal-title":"Acta Informatica"},{"doi-asserted-by":"crossref","unstructured":"Beckmann, N., Kriegel, H.P., Schneider, R., Seeger, B.: The R*-tree: an efficient and robust access method for points and rectangles. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 322\u2013331 (1990)","key":"23_CR4","DOI":"10.1145\/93605.98741"},{"key":"23_CR5","doi-asserted-by":"publisher","DOI":"10.1515\/9781400874668","volume-title":"Adaptive Control Processes: A Guided Tour","author":"R Bellman","year":"1961","unstructured":"Bellman, R.: Adaptive Control Processes: A Guided Tour. Princeton University Press, Princeton (1961)"},{"issue":"9","key":"23_CR6","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1145\/361002.361007","volume":"18","author":"JL Bentley","year":"1975","unstructured":"Bentley, J.L.: Multidimensional binary search trees used for associative searching. Commun. ACM 18(9), 509\u2013517 (1975)","journal-title":"Commun. ACM"},{"doi-asserted-by":"crossref","unstructured":"B\u00f6hm, C., Braunm\u00fcller, B., Krebs, F., Kriegel, H.P.: Epsilon grid order: an algorithm for the similarity join on massive high-dimensional data. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 379\u2013388 (2001)","key":"23_CR7","DOI":"10.1145\/376284.375714"},{"unstructured":"B\u00f6hm, C., Noll, R., Plant, C., Zherdin, A.: Index-supported similarity join on graphics processors, pp. 57\u201366 (2009)","key":"23_CR8"},{"issue":"2","key":"23_CR9","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1145\/356770.356776","volume":"11","author":"D Comer","year":"1979","unstructured":"Comer, D.: The ubiquitous B-tree. ACM Comput. Surv. 11(2), 121\u2013137 (1979)","journal-title":"ACM Comput. Surv."},{"issue":"1","key":"23_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/BF00288933","volume":"4","author":"RA Finkel","year":"1974","unstructured":"Finkel, R.A., Bentley, J.L.: Quad trees: a data structure for retrieval on composite keys. Acta Informatica 4(1), 1\u20139 (1974)","journal-title":"Acta Informatica"},{"doi-asserted-by":"crossref","unstructured":"Gallet, B., Gowanlock, M.: Load imbalance mitigation optimizations for GPU-accelerated similarity joins. In: Proceedings of the 2019 IEEE International Parallel and Distributed Processing Symposium Workshops, pp. 396\u2013405 (2019)","key":"23_CR11","DOI":"10.1109\/IPDPSW.2019.00078"},{"doi-asserted-by":"crossref","unstructured":"Gowanlock, M.: KNN-joins using a hybrid approach: exploiting CPU\/GPU workload characteristics. In: Proceedings of the 12th Workshop on General Purpose Processing Using GPUs, pp. 33\u201342 (2019)","key":"23_CR12","DOI":"10.1145\/3300053.3319417"},{"key":"23_CR13","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.jpdc.2019.06.005","volume":"133","author":"M Gowanlock","year":"2019","unstructured":"Gowanlock, M., Karsin, B.: Accelerating the similarity self-join using the GPU. J. Parallel Distrib. Comput. 133, 107\u2013123 (2019)","journal-title":"J. Parallel Distrib. Comput."},{"issue":"2","key":"23_CR14","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1145\/971697.602266","volume":"14","author":"A Guttman","year":"1984","unstructured":"Guttman, A.: R-trees: a dynamic index structure for spatial searching. SIGMOD Rec. 14(2), 47\u201357 (1984)","journal-title":"SIGMOD Rec."},{"issue":"4","key":"23_CR15","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1007\/s00778-012-0305-7","volume":"22","author":"DV Kalashnikov","year":"2013","unstructured":"Kalashnikov, D.V.: Super-EGO: fast multi-dimensional similarity join. VLDB J. 22(4), 561\u2013585 (2013)","journal-title":"VLDB J."},{"issue":"8","key":"23_CR16","doi-asserted-by":"publisher","first-page":"2258","DOI":"10.1109\/TPDS.2014.2347041","volume":"26","author":"J Kim","year":"2015","unstructured":"Kim, J., Jeong, W., Nam, B.: Exploiting massive parallelism for indexing multi-dimensional datasets on the GPU. IEEE Trans. Parallel Distrib. Syst. 26(8), 2258\u20132271 (2015)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"issue":"8","key":"23_CR17","doi-asserted-by":"publisher","first-page":"1195","DOI":"10.1016\/j.jpdc.2013.03.015","volume":"73","author":"J Kim","year":"2013","unstructured":"Kim, J., Kim, S.G., Nam, B.: parallel multi-dimensional range query processing with R-trees on GPU. J. Parallel Distribut. Comput. 73(8), 1195\u20131207 (2013)","journal-title":"J. Parallel Distribut. Comput."},{"key":"23_CR18","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.jpdc.2017.10.015","volume":"113","author":"J Kim","year":"2018","unstructured":"Kim, J., Nam, B.: Co-processing heterogeneous parallel index for multi-dimensional datasets. J. Parallel Distrib. Comput. 113, 195\u2013203 (2018)","journal-title":"J. Parallel Distrib. Comput."},{"doi-asserted-by":"crossref","unstructured":"Lieberman, M.D., Sankaranarayanan, J., Samet, H.: A fast similarity join algorithm using graphics processing units. In: 2008 IEEE 24th International Conference on Data Engineering, pp. 1111\u20131120 (2008)","key":"23_CR19","DOI":"10.1109\/ICDE.2008.4497520"},{"unstructured":"MIT Haystack Observatory: Space Weather Datasets. ftp:\/\/gemini.haystack.mit.edu\/pub\/informatics\/dbscandat.zip. Accessed 27 Feb 2020","key":"23_CR20"},{"doi-asserted-by":"crossref","unstructured":"Prasad, S.K., McDermott, M., He, X., Puri, S.: GPU-based parallel R-tree construction and querying. In: 2015 IEEE International Parallel and Distributed Processing Symposium Workshops, pp. 618\u2013627 (2015)","key":"23_CR21","DOI":"10.1109\/IPDPSW.2015.127"},{"unstructured":"Sellis, T., Roussopoulos, N., Faloutsos, C.: The R+-tree: a dynamic index for multi-dimensional objects. In: Proceedings of the 13th VLDB Conference, pp. 507\u2013518 (1987)","key":"23_CR22"},{"doi-asserted-by":"crossref","unstructured":"Shahvarani, A., Jacobsen, H.A.: A Hybrid B+-tree as solution for in-memory indexing on CPU-GPU heterogeneous computing platforms. In: Proceedings of the International Conference on Management of Data, pp. 1523\u20131538 (2016)","key":"23_CR23","DOI":"10.1145\/2882903.2882918"},{"doi-asserted-by":"crossref","unstructured":"Yan, Z., Lin, Y., Peng, L., Zhang, W.: Harmonia: a high throughput B+tree for GPUs. In: Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming, pp. 133\u2013144 (2019)","key":"23_CR24","DOI":"10.1145\/3293883.3295704"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-59419-0_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T17:53:22Z","timestamp":1710266002000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-59419-0_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030594183","9783030594190"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59419-0_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"22 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jeju","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/db.pknu.ac.kr\/dasfaa2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"487","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"119","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"23","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.11","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6.81","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"15 demo papers and 4 industrial papers","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}