{"id":"https://openalex.org/W4281741895","doi":"https://doi.org/10.1145/3489048.3522644","title":"A Comprehensive Empirical Study of Query Performance Across GPU DBMSes","display_name":"A Comprehensive Empirical Study of Query Performance Across GPU DBMSes","publication_year":2022,"publication_date":"2022-06-02","ids":{"openalex":"https://openalex.org/W4281741895","doi":"https://doi.org/10.1145/3489048.3522644"},"language":"en","primary_location":{"id":"doi:10.1145/3489048.3522644","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3489048.3522644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101626811","display_name":"Young\u2010Kyoon Suh","orcid":"https://orcid.org/0000-0003-3124-2566"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Young-Kyoon Suh","raw_affiliation_strings":["Kyungpook National University, Daegu, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Kyungpook National University, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007261439","display_name":"Junyoung An","orcid":"https://orcid.org/0009-0005-8294-7349"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junyoung An","raw_affiliation_strings":["Kyungpook National University, Daegu, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Kyungpook National University, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010776108","display_name":"Byungchul Tak","orcid":"https://orcid.org/0000-0002-8204-6816"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Byungchul Tak","raw_affiliation_strings":["School of Computer Science and Engineering, Kyungpook National University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Kyungpook National University, Republic of Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063225256","display_name":"Gap-Joo Na","orcid":null},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gap-Joo Na","raw_affiliation_strings":["Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101626811"],"corresponding_institution_ids":["https://openalex.org/I31419693"],"apc_list":null,"apc_paid":null,"fwci":0.3031,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57909569,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"51","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8882128000259399},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7019360065460205},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.556890070438385},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.5394670963287354},{"id":"https://openalex.org/keywords/online-aggregation","display_name":"Online aggregation","score":0.5348872542381287},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.503131091594696},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.497936487197876},{"id":"https://openalex.org/keywords/sargable","display_name":"Sargable","score":0.4767492711544037},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.42497286200523376},{"id":"https://openalex.org/keywords/web-query-classification","display_name":"Web query classification","score":0.42160671949386597},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4162874221801758},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35230645537376404},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.33720824122428894},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.24137374758720398},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.2169552445411682},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.19458740949630737}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8882128000259399},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7019360065460205},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.556890070438385},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.5394670963287354},{"id":"https://openalex.org/C24028149","wikidata":"https://www.wikidata.org/wiki/Q7094056","display_name":"Online aggregation","level":5,"score":0.5348872542381287},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.503131091594696},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.497936487197876},{"id":"https://openalex.org/C192939062","wikidata":"https://www.wikidata.org/wiki/Q104840822","display_name":"Sargable","level":4,"score":0.4767492711544037},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.42497286200523376},{"id":"https://openalex.org/C118689300","wikidata":"https://www.wikidata.org/wiki/Q7978614","display_name":"Web query classification","level":4,"score":0.42160671949386597},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4162874221801758},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35230645537376404},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.33720824122428894},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.24137374758720398},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2169552445411682},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.19458740949630737},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3489048.3522644","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3489048.3522644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1983602503","https://openalex.org/W2012449229","https://openalex.org/W2014839149","https://openalex.org/W2058884229","https://openalex.org/W2342922783","https://openalex.org/W2548100623","https://openalex.org/W2604961016","https://openalex.org/W3201461576"],"related_works":["https://openalex.org/W2096359267","https://openalex.org/W3125756434","https://openalex.org/W1560919561","https://openalex.org/W2901901036","https://openalex.org/W1793997780","https://openalex.org/W2013069866","https://openalex.org/W185198413","https://openalex.org/W2150741898","https://openalex.org/W2034583622","https://openalex.org/W2186703450"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"GPU":[3,38,90,166,177],"database":[4],"management":[5],"systems":[6,154],"(DBMSes)":[7],"have":[8,56,97],"rapidly":[9],"become":[10],"popular":[11],"largely":[12],"due":[13],"to":[14,62,67,79,142,157],"their":[15,45,77],"remarkable":[16],"acceleration":[17],"capability":[18],"obtained":[19,110],"through":[20],"extreme":[21],"parallelism":[22],"in":[23,48],"query":[24,46,85,126,145,171],"evaluations.":[25],"However,":[26],"there":[27],"has":[28],"been":[29],"relatively":[30],"little":[31],"study":[32,61],"on":[33,88,108,124],"the":[34,81,84,89,94,109,125,139,144,152],"characteristics":[35],"of":[36,44,83,121,169],"these":[37],"DBMSes":[39],"for":[40],"a":[41,58,69,113],"better":[42],"understanding":[43],"performance":[47],"various":[49],"contexts.":[50],"To":[51,92],"fill":[52],"this":[53],"gap,":[54],"we":[55,96],"conducted":[57,104],"rigorous":[59],"empirical":[60],"identify":[63],"such":[64,161],"factors":[65,75,141],"and":[66,76,99,103,128,134,176],"propose":[68],"structural":[70],"causal":[71],"model,":[72,95],"including":[73],"key":[74,140],"relationships,":[78],"explicate":[80],"variances":[82],"execution":[86],"times":[87],"DBMSes.":[91],"test":[93],"designed":[98],"run":[100],"comprehensive":[101],"experiments":[102],"in-depth":[105],"statistical":[106],"analyses":[107],"data.":[111],"As":[112],"result,":[114],"our":[115,148],"model":[116],"achieves":[117],"about":[118],"77%":[119],"amount":[120],"variance":[122],"explained":[123],"time":[127,133,137],"indicates":[129],"that":[130,151],"reducing":[131],"kernel":[132],"data":[135],"transfer":[136],"are":[138],"improve":[143],"time.":[146],"Also,":[147],"results":[149],"show":[150],"studied":[153],"still":[155],"need":[156],"resolve":[158],"several":[159],"concerns":[160],"as":[162],"bounded":[163],"processing":[164],"within":[165],"memory,":[167],"lack":[168],"rich":[170],"evaluation":[172],"operators,":[173],"limited":[174],"scalability,":[175],"under-utilization.":[178]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}
