{"id":"https://openalex.org/W4380668110","doi":"https://doi.org/10.1145/3592980.3595307","title":"Accelerating User-Defined Aggregate Functions (UDAF) with Block-wide Execution and JIT Compilation on GPUs","display_name":"Accelerating User-Defined Aggregate Functions (UDAF) with Block-wide Execution and JIT Compilation on GPUs","publication_year":2023,"publication_date":"2023-06-14","ids":{"openalex":"https://openalex.org/W4380668110","doi":"https://doi.org/10.1145/3592980.3595307"},"language":"en","primary_location":{"id":"doi:10.1145/3592980.3595307","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3592980.3595307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th International Workshop on Data Management on New Hardware","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/A5068295839","display_name":"Bobbi Yogatama","orcid":"https://orcid.org/0009-0002-7101-1068"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Bobbi Yogatama","raw_affiliation_strings":["University of Wisconsin-Madison, US"],"raw_orcid":"https://orcid.org/0009-0002-7101-1068","affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, US","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102972787","display_name":"Brandon Miller","orcid":"https://orcid.org/0009-0002-9240-4872"},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Brandon Miller","raw_affiliation_strings":["NVIDIA, US"],"raw_orcid":"https://orcid.org/0009-0002-9240-4872","affiliations":[{"raw_affiliation_string":"NVIDIA, US","institution_ids":["https://openalex.org/I1304085615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075611869","display_name":"Yunsong Wang","orcid":"https://orcid.org/0000-0001-5809-8141"},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yunsong Wang","raw_affiliation_strings":["NVIDIA, US"],"raw_orcid":"https://orcid.org/0000-0001-5809-8141","affiliations":[{"raw_affiliation_string":"NVIDIA, US","institution_ids":["https://openalex.org/I1304085615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083653923","display_name":"Graham Markall","orcid":"https://orcid.org/0009-0003-9005-1716"},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Graham Markall","raw_affiliation_strings":["NVIDIA, UK"],"raw_orcid":"https://orcid.org/0009-0003-9005-1716","affiliations":[{"raw_affiliation_string":"NVIDIA, UK","institution_ids":["https://openalex.org/I1304085615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001661918","display_name":"Jacob Hemstad","orcid":"https://orcid.org/0009-0009-5777-3657"},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jacob Hemstad","raw_affiliation_strings":["NVIDIA, US"],"raw_orcid":"https://orcid.org/0009-0009-5777-3657","affiliations":[{"raw_affiliation_string":"NVIDIA, US","institution_ids":["https://openalex.org/I1304085615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049698352","display_name":"Gregory M. Kimball","orcid":"https://orcid.org/0000-0003-1075-1417"},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gregory Kimball","raw_affiliation_strings":["NVIDIA, US"],"raw_orcid":"https://orcid.org/0000-0003-1075-1417","affiliations":[{"raw_affiliation_string":"NVIDIA, US","institution_ids":["https://openalex.org/I1304085615"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100734491","display_name":"Xiangyao Yu","orcid":"https://orcid.org/0009-0001-0785-2519"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiangyao Yu","raw_affiliation_strings":["University of Wisconsin-Madison, US"],"raw_orcid":"https://orcid.org/0009-0001-0785-2519","affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, US","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5068295839"],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":null,"apc_paid":null,"fwci":0.9838,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7645549,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"19","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9983000159263611,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.996999979019165,"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/aggregate","display_name":"Aggregate (composite)","score":0.8297828435897827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8170812726020813},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6536918878555298},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.525350034236908},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5004293918609619},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.3202739953994751},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.23562157154083252}],"concepts":[{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.8297828435897827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8170812726020813},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6536918878555298},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.525350034236908},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5004293918609619},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.3202739953994751},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.23562157154083252},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3592980.3595307","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3592980.3595307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th International Workshop on Data Management on New Hardware","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2004772832","https://openalex.org/W2012449229","https://openalex.org/W2053955827","https://openalex.org/W2068418796","https://openalex.org/W2106329447","https://openalex.org/W2127766448","https://openalex.org/W2145061307","https://openalex.org/W2276395270","https://openalex.org/W2440046523","https://openalex.org/W2547543723","https://openalex.org/W2548941637","https://openalex.org/W2592936523","https://openalex.org/W2604606554","https://openalex.org/W2623697208","https://openalex.org/W2752640170","https://openalex.org/W2798422034","https://openalex.org/W2908321983","https://openalex.org/W3011144431","https://openalex.org/W3028661980","https://openalex.org/W3109106363","https://openalex.org/W3129890341","https://openalex.org/W3177047120","https://openalex.org/W4281927114","https://openalex.org/W4282554945","https://openalex.org/W4312559100"],"related_works":["https://openalex.org/W2418291489","https://openalex.org/W2068121105","https://openalex.org/W2372403409","https://openalex.org/W3096519538","https://openalex.org/W2023578311","https://openalex.org/W1973516247","https://openalex.org/W4241166160","https://openalex.org/W2384826897","https://openalex.org/W1997466117","https://openalex.org/W2029210135"],"abstract_inverted_index":{"The":[0],"GPU-accelerated":[1],"DataFrame":[2,20],"library":[3],"cuDF":[4],"has":[5],"become":[6],"increasingly":[7],"popular":[8],"for":[9],"data":[10],"analytics":[11],"applications":[12],"due":[13],"to":[14,41],"its":[15],"superior":[16],"performance":[17],"against":[18],"CPU-based":[19],"libraries":[21],"such":[22],"as":[23],"Pandas.":[24],"One":[25],"of":[26,47],"the":[27,48],"frequently-used":[28],"operations":[29,51],"in":[30],"dataframe":[31],"manipulation":[32],"is":[33],"user-defined":[34],"aggregate":[35,44,50],"functions":[36],"(UDAFs).":[37],"UDAFs":[38],"allow":[39],"users":[40],"define":[42],"custom":[43],"routines":[45],"outside":[46],"pre-defined":[49],"(Sum(),":[52],"Max(),":[53],"Avg(),":[54],"etc.)":[55]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
