{"id":"https://openalex.org/W2954265087","doi":"https://doi.org/10.1145/3331184.3331376","title":"Accelerating Exact Inner Product Retrieval by CPU-GPU Systems","display_name":"Accelerating Exact Inner Product Retrieval by CPU-GPU Systems","publication_year":2019,"publication_date":"2019-07-18","ids":{"openalex":"https://openalex.org/W2954265087","doi":"https://doi.org/10.1145/3331184.3331376","mag":"2954265087"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3331184.3331376","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5045357216","display_name":"Xiang Long","orcid":"https://orcid.org/0000-0002-0589-8839"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"funder","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"funder","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Xiang","raw_affiliation_strings":["Southern University of Science and Technology & Peng Cheng Laboratory, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology & Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101455930","display_name":"Bo Tang","orcid":"https://orcid.org/0000-0001-8424-0092"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"funder","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"funder","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Tang","raw_affiliation_strings":["Southern University of Science and Technology & Peng Cheng Laboratory, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology & Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I3045169105"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007919135","display_name":"Chuan Yang","orcid":"https://orcid.org/0000-0002-0343-9065"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"funder","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"funder","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuan Yang","raw_affiliation_strings":["Southern University of Science and Technology & Peng Cheng Laboratory, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology & Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I3045169105"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.058,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":8,"citation_normalized_percentile":{"value":0.698551,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":83,"max":84},"biblio":{"volume":null,"issue":null,"first_page":"1277","last_page":"1280"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9987,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9987,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9965,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9956,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/graphics-processing-unit","display_name":"Graphics processing unit","score":0.4822091},{"id":"https://openalex.org/keywords/multi-core-processor","display_name":"Multi-core processor","score":0.45462325},{"id":"https://openalex.org/keywords/subroutine","display_name":"Subroutine","score":0.45257232}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8496074},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8460831},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.67697954},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5936463},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5405148},{"id":"https://openalex.org/C49154492","wikidata":"https://www.wikidata.org/wiki/Q5300","display_name":"Central processing unit","level":2,"score":0.5101238},{"id":"https://openalex.org/C50630238","wikidata":"https://www.wikidata.org/wiki/Q971505","display_name":"General-purpose computing on graphics processing units","level":3,"score":0.5056405},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.4939385},{"id":"https://openalex.org/C2779851693","wikidata":"https://www.wikidata.org/wiki/Q183484","display_name":"Graphics processing unit","level":2,"score":0.4822091},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.48169908},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.4727391},{"id":"https://openalex.org/C78766204","wikidata":"https://www.wikidata.org/wiki/Q555032","display_name":"Multi-core processor","level":2,"score":0.45462325},{"id":"https://openalex.org/C96147967","wikidata":"https://www.wikidata.org/wiki/Q190686","display_name":"Subroutine","level":2,"score":0.45257232},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4518565},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.40504855},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18201599},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.16714922},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.1635825},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.13595709},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12401727},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3331184.3331376","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.48}],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61802163"}],"datasets":[],"versions":[],"referenced_works_count":4,"referenced_works":["https://openalex.org/W1971187657","https://openalex.org/W1977046819","https://openalex.org/W2249264440","https://openalex.org/W2612493630"],"related_works":["https://openalex.org/W3158047141","https://openalex.org/W2388314963","https://openalex.org/W2167646277","https://openalex.org/W2151046618","https://openalex.org/W2063573318","https://openalex.org/W2027443981","https://openalex.org/W1972148443","https://openalex.org/W1969233021","https://openalex.org/W1656096860","https://openalex.org/W151175334"],"abstract_inverted_index":{"Recommender":[0],"systems":[1,82,122],"are":[2,133],"widely":[3],"used":[4],"in":[5,20,67,110,136],"many":[6],"applications,":[7],"e.g.,":[8],"social":[9],"network,":[10],"e-commerce.":[11],"Inner":[12],"product":[13,34,49],"retrieval":[14],"IPR":[15,88,97,111,131],"is":[16,47,63,76],"the":[17,59,64,85,92,96,104,118,127,142],"core":[18],"subroutine":[19],"Matrix":[21],"Factorization":[22],"(MF)":[23],"based":[24],"recommender":[25],"systems.":[26,138],"It":[27],"consists":[28],"of":[29,44,87,95,107,120,130,144],"two":[30],"phases:":[31],"i)":[32],"inner":[33,48],"computation":[35,50,60,128],"and":[36,70],"ii)":[37],"top-k":[38],"items":[39],"retrieval.":[40],"The":[41],"performance":[42,86],"bottleneck":[43],"existing":[45],"solutions":[46,89,112],"phase.":[51],"Exploiting":[52],"Graphics":[53],"Processing":[54],"Units":[55],"(GPUs)":[56],"to":[57,79,83,91,123],"accelerate":[58],"intensive":[61],"workloads":[62],"gold":[65],"standard":[66,149],"data":[68],"mining":[69],"machine":[71],"learning":[72],"communities.":[73],"However,":[74],"it":[75],"not":[77],"trivial":[78],"apply":[80],"CPU-GPU":[81,121,137],"boost":[84],"due":[90],"nature":[93],"complex":[94],"problem.":[98],"In":[99],"this":[100],"work,":[101],"we":[102,116,140],"analyze":[103],"time":[105],"cost":[106],"each":[108],"phase":[109],"at":[113],"first.":[114],"Second,":[115],"exploit":[117],"characteristics":[119],"improve":[124],"performance.":[125],"Specifically,":[126],"tasks":[129],"solution":[132],"heterogeneously":[134],"processed":[135],"Third,":[139],"demonstrate":[141],"efficiency":[143],"our":[145],"proposal":[146],"on":[147],"four":[148],"real":[150],"datasets.":[151]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2954265087","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2025-02-15T22:52:47.532522","created_date":"2019-07-12"}