{"id":"https://openalex.org/W2037335597","doi":"https://doi.org/10.1109/bigdata.2014.7004365","title":"Connecting the dots: Triangle completion and related problems on large data sets using GPUs","display_name":"Connecting the dots: Triangle completion and related problems on large data sets using GPUs","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2037335597","doi":"https://doi.org/10.1109/bigdata.2014.7004365","mag":"2037335597"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2014.7004365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004365","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103977478","display_name":"Amlan Chatterjee","orcid":"https://orcid.org/0000-0001-5897-8624"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amlan Chatterjee","raw_affiliation_strings":["School of Computer Science, University of Oklahoma, Norman, USA","School of Computer Science, University of Oklahoma, Norman, USA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Oklahoma, Norman, USA","institution_ids":["https://openalex.org/I8692664"]},{"raw_affiliation_string":"School of Computer Science, University of Oklahoma, Norman, USA;","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101878770","display_name":"Sridhar Radhakrishnan","orcid":"https://orcid.org/0000-0002-0327-8134"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sridhar Radhakrishnan","raw_affiliation_strings":["School of Computer Science, University of Oklahoma, Norman, USA","School of Computer Science, University of Oklahoma, Norman, USA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Oklahoma, Norman, USA","institution_ids":["https://openalex.org/I8692664"]},{"raw_affiliation_string":"School of Computer Science, University of Oklahoma, Norman, USA;","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026213288","display_name":"Chandra N. Sekharan","orcid":"https://orcid.org/0000-0002-5784-7400"},"institutions":[{"id":"https://openalex.org/I1925986","display_name":"Loyola University Chicago","ror":"https://ror.org/04b6x2g63","country_code":"US","type":"education","lineage":["https://openalex.org/I1925986"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chandra N. Sekharan","raw_affiliation_strings":["Department of Computer Science, Loyola University Chicago, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Loyola University Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I1925986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2901,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.53502235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"5","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9984999895095825,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9905999898910522,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8323270678520203},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.7164298295974731},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5236291885375977},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.5139086246490479},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4989769458770752},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4864075183868408},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4821045696735382},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4756091237068176},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23295915126800537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.09302634000778198}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8323270678520203},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.7164298295974731},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5236291885375977},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.5139086246490479},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4989769458770752},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4864075183868408},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4821045696735382},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4756091237068176},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23295915126800537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.09302634000778198},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2014.7004365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004365","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","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":13,"referenced_works":["https://openalex.org/W247230535","https://openalex.org/W1970826706","https://openalex.org/W1994473607","https://openalex.org/W2012720017","https://openalex.org/W2101890615","https://openalex.org/W2102322109","https://openalex.org/W2110814195","https://openalex.org/W2115022330","https://openalex.org/W2117410972","https://openalex.org/W2136486572","https://openalex.org/W2146591355","https://openalex.org/W2158432527","https://openalex.org/W4240443285"],"related_works":["https://openalex.org/W2011840458","https://openalex.org/W3213381848","https://openalex.org/W2017587301","https://openalex.org/W2005148983","https://openalex.org/W2030707850","https://openalex.org/W4386975487","https://openalex.org/W2096672917","https://openalex.org/W2009169896","https://openalex.org/W2392023973","https://openalex.org/W2939411666"],"abstract_inverted_index":{"Studying":[0],"the":[1,18,43,47,53,85,110,115,132,169,187,201,205,218,224,236,256,272,300,331,351,382,386,395,404,408],"properties":[2,61,111,161],"of":[3,21,46,49,55,66,102,112,144,162,189,207,220,274,302,333,388,403],"Online":[4],"Social":[5],"Networks":[6],"(OSNs)":[7],"and":[8,35,41,88,121,138,231,242,282,311,343,356,394,399],"other":[9],"real":[10],"world":[11],"graphs":[12,28,57,116],"have":[13,122],"gained":[14],"importance":[15],"due":[16,108],"to":[17,98,109,130,234,364,401],"large":[19,27],"amount":[20],"information":[22],"available":[23,77],"from":[24,78],"them.":[25],"These":[26],"contain":[29],"data":[30,124,134],"that":[31,166,265,293,325],"can":[32,148],"be":[33],"analyzed":[34],"effectively":[36],"used":[37],"in":[38,158,183,186,200,204,223,276,304,336,381,385],"advertising,":[39],"security":[40],"improving":[42],"overall":[44],"experience":[45],"users":[48],"these":[50,56,100,150,163],"networks.":[51],"However,":[52],"analysis":[54],"for":[58,80,135,255,373],"studying":[59,159],"specific":[60],"requires":[62],"combinatorially":[63],"explosive":[64],"number":[65,188,206,219,273,301,332,387],"computations.":[67],"Compute":[68],"Unified":[69],"Device":[70],"Architecture":[71],"(CUDA)":[72],"is":[73,104,392],"a":[74,175,246,287,319,354,358,365,371],"programming":[75],"model":[76],"Nvidia":[79],"solving":[81],"general-purpose":[82],"problems":[83,103,238],"using":[84,96,127,239,353],"massively":[86],"parallel":[87],"highly":[89],"multi-threaded":[90],"Graphics":[91],"Processing":[92],"Units":[93],"(GPUs).":[94],"Therefore,":[95],"GPUs":[97],"solve":[99,235],"types":[101],"appropriate.":[105],"In":[106,152,226],"addition,":[107],"real-world":[113,164],"data,":[114],"being":[117],"considered":[118],"are":[119,156,397],"sparse":[120],"irregular":[123],"dependencies.":[125],"Hence,":[126],"efficient":[128],"techniques":[129],"store":[131],"graph":[133,171,247],"initial":[136],"preprocessing":[137],"final":[139],"computation":[140],"by":[141],"taking":[142],"advantage":[143],"heterogeneous":[145],"CPU-GPU":[146],"systems":[147],"address":[149],"issues.":[151],"this":[153,227],"paper,":[154,228],"we":[155,229,252,369],"interested":[157],"different":[160],"entities":[165],"transform":[167],"into":[168],"following":[170],"problems:":[172],"a)":[173,258],"identifying":[174,192,210],"missing":[176],"edge,":[177],"which":[178],"when":[179],"added":[180],"would":[181,198,216,379],"result":[182,199,380],"maximum":[184,202,383],"increase":[185,217,384],"triangles,":[190,208],"b)":[191,285],"an":[193,211,375],"existing":[194,212],"edge":[195,213,376],"whose":[196,214,377],"removal":[197,215],"decrease":[203],"c)":[209,317],"connected":[221,334],"components":[222,335],"graph.":[225],"develop":[230],"implement":[232,350],"algorithms":[233,254,352],"above":[237],"both":[240],"CPU":[241],"GPU.":[243,409],"Specifically,":[244],"given":[245],"G":[248,312,344],"=":[249,313,345],"(V,":[250,278,306,314,338,346],"E),":[251,315,347],"provide":[253],"following:":[257],"find":[259,286,318],"(vi,":[260,288,309,320,341],"Vj)":[261,289,321],"\u2209":[262],"E,":[263,291,323],"such":[264,292,324],"\u0394f-":[266],"\u0394cis":[267],"maximized,":[268,296],"where":[269,297,328],"\u0394fand":[270,298],"\u0394care":[271,299],"triangles":[275,303],"Gm=":[277,305,337],"E":[279,307,339],"\u222a(vi,":[280],"Vj))":[281,310,342],"G,":[283],"respectively,":[284,316],"\u03f5":[290,322],"\u0394c-":[294],"\u0394fis":[295],"\\":[308,340],"\u03a6c>":[326],"\u03a6c,":[327],"\u03a6cand":[329],"\u03a6care":[330],"respectively.":[348],"We":[349],"GPU":[355],"achieve":[357],"10":[359],"\u00d7":[360],"speedup":[361],"as":[362],"compared":[363,400],"sequential":[366],"implementation.":[367],"Thereafter,":[368],"design":[370],"heuristic":[372,391],"finding":[374],"existence":[378],"triangles.":[389],"The":[390],"implemented":[393],"results":[396],"reported":[398],"those":[402],"regular":[405],"algorithm":[406],"on":[407]},"counts_by_year":[{"year":2018,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}