{"id":"https://openalex.org/W2004388081","doi":"https://doi.org/10.1109/bigdata.2014.7004219","title":"Parallel Breadth First Search on GPU clusters","display_name":"Parallel Breadth First Search on GPU clusters","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2004388081","doi":"https://doi.org/10.1109/bigdata.2014.7004219","mag":"2004388081"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2014.7004219","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004219","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":"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/A5110206073","display_name":"Zhisong Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099077","display_name":"Blazegraph (United States)","ror":"https://ror.org/00vwzq490","country_code":"US","type":"company","lineage":["https://openalex.org/I4210099077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhisong Fu","raw_affiliation_strings":["SYSTAP, LLC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SYSTAP, LLC","institution_ids":["https://openalex.org/I4210099077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047269612","display_name":"Harish Kumar Dasari","orcid":null},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Harish Kumar Dasari","raw_affiliation_strings":["University of Utah","University of Utah,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Utah","institution_ids":["https://openalex.org/I223532165"]},{"raw_affiliation_string":"University of Utah,","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058340836","display_name":"Bradley R. Bebee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099077","display_name":"Blazegraph (United States)","ror":"https://ror.org/00vwzq490","country_code":"US","type":"company","lineage":["https://openalex.org/I4210099077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bradley Bebee","raw_affiliation_strings":["SYSTAP, LLC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SYSTAP, LLC","institution_ids":["https://openalex.org/I4210099077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018125253","display_name":"Martin Berzins","orcid":"https://orcid.org/0000-0002-5419-0634"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martin Berzins","raw_affiliation_strings":["University of Utah","University of Utah,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Utah","institution_ids":["https://openalex.org/I223532165"]},{"raw_affiliation_string":"University of Utah,","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015843974","display_name":"Bryan Thompson","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099077","display_name":"Blazegraph (United States)","ror":"https://ror.org/00vwzq490","country_code":"US","type":"company","lineage":["https://openalex.org/I4210099077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bryan Thompson","raw_affiliation_strings":["SYSTAP, LLC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SYSTAP, LLC","institution_ids":["https://openalex.org/I4210099077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.7082,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.94560016,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"47","issue":null,"first_page":"110","last_page":"118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9998999834060669,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.996999979019165,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.9966999888420105,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8713066577911377},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.7447335720062256},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6977535486221313},{"id":"https://openalex.org/keywords/xeon","display_name":"Xeon","score":0.6553220152854919},{"id":"https://openalex.org/keywords/memory-bandwidth","display_name":"Memory bandwidth","score":0.6410680413246155},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.6053739786148071},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4888297915458679},{"id":"https://openalex.org/keywords/coprocessor","display_name":"Coprocessor","score":0.47069835662841797},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.45508888363838196},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.44873175024986267},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44072383642196655},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1601771116256714},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.1592443287372589}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8713066577911377},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.7447335720062256},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6977535486221313},{"id":"https://openalex.org/C145108525","wikidata":"https://www.wikidata.org/wiki/Q656154","display_name":"Xeon","level":2,"score":0.6553220152854919},{"id":"https://openalex.org/C188045654","wikidata":"https://www.wikidata.org/wiki/Q17148339","display_name":"Memory bandwidth","level":2,"score":0.6410680413246155},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.6053739786148071},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4888297915458679},{"id":"https://openalex.org/C86111242","wikidata":"https://www.wikidata.org/wiki/Q859595","display_name":"Coprocessor","level":2,"score":0.47069835662841797},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.45508888363838196},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.44873175024986267},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44072383642196655},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1601771116256714},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.1592443287372589},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2014.7004219","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004219","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":[{"id":"https://metadata.un.org/sdg/9","score":0.5600000023841858,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W78077100","https://openalex.org/W1482680420","https://openalex.org/W1621476058","https://openalex.org/W1788180225","https://openalex.org/W1884976205","https://openalex.org/W1967810620","https://openalex.org/W1967810725","https://openalex.org/W1982056505","https://openalex.org/W1985291160","https://openalex.org/W1994840070","https://openalex.org/W2004951603","https://openalex.org/W2020385058","https://openalex.org/W2021685712","https://openalex.org/W2063597636","https://openalex.org/W2078174680","https://openalex.org/W2085761620","https://openalex.org/W2093739557","https://openalex.org/W2096544401","https://openalex.org/W2110942501","https://openalex.org/W2123538390","https://openalex.org/W2124200646","https://openalex.org/W2127927798","https://openalex.org/W2128653745","https://openalex.org/W2130488390","https://openalex.org/W2141380216","https://openalex.org/W2142184646","https://openalex.org/W2157427457","https://openalex.org/W2163501979","https://openalex.org/W2164041305","https://openalex.org/W2166860697","https://openalex.org/W2397037157","https://openalex.org/W2399032974","https://openalex.org/W2910856820","https://openalex.org/W2949338522","https://openalex.org/W2951113132","https://openalex.org/W3142035222","https://openalex.org/W4230357857","https://openalex.org/W6603201521","https://openalex.org/W6638233953","https://openalex.org/W6639305158","https://openalex.org/W6648939576","https://openalex.org/W6679180178"],"related_works":["https://openalex.org/W3145240193","https://openalex.org/W2147073383","https://openalex.org/W2540373069","https://openalex.org/W2085105049","https://openalex.org/W1507301366","https://openalex.org/W3203561460","https://openalex.org/W4251138667","https://openalex.org/W4401155055","https://openalex.org/W3009624197","https://openalex.org/W2165099691"],"abstract_inverted_index":{"Fast,":[0],"scalable,":[1],"low-cost,":[2],"and":[3,18,33,36,50,56,68,90,138,156,163,177],"low-power":[4],"execution":[5],"of":[6,16,77,134,147],"parallel":[7,52,112,168],"graph":[8,113,159,169],"algorithms":[9,114],"is":[10,119],"important":[11],"for":[12,111],"a":[13,41,92,126,166],"wide":[14],"variety":[15],"commercial":[17],"public":[19],"sector":[20],"applications.":[21],"Breadth":[22],"First":[23],"Search":[24],"(BFS)":[25],"imposes":[26],"an":[27],"extreme":[28],"burden":[29],"on":[30,154,157,161],"memory":[31,95],"bandwidth":[32,96],"network":[34],"communications":[35],"has":[37,103],"been":[38],"proposed":[39],"as":[40,65],"benchmark":[42],"that":[43,61,105,117,123,128,165],"may":[44],"be":[45,172],"used":[46],"to":[47,85,121],"evaluate":[48],"current":[49],"future":[51,79],"computers.":[53],"Hardware":[54],"trends":[55],"manufacturing":[57],"limits":[58],"strongly":[59],"imply":[60],"many-core":[62],"devices,":[63],"such":[64,78],"NVIDIA\u00ae":[66],"GPUs":[67,81,106,155,176],"the":[69,87,130,135,139,144,148],"Intel\u00ae":[70],"Xeon":[71],"Phi\u00ae,":[72],"will":[73],"become":[74],"central":[75],"components":[76],"systems.":[80],"are":[82],"well":[83],"known":[84],"deliver":[86,108],"highest":[88],"FLOPS/watt":[89],"enjoy":[91],"very":[93],"significant":[94],"advantage":[97],"over":[98],"CPU":[99],"architectures.":[100],"Recent":[101],"work":[102],"demonstrated":[104],"can":[107,171],"high":[109,145],"performance":[110],"and,":[115],"further,":[116],"it":[118],"possible":[120],"encapsulate":[122],"capability":[124],"in":[125],"manner":[127],"hides":[129],"low":[131],"level":[132],"details":[133],"GPU":[136],"architecture":[137],"CUDA":[140],"language":[141],"but":[142],"preserves":[143],"throughput":[146],"GPU.":[149],"We":[150],"extend":[151],"previous":[152],"research":[153],"scalable":[158],"processing":[160],"supercomputers":[162],"demonstrate":[164],"high-performance":[167],"machine":[170],"created":[173],"using":[174],"commodity":[175],"networking":[178],"hardware.":[179]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
