{"id":"https://openalex.org/W2585968540","doi":"https://doi.org/10.1109/bigdata.2016.7840705","title":"Extreme scale breadth-first search on supercomputers","display_name":"Extreme scale breadth-first search on supercomputers","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2585968540","doi":"https://doi.org/10.1109/bigdata.2016.7840705","mag":"2585968540"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2016.7840705","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 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/A5109933181","display_name":"Koji Ueno","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Koji Ueno","raw_affiliation_strings":["Tokyo Institute of Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011886931","display_name":"Toyotaro Suzumura","orcid":"https://orcid.org/0000-0001-6412-8386"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Toyotaro Suzumura","raw_affiliation_strings":["IBM T.J. Watson Research Center New York, USA"],"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson Research Center New York, USA","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035025604","display_name":"Naoya Maruyama","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naoya Maruyama","raw_affiliation_strings":["RIKEN Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"RIKEN Kobe, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067662454","display_name":"Katsuki Fujisawa","orcid":"https://orcid.org/0000-0001-8549-641X"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Katsuki Fujisawa","raw_affiliation_strings":["Kyushu University Fukuoka, Japan"],"affiliations":[{"raw_affiliation_string":"Kyushu University Fukuoka, Japan","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103252086","display_name":"Satoshi Matsuoka","orcid":"https://orcid.org/0000-0003-2126-2926"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoshi Matsuoka","raw_affiliation_strings":["Tokyo Institute of Technology / AIST Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology / AIST Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5109933181"],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":1.6892,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.89887826,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1040","last_page":"1047"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9927999973297119,"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.7355266213417053},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5444726347923279},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.52553790807724},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.46427056193351746},{"id":"https://openalex.org/keywords/breadth-first-search","display_name":"Breadth-first search","score":0.4597902297973633},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.4155067205429077},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40626558661460876},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.356899619102478},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1760108768939972}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7355266213417053},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5444726347923279},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.52553790807724},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.46427056193351746},{"id":"https://openalex.org/C138843760","wikidata":"https://www.wikidata.org/wiki/Q325904","display_name":"Breadth-first search","level":2,"score":0.4597902297973633},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.4155067205429077},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40626558661460876},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.356899619102478},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1760108768939972},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata.2016.7840705","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:t2r2.star.titech.ac.jp:50704104","is_oa":false,"landing_page_url":"http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100919352","pdf_url":null,"source":{"id":"https://openalex.org/S4377196385","display_name":"Tokyo Tech Research Repository (Tokyo Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114531698","host_organization_name":"Tokyo Institute of Technology","host_organization_lineage":["https://openalex.org/I114531698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W312849892","https://openalex.org/W1562536132","https://openalex.org/W1992011279","https://openalex.org/W2005129866","https://openalex.org/W2006007301","https://openalex.org/W2013638793","https://openalex.org/W2018481625","https://openalex.org/W2071249960","https://openalex.org/W2081538566","https://openalex.org/W2093739557","https://openalex.org/W2129889687","https://openalex.org/W2130488390","https://openalex.org/W2134237243","https://openalex.org/W2141662114","https://openalex.org/W2154111453","https://openalex.org/W2949631483","https://openalex.org/W3145639177","https://openalex.org/W4230357857","https://openalex.org/W4231394584","https://openalex.org/W4253426709","https://openalex.org/W6610864286"],"related_works":["https://openalex.org/W141820298","https://openalex.org/W4378770497","https://openalex.org/W2049584446","https://openalex.org/W2079781215","https://openalex.org/W2064404759","https://openalex.org/W4308245303","https://openalex.org/W2014033564","https://openalex.org/W2910573937","https://openalex.org/W4385571583","https://openalex.org/W4389519396"],"abstract_inverted_index":{"Breadth-First":[0],"Search(BFS)":[1],"is":[2,119],"one":[3,29],"of":[4,14,47,84,91],"the":[5,42,45,51,60,76,113,127,131],"most":[6],"fundamental":[7],"graph":[8,16,32,97],"algorithms":[9],"used":[10],"as":[11,41,104],"a":[12,35,94],"component":[13],"many":[15],"algorithms.":[17],"Our":[18],"new":[19,95,117],"method":[20],"for":[21,28,86],"distributed":[22],"parallel":[23],"BFS":[24,27,118],"can":[25],"compute":[26],"trillion":[30],"vertices":[31],"within":[33],"half":[34],"second,":[36],"using":[37,58,130],"large":[38],"supercomputers":[39],"such":[40,103],"K-Computer.":[43],"By":[44],"use":[46],"our":[48,116],"proposed":[49],"algorithm,":[50],"K-Computer":[52],"was":[53],"ranked":[54],"1st":[55],"in":[56],"Graph500":[57],"all":[59],"82,944":[61],"nodes":[62,125],"available":[63],"on":[64,75,112,123],"June":[65,70],"and":[66,69,100,107],"November":[67],"2015":[68],"2016":[71],"38,621.4":[72],"GTEPS.":[73],"Based":[74],"hybrid-BFS":[77],"algorithm":[78],"by":[79],"Beamer[3],":[80],"we":[81],"devise":[82],"sets":[83],"optimizations":[85],"scaling":[87],"to":[88],"extreme":[89],"number":[90],"nodes,":[92],"including":[93],"efficient":[96],"data":[98],"structure":[99],"optimization":[101],"techniques":[102],"vertex":[105],"reordering":[106],"load":[108],"balancing.":[109],"Performance":[110],"evaluation":[111],"K":[114],"shows":[115],"3.19":[120],"times":[121],"faster":[122],"30,720":[124],"than":[126],"base":[128],"version":[129],"previously-known":[132],"best":[133],"techniques.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
