{"id":"https://openalex.org/W2584035248","doi":"https://doi.org/10.1109/bigdata.2016.7840780","title":"An edge-set based large scale graph processing system","display_name":"An edge-set based large scale graph processing system","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2584035248","doi":"https://doi.org/10.1109/bigdata.2016.7840780","mag":"2584035248"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2016.7840780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840780","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":"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/A5100452292","display_name":"L. P. Zhou","orcid":"https://orcid.org/0000-0001-6989-8080"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li Zhou","raw_affiliation_strings":["The Ohio State University Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State University Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103733183","display_name":"Yinglong Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yinglong Xia","raw_affiliation_strings":["Huawei Research America, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Research America, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210146936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109002279","display_name":"Hui Zang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Zang","raw_affiliation_strings":["Huawei Research America, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Research America, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210146936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112423612","display_name":"Jian Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Xu","raw_affiliation_strings":["Huawei Technologies, Ltd, Shenzhen, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies, Ltd, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044814594","display_name":"Mingzhen Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingzhen Xia","raw_affiliation_strings":["Huawei Technologies, Ltd, Shenzhen, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies, Ltd, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":null,"first_page":"1664","last_page":"1669"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":1.0,"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":1.0,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.9977999925613403,"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":0.9973999857902527,"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":0.7399905323982239},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.5852881669998169},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5245930552482605},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4920167624950409},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.47064918279647827},{"id":"https://openalex.org/keywords/instruction-prefetch","display_name":"Instruction prefetch","score":0.46144595742225647},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.23693841695785522},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13660073280334473}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7399905323982239},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.5852881669998169},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5245930552482605},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4920167624950409},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.47064918279647827},{"id":"https://openalex.org/C133588205","wikidata":"https://www.wikidata.org/wiki/Q28455645","display_name":"Instruction prefetch","level":3,"score":0.46144595742225647},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.23693841695785522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13660073280334473},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2016.7840780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840780","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"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5799999833106995,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1788180225","https://openalex.org/W2053076698","https://openalex.org/W2196885578","https://openalex.org/W2218562164","https://openalex.org/W2297018065","https://openalex.org/W2469279958","https://openalex.org/W2512825584","https://openalex.org/W6638233953"],"related_works":["https://openalex.org/W2140324148","https://openalex.org/W2121199344","https://openalex.org/W2285914869","https://openalex.org/W3117515082","https://openalex.org/W2113441357","https://openalex.org/W3022537591","https://openalex.org/W2126134823","https://openalex.org/W2336226224","https://openalex.org/W1974128693","https://openalex.org/W126407280"],"abstract_inverted_index":{"Next":[0],"generation":[1],"analytics":[2],"will":[3],"be":[4,90,127],"all":[5],"about":[6],"graphs,":[7,63],"though":[8],"performance":[9,40,168],"has":[10],"been":[11],"a":[12,49,52,75,130,179],"fundamental":[13],"challenge":[14],"for":[15,30,62,68,82,93,95,149],"large":[16,33,69,105],"scale":[17,34,70,106],"graph":[18,27,50,97,107,166],"processing.":[19,71],"In":[20],"this":[21,109],"paper,":[22],"we":[23],"present":[24],"an":[25],"industrial":[26],"processing":[28,167],"engine":[29,47,110],"exploring":[31],"various":[32],"linked":[35],"data,":[36],"which":[37],"exhibits":[38],"superior":[39],"due":[41],"to":[42,101,134,142,157,170],"the":[43,58,78,85,102,115,120,136,145,150,164,189,193],"several":[44],"innovations.":[45],"This":[46],"organizes":[48],"as":[51],"set":[53,181],"of":[54,77,104,182],"edge-sets,":[55],"compatible":[56],"with":[57],"traditional":[59],"edge-centric":[60],"sharding":[61],"but":[64],"becomes":[65],"more":[66],"amenable":[67],"Each":[72],"time":[73],"only":[74],"portion":[76],"sets":[79],"are":[80],"needed":[81],"computation":[83],"and":[84],"data":[86,137,146,172],"access":[87,173],"patterns":[88],"can":[89,126,153],"highly":[91],"predictable":[92],"prefetch":[94],"many":[96],"computing":[98],"algorithms.":[99],"Due":[100],"sparsity":[103],"structure,":[108],"differentiates":[111],"logical":[112,124],"edge-sets":[113,116,125,152],"from":[114,155],"physically":[117],"stored":[118],"on":[119,178,185],"disk,":[121],"where":[122,188],"multiple":[123,186],"organized":[128],"into":[129],"same":[131],"physical":[132,151],"edge-set":[133,161],"increase":[135],"locality.":[138],"Besides,":[139],"in":[140],"contrast":[141],"existing":[143],"solution,":[144],"structures":[147],"utilized":[148],"vary":[154],"one":[156],"another.":[158],"Such":[159],"heterogeneous":[160],"representation":[162],"explores":[163],"best":[165],"according":[169],"local":[171],"patterns.":[174],"We":[175],"conduct":[176],"experiments":[177],"representative":[180],"property":[183],"graphs":[184],"platforms,":[187],"proposed":[190],"system":[191],"outperform":[192],"baseline":[194],"systems":[195],"consistently.":[196]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
