{"id":"https://openalex.org/W2042545849","doi":"https://doi.org/10.1145/2807591.2807594","title":"Enterprise","display_name":"Enterprise","publication_year":2015,"publication_date":"2015-10-27","ids":{"openalex":"https://openalex.org/W2042545849","doi":"https://doi.org/10.1145/2807591.2807594","mag":"2042545849"},"language":"en","primary_location":{"id":"doi:10.1145/2807591.2807594","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2807591.2807594","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2807594&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://dl.acm.org/ft_gateway.cfm?id=2807594&type=pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119011911","display_name":"Hang Liu","orcid":"https://orcid.org/0009-0001-2928-1040"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hang Liu","raw_affiliation_strings":["George Washington University","george Washington University"],"affiliations":[{"raw_affiliation_string":"George Washington University","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"george Washington University","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002254350","display_name":"H. Howie Huang","orcid":"https://orcid.org/0000-0001-8588-7680"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H. Howie Huang","raw_affiliation_strings":["George Washington University","george Washington University"],"affiliations":[{"raw_affiliation_string":"George Washington University","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"george Washington University","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5119011911"],"corresponding_institution_ids":["https://openalex.org/I193531525"],"apc_list":null,"apc_paid":null,"fwci":7.4878,"has_fulltext":false,"cited_by_count":158,"citation_normalized_percentile":{"value":0.98143223,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"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/T11478","display_name":"Caching and Content Delivery","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.9973000288009644,"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":0.8770004510879517},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.7222554087638855},{"id":"https://openalex.org/keywords/graphics-processing-unit","display_name":"Graphics processing unit","score":0.4860697090625763},{"id":"https://openalex.org/keywords/thread","display_name":"Thread (computing)","score":0.4472092092037201},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.4343249201774597},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.423290878534317},{"id":"https://openalex.org/keywords/general-purpose-computing-on-graphics-processing-units","display_name":"General-purpose computing on graphics processing units","score":0.41415658593177795},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.3334025740623474},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.16164809465408325}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8770004510879517},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.7222554087638855},{"id":"https://openalex.org/C2779851693","wikidata":"https://www.wikidata.org/wiki/Q183484","display_name":"Graphics processing unit","level":2,"score":0.4860697090625763},{"id":"https://openalex.org/C138101251","wikidata":"https://www.wikidata.org/wiki/Q213092","display_name":"Thread (computing)","level":2,"score":0.4472092092037201},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.4343249201774597},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.423290878534317},{"id":"https://openalex.org/C50630238","wikidata":"https://www.wikidata.org/wiki/Q971505","display_name":"General-purpose computing on graphics processing units","level":3,"score":0.41415658593177795},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.3334025740623474},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.16164809465408325},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2807591.2807594","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2807591.2807594","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2807594&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/2807591.2807594","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2807591.2807594","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2807594&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8600000143051147,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1289958494","display_name":"CDI Type-II: Collaborative Research: From Ion Channels to Blood Flow and Heart Sounds: A New Paradigm in Cyber-Enabled Multiphysical Analysis of Heart Function","funder_award_id":"1124813","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G446689757","display_name":null,"funder_award_id":"Academic Partnership Award","funder_id":"https://openalex.org/F4320309480","funder_display_name":"Nvidia"},{"id":"https://openalex.org/G602702742","display_name":null,"funder_award_id":"1350766","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6671297155","display_name":null,"funder_award_id":"CAREER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6896774754","display_name":null,"funder_award_id":"CNS-1350766,IOS-1124813","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7184870667","display_name":null,"funder_award_id":"IOS-1124813","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2042545849.pdf","grobid_xml":"https://content.openalex.org/works/W2042545849.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W19838944","https://openalex.org/W78077100","https://openalex.org/W1482680420","https://openalex.org/W1504291959","https://openalex.org/W1512819151","https://openalex.org/W1643412971","https://openalex.org/W1972090741","https://openalex.org/W1979270822","https://openalex.org/W1985291160","https://openalex.org/W1987396134","https://openalex.org/W1997310799","https://openalex.org/W2016706026","https://openalex.org/W2041470524","https://openalex.org/W2047576351","https://openalex.org/W2055497547","https://openalex.org/W2063656563","https://openalex.org/W2093053744","https://openalex.org/W2094722168","https://openalex.org/W2101196063","https://openalex.org/W2107251158","https://openalex.org/W2109473404","https://openalex.org/W2114616878","https://openalex.org/W2118893477","https://openalex.org/W2123538390","https://openalex.org/W2136944230","https://openalex.org/W2143114052","https://openalex.org/W2144085134","https://openalex.org/W2144885342","https://openalex.org/W2146381930","https://openalex.org/W2147256592","https://openalex.org/W2147393894","https://openalex.org/W2161061943","https://openalex.org/W2164516366","https://openalex.org/W2167383108","https://openalex.org/W2555756770","https://openalex.org/W2625099696","https://openalex.org/W2739266613","https://openalex.org/W2769133055","https://openalex.org/W2994762488","https://openalex.org/W3103786587","https://openalex.org/W3142588439","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2151046618","https://openalex.org/W1972148443","https://openalex.org/W1969233021","https://openalex.org/W2167646277","https://openalex.org/W2063573318","https://openalex.org/W2388314963","https://openalex.org/W3158047141","https://openalex.org/W1656096860","https://openalex.org/W2027443981","https://openalex.org/W151175334"],"abstract_inverted_index":{"The":[0],"Breadth-First":[1],"Search":[2],"(BFS)":[3],"algorithm":[4],"serves":[5],"as":[6,213],"the":[7,100,108,128,146,202,217],"foundation":[8],"for":[9,88],"many":[10],"graph-processing":[11],"applications":[12],"and":[13,39,86,91,120,135,188],"analytics":[14],"workloads.":[15],"While":[16],"Graphics":[17],"Processing":[18],"Unit":[19],"(GPU)":[20],"offers":[21],"massive":[22],"parallelism,":[23],"achieving":[24],"high-performance":[25],"BFS":[26,55,124],"on":[27,103,133,161,182,194,205],"GPUs":[28,196],"entails":[29],"efficient":[30],"scheduling":[31,70],"of":[32,36,42,111,130,141,165],"a":[33,52,73,138,162,183],"large":[34,163],"number":[35],"GPU":[37,43,68,95,112,122,148,169],"threads":[38,69],"effective":[40],"utilization":[41],"memory":[44,150],"hierarchy.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49],"present":[50],"Enterprise,":[51],"new":[53],"GPU-based":[54],"system":[56],"that":[57,98,197],"combines":[58],"three":[59],"techniques":[60],"to":[61,106,151,174,190],"remove":[62],"potential":[63],"performance":[64],"bottlenecks:":[65],"(1)":[66],"streamlined":[67],"through":[71],"constructing":[72],"frontier":[74],"queue":[75],"without":[76],"contention":[77],"from":[78],"concurrent":[79],"threads,":[80],"yet":[81],"containing":[82],"no":[83],"duplicated":[84],"frontiers":[85,101],"optimized":[87],"both":[89],"top-down":[90],"bottom-up":[92],"BFS.":[93],"(2)":[94],"workload":[96],"balancing":[97],"classifies":[99],"based":[102,123],"different":[104,168],"out-degrees":[105],"utilize":[107],"full":[109],"spectrum":[110],"parallel":[113],"granularity,":[114],"which":[115],"significantly":[116],"increases":[117],"thread-level":[118],"parallelism;":[119],"(3)":[121],"direction":[125],"optimization":[126],"quantifies":[127],"effect":[129],"hub":[131,143],"vertices":[132,144],"direction-switching":[134],"selectively":[136],"caches":[137],"small":[139],"set":[140],"critical":[142],"in":[145,201,216],"limited":[147],"shared":[149],"reduce":[152],"expensive":[153],"random":[154],"data":[155,221],"accesses.":[156],"We":[157],"have":[158],"evaluated":[159],"Enterprise":[160,171,208],"variety":[164],"graphs":[166],"with":[167],"devices.":[170],"achieves":[172],"up":[173,189],"76":[175],"billion":[176,192],"traversed":[177],"edges":[178],"per":[179,227],"second":[180],"(TEPS)":[181],"single":[184],"NVIDIA":[185],"Kepler":[186],"K40,":[187],"122":[191],"TEPS":[193,226],"two":[195],"ranks":[198],"No.":[199,214],"45":[200],"Graph":[203],"500":[204,219],"November":[206],"2014.":[207],"is":[209],"also":[210],"very":[211],"energy-efficient":[212],"1":[215],"GreenGraph":[218],"(small":[220],"category),":[222],"delivering":[223],"446":[224],"million":[225],"watt.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":25},{"year":2019,"cited_by_count":19},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":18},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2016-06-24T00:00:00"}
