{"id":"https://openalex.org/W7154408020","doi":"https://doi.org/10.48550/arxiv.2604.10601","title":"gMatch: Fine-Grained and Hardware-Efficient Subgraph Matching on GPUs","display_name":"gMatch: Fine-Grained and Hardware-Efficient Subgraph Matching on GPUs","publication_year":2026,"publication_date":"2026-04-12","ids":{"openalex":"https://openalex.org/W7154408020","doi":"https://doi.org/10.48550/arxiv.2604.10601"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.10601","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10601","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.10601","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133600905","display_name":"Weitian Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Weitian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043164368","display_name":"Shixuan Sun","orcid":"https://orcid.org/0000-0003-4060-9438"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Shixuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133604101","display_name":"Cheng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122997986","display_name":"Yongmin Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Yongmin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123036469","display_name":"Yingqian Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Yingqian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133586786","display_name":"Minyi Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Minyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9596999883651733,"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":0.9596999883651733,"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/T11719","display_name":"Data Quality and Management","score":0.009999999776482582,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.007499999832361937,"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/scalability","display_name":"Scalability","score":0.670799970626831},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5920000076293945},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5126000046730042},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4431000053882599},{"id":"https://openalex.org/keywords/thread","display_name":"Thread (computing)","score":0.420199990272522},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.40799999237060547},{"id":"https://openalex.org/keywords/subgraph-isomorphism-problem","display_name":"Subgraph isomorphism problem","score":0.392300009727478},{"id":"https://openalex.org/keywords/load-balancing","display_name":"Load balancing (electrical power)","score":0.35499998927116394}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8579999804496765},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.671999990940094},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.670799970626831},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5920000076293945},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5126000046730042},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.45890000462532043},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4431000053882599},{"id":"https://openalex.org/C138101251","wikidata":"https://www.wikidata.org/wiki/Q213092","display_name":"Thread (computing)","level":2,"score":0.420199990272522},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.40799999237060547},{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.392300009727478},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36309999227523804},{"id":"https://openalex.org/C138959212","wikidata":"https://www.wikidata.org/wiki/Q1806783","display_name":"Load balancing (electrical power)","level":3,"score":0.35499998927116394},{"id":"https://openalex.org/C2989134064","wikidata":"https://www.wikidata.org/wiki/Q288510","display_name":"Execution time","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C78766204","wikidata":"https://www.wikidata.org/wiki/Q555032","display_name":"Multi-core processor","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C61455927","wikidata":"https://www.wikidata.org/wiki/Q1030529","display_name":"Blossom algorithm","level":3,"score":0.31139999628067017},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C36038622","wikidata":"https://www.wikidata.org/wiki/Q5428703","display_name":"Factor-critical graph","level":5,"score":0.30309998989105225},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C2777480716","wikidata":"https://www.wikidata.org/wiki/Q23582796","display_name":"Resource consumption","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C91481028","wikidata":"https://www.wikidata.org/wiki/Q1054686","display_name":"Distributed memory","level":3,"score":0.25839999318122864},{"id":"https://openalex.org/C128115575","wikidata":"https://www.wikidata.org/wiki/Q5597083","display_name":"Graph factorization","level":5,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.10601","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10601","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.10601","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10601","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.412906289100647}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Subgraph":[0],"matching":[1,26,61,111],"is":[2],"a":[3,10,33,58,67],"core":[4],"operation":[5],"in":[6,118],"graph":[7],"analytics,":[8],"supporting":[9],"broad":[11],"spectrum":[12],"of":[13],"applications":[14],"from":[15,39],"social":[16],"network":[17],"analysis":[18],"to":[19,45,92,149,161],"bioinformatics.":[20],"Recent":[21],"GPU-based":[22],"approaches":[23,157],"accelerate":[24],"subgraph":[25,60,110],"by":[27],"leveraging":[28],"parallelism":[29],"but":[30],"rely":[31],"on":[32,63,99,144],"coarse-grained":[34],"execution":[35,69,94],"model":[36,70],"that":[37,71,106],"suffers":[38],"scalability":[40],"and":[41,49,75,88,96,102,116,121,136,153],"efficiency":[42,95],"issues":[43],"due":[44],"high":[46],"memory":[47,73],"overhead":[48],"thread":[50],"underutilization.":[51],"In":[52],"this":[53],"paper,":[54],"we":[55],"propose":[56],"gMatch,":[57],"hardware-efficient":[59],"approach":[62],"GPUs.":[64],"gMatch":[65,107,147],"introduces":[66],"fine-grained":[68],"reduces":[72],"consumption":[74],"enables":[76],"flexible":[77],"task":[78],"scheduling":[79],"among":[80],"threads.":[81],"We":[82,123],"further":[83],"design":[84],"warp-level":[85],"batch":[86],"exploration":[87],"lightweight":[89],"load":[90],"balancing":[91],"improve":[93],"scalability.":[97,122],"Experiments":[98],"diverse":[100],"workloads":[101],"real-world":[103],"datasets":[104],"show":[105],"outperforms":[108],"state-of-the-art":[109,127],"methods,":[112],"including":[113],"STMatch,":[114],"T-DFS,":[115],"EGSM,":[117],"both":[119],"performance":[120,143],"also":[124],"compare":[125],"against":[126],"systems":[128,140],"for":[129],"mining":[130],"small":[131,145],"patterns,":[132],"such":[133],"as":[134],"BEEP":[135],"G$^2$Miner.":[137],"While":[138],"these":[139],"achieve":[141],"better":[142],"datasets,":[146,154],"scales":[148],"substantially":[150],"larger":[151],"queries":[152],"where":[155],"existing":[156],"degrade":[158],"or":[159],"fail":[160],"complete.":[162]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-15T00:00:00"}