{"id":"https://openalex.org/W4410583284","doi":"https://doi.org/10.23919/date64628.2025.10993094","title":"LiGNN: Accelerating GNN Training Through Locality-Aware Dropout","display_name":"LiGNN: Accelerating GNN Training Through Locality-Aware Dropout","publication_year":2025,"publication_date":"2025-03-31","ids":{"openalex":"https://openalex.org/W4410583284","doi":"https://doi.org/10.23919/date64628.2025.10993094"},"language":"en","primary_location":{"id":"doi:10.23919/date64628.2025.10993094","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date64628.2025.10993094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Design, Automation &amp;amp; Test in Europe Conference (DATE)","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/A5010530857","display_name":"Gongjian Sun","orcid":"https://orcid.org/0000-0003-1447-2810"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gongjian Sun","raw_affiliation_strings":["Institute of Computing Technology, CAS,State Key Lab of Processors"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, CAS,State Key Lab of Processors","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004624509","display_name":"Mingyu Yan","orcid":"https://orcid.org/0000-0002-6915-955X"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyu Yan","raw_affiliation_strings":["Institute of Computing Technology, CAS,State Key Lab of Processors"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, CAS,State Key Lab of Processors","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070317336","display_name":"Dengke Han","orcid":"https://orcid.org/0000-0003-0641-5779"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dengke Han","raw_affiliation_strings":["Institute of Computing Technology, CAS,State Key Lab of Processors"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, CAS,State Key Lab of Processors","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050471084","display_name":"Runzhen Xue","orcid":"https://orcid.org/0000-0002-1956-1284"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runzhen Xue","raw_affiliation_strings":["Institute of Computing Technology, CAS,State Key Lab of Processors"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, CAS,State Key Lab of Processors","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023098180","display_name":"Xiaochun Ye","orcid":"https://orcid.org/0000-0003-4598-1685"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaochun Ye","raw_affiliation_strings":["Institute of Computing Technology, CAS,State Key Lab of Processors"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, CAS,State Key Lab of Processors","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011407484","display_name":"Dongrui Fan","orcid":"https://orcid.org/0000-0001-5219-0908"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongrui Fan","raw_affiliation_strings":["Institute of Computing Technology, CAS,State Key Lab of Processors"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, CAS,State Key Lab of Processors","institution_ids":["https://openalex.org/I4210090176"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5010530857"],"corresponding_institution_ids":["https://openalex.org/I4210090176"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14898889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13382","display_name":"Robotics and Automated Systems","score":0.9519000053405762,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13382","display_name":"Robotics and Automated Systems","score":0.9519000053405762,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9082000255584717,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.8780149221420288},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.7820663452148438},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6866413950920105},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6287035346031189},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36271125078201294},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18881529569625854},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05965155363082886}],"concepts":[{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.8780149221420288},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.7820663452148438},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6866413950920105},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6287035346031189},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36271125078201294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18881529569625854},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05965155363082886},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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:10.23919/date64628.2025.10993094","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date64628.2025.10993094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Design, Automation &amp;amp; Test in Europe Conference (DATE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1312224172","display_name":null,"funder_award_id":"62202451,6230247","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1702756715","display_name":null,"funder_award_id":"2022YFB4501400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322847","display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences","ror":"https://ror.org/031141b54"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2015140204","https://openalex.org/W2034861439","https://openalex.org/W2111406701","https://openalex.org/W2116341502","https://openalex.org/W2604314403","https://openalex.org/W2807021761","https://openalex.org/W2907492528","https://openalex.org/W2951351492","https://openalex.org/W2964094751","https://openalex.org/W3004208721","https://openalex.org/W3017228913","https://openalex.org/W3042770487","https://openalex.org/W3105753905","https://openalex.org/W3162147375","https://openalex.org/W4293246010","https://openalex.org/W4295934676","https://openalex.org/W4312076502","https://openalex.org/W4312265340","https://openalex.org/W4360831816","https://openalex.org/W4380875717","https://openalex.org/W4382239899","https://openalex.org/W4389495241","https://openalex.org/W4396506070","https://openalex.org/W4401862168","https://openalex.org/W4404132963","https://openalex.org/W4408017452","https://openalex.org/W6674330103","https://openalex.org/W6682824805","https://openalex.org/W6738964360","https://openalex.org/W6754929296","https://openalex.org/W6771932116"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3082178636","https://openalex.org/W2782041652","https://openalex.org/W2612657834","https://openalex.org/W2392157706","https://openalex.org/W2599192953","https://openalex.org/W1987310671","https://openalex.org/W2952088488"],"abstract_inverted_index":{"Graph":[0],"Neural":[1],"Networks":[2],"(GNNs)":[3],"have":[4,56],"demonstrated":[5],"significant":[6,44],"success":[7],"in":[8,31],"graph":[9],"learning":[10],"and":[11,34,60,91,110,141,150,162,186],"are":[12],"widely":[13],"adopted":[14],"across":[15],"various":[16],"critical":[17],"domains.":[18],"However,":[19],"the":[20,128,154],"irregular":[21,33,75,131],"connectivity":[22],"between":[23],"vertices":[24],"leads":[25],"to":[26,65,94,96,118,169],"inefficient":[27],"neighbor":[28],"aggregation,":[29],"resulting":[30],"substantial":[32],"coarse-grained":[35],"DRAM":[36,132,143,155,166,182,187],"accesses.":[37],"This":[38,157],"lack":[39],"of":[40,130],"data":[41,61,123,160],"locality":[42,90,124,161],"presents":[43],"challenges":[45],"for":[46],"execution":[47],"platforms,":[48],"ultimately":[49],"degrading":[50],"performance.":[51],"While":[52],"previous":[53],"accelerator":[54],"designs":[55],"leveraged":[57],"on-chip":[58],"memory":[59],"access":[62,72],"scheduling":[63],"strategies":[64],"address":[66],"this":[67,80],"issue,":[68],"they":[69],"still":[70],"inevitably":[71],"features":[73,121],"at":[74,153],"addresses":[76],"from":[77],"DRAM.":[78],"In":[79],"work,":[81],"we":[82],"propose":[83],"LiGNN,":[84],"a":[85,142,178],"hardware-based":[86],"solution":[87],"that":[88,104],"enhances":[89],"applies":[92],"dropout":[93,102,152],"aggregation":[95],"accelerate":[97],"GNN":[98],"training.":[99],"Unlike":[100],"algorithmic":[101],"approaches":[103],"primarily":[105],"focus":[106],"on":[107],"improving":[108],"accuracy":[109],"neglects":[111],"hardware":[112],"costs,":[113],"LiGNN":[114,137,176],"is":[115],"specifically":[116],"designed":[117],"drop":[119],"nodes'":[120],"with":[122],"awareness,":[125],"directly":[126],"targeting":[127],"reduction":[129],"accesses,":[133],"meanwhile":[134],"maintaining":[135],"accuracy.":[136,195],"introduces":[138],"locality-aware":[139],"ordering":[140],"row":[144,188],"integrity":[145],"policy,":[146],"enabling":[147],"configurable":[148],"burst":[149],"row-granularity":[151],"level.":[156],"approach":[158],"improves":[159],"ensures":[163],"more":[164],"efficient":[165],"access.":[167],"Compared":[168],"state-of-the-art":[170],"methods,":[171],"under":[172],"classic":[173],"0.5":[174],"droprate,":[175],"achieves":[177],"1.62~2.2\u00d7":[179],"speedup,":[180],"reduces":[181],"accesses":[183],"by":[184,190],"44~50%":[185],"activation":[189],"41~82%,":[191],"all":[192],"without":[193],"losing":[194]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
