{"id":"https://openalex.org/W4412855194","doi":"https://doi.org/10.1145/3758094","title":"FORT-GCN: A <u>F</u> ault-T <u>o</u> le <u>r</u> ant and Adap <u>t</u> ive Accelerator Design for Efficient Graph Convolutional Network Inference","display_name":"FORT-GCN: A <u>F</u> ault-T <u>o</u> le <u>r</u> ant and Adap <u>t</u> ive Accelerator Design for Efficient Graph Convolutional Network Inference","publication_year":2025,"publication_date":"2025-08-02","ids":{"openalex":"https://openalex.org/W4412855194","doi":"https://doi.org/10.1145/3758094"},"language":"en","primary_location":{"id":"doi:10.1145/3758094","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3758094","pdf_url":null,"source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-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/A5025289290","display_name":"Ke Wang","orcid":"https://orcid.org/0000-0001-7189-9293"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ke Wang","raw_affiliation_strings":["Electrical and Computer Engineering, The University of North Carolina at Charlotte","Electrical and Computer Engineering, The University of North Carolina at Charlotte, Charlotte, United States"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, The University of North Carolina at Charlotte","institution_ids":["https://openalex.org/I102149020"]},{"raw_affiliation_string":"Electrical and Computer Engineering, The University of North Carolina at Charlotte, Charlotte, United States","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081760516","display_name":"Yingnan Zhao","orcid":"https://orcid.org/0009-0005-5776-6239"},"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":"Yingnan Zhao","raw_affiliation_strings":["Electrical and Computer Engineering, The George Washington University","Electrical and Computer Engineering, The George Washington University, Washington, United States"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, The George Washington University","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"Electrical and Computer Engineering, The George Washington University, Washington, United States","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034189643","display_name":"Ahmed Louri","orcid":"https://orcid.org/0000-0003-4262-6688"},"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":"Ahmed Louri","raw_affiliation_strings":["Electrical and Computer Engineering, The George Washington University","Electrical and Computer Engineering, The George Washington University, Washington, United States"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, The George Washington University","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"Electrical and Computer Engineering, The George Washington University, Washington, United States","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025289290"],"corresponding_institution_ids":["https://openalex.org/I102149020"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1044035,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"24","issue":"5s","first_page":"1","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9997000098228455,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9900000095367432,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7152954339981079},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6096063256263733},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5479181408882141},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29057493805885315},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2774871289730072}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7152954339981079},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6096063256263733},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5479181408882141},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29057493805885315},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2774871289730072}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3758094","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3758094","pdf_url":null,"source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1891950198","https://openalex.org/W1965729545","https://openalex.org/W2004016834","https://openalex.org/W2037547340","https://openalex.org/W2045554437","https://openalex.org/W2100956485","https://openalex.org/W2101930816","https://openalex.org/W2109678242","https://openalex.org/W2129960401","https://openalex.org/W2130189691","https://openalex.org/W2149637086","https://openalex.org/W2150283124","https://openalex.org/W2346811907","https://openalex.org/W2513554817","https://openalex.org/W2529635959","https://openalex.org/W2613252096","https://openalex.org/W2748528844","https://openalex.org/W2807021761","https://openalex.org/W2901504064","https://openalex.org/W2944349874","https://openalex.org/W2949208225","https://openalex.org/W2963396341","https://openalex.org/W2968554659","https://openalex.org/W2971653768","https://openalex.org/W2980367488","https://openalex.org/W2997019200","https://openalex.org/W3017228913","https://openalex.org/W3021294679","https://openalex.org/W3031469573","https://openalex.org/W3036561617","https://openalex.org/W3048221011","https://openalex.org/W3094588037","https://openalex.org/W3100848837","https://openalex.org/W3105753905","https://openalex.org/W3106867121","https://openalex.org/W3139765438","https://openalex.org/W3152663991","https://openalex.org/W3157609068","https://openalex.org/W3179429918","https://openalex.org/W3192157621","https://openalex.org/W3206743063","https://openalex.org/W4205993941","https://openalex.org/W4210607614","https://openalex.org/W4220689021","https://openalex.org/W4226137788","https://openalex.org/W4229487452","https://openalex.org/W4254300870","https://openalex.org/W4312312641","https://openalex.org/W4360831816","https://openalex.org/W4366275315","https://openalex.org/W4380520401","https://openalex.org/W4380881139","https://openalex.org/W4396941334","https://openalex.org/W4410949647"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Hardware":[0],"reliability":[1,52],"has":[2,42],"emerged":[3],"as":[4,12,37],"a":[5,92,112,135],"paramount":[6],"concern":[7],"for":[8,97],"machine":[9,34],"learning":[10],"accelerators,":[11],"transient":[13,124],"errors":[14],"and":[15,26,60,72,80,121,134,150,165,172],"permanent":[16,108],"failures":[17],"occurring":[18],"during":[19],"inference":[20],"can":[21],"severely":[22],"compromise":[23],"accuracy,":[24],"performance,":[25],"service":[27],"availability.":[28],"Although":[29],"fault":[30,65,99,109,143,159],"resilience":[31,126],"in":[32,158],"traditional":[33],"learning,":[35],"such":[36],"Deep":[38],"Neural":[39],"Networks":[40],"(DNNs),":[41],"been":[43],"extensively":[44],"studied,":[45],"graph":[46,151],"convolutional":[47],"networks":[48],"(GCNs)":[49],"present":[50],"unique":[51],"challenges":[53],"due":[54],"to":[55,85,162],"their":[56],"irregular":[57],"computation":[58],"patterns":[59],"dynamic":[61],"data":[62],"dependencies.":[63],"Traditional":[64],"mitigation":[66],"approaches,":[67,167],"including":[68],"hardware":[69,94],"redundancy,":[70],"recomputation,":[71],"Hamming":[73],"code":[74],"protection,":[75],"suffer":[76],"from":[77],"prohibitive":[78],"latency":[79],"power":[81,173],"overheads":[82],"when":[83],"applied":[84],"GCN":[86],"accelerators.":[87],"This":[88],"article":[89],"presents":[90],"FORT-GCN,":[91],"holistic":[93],"architecture":[95],"co-optimized":[96],"GCN-specific":[98],"resilience.":[100],"Our":[101],"solution":[102],"integrates":[103],"three":[104],"key":[105],"innovations,":[106],"namely":[107],"tolerance":[110],"through":[111],"novel":[113],"robust":[114],"processing":[115],"element":[116],"design":[117,139],"with":[118,168],"runtime":[119],"reconfiguration":[120],"defect-adaptive":[122],"interconnects,":[123],"error":[125,130],"via":[127],"lightweight":[128],"selective":[129],"correction":[131],"unit":[132],"design,":[133],"fault-aware":[136],"adaptive":[137],"controller":[138],"that":[140],"dynamically":[141],"adjusts":[142],"protection":[144],"strategies":[145],"based":[146],"on":[147],"operational":[148],"faults":[149],"characteristics.":[152],"Experimental":[153],"evaluation":[154],"demonstrates":[155],"35.4%":[156],"improvement":[157],"robustness":[160],"compared":[161],"conventional":[163],"error-correction":[164],"redundancy-based":[166],"minimal":[169],"timing,":[170],"area,":[171],"overheads.":[174]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-08-02T00:00:00"}
