{"id":"https://openalex.org/W3205165858","doi":"https://doi.org/10.1109/tcad.2022.3166108","title":"Functional Criticality Analysis of Structural Faults in AI Accelerators","display_name":"Functional Criticality Analysis of Structural Faults in AI Accelerators","publication_year":2022,"publication_date":"2022-04-08","ids":{"openalex":"https://openalex.org/W3205165858","doi":"https://doi.org/10.1109/tcad.2022.3166108","mag":"3205165858"},"language":"en","primary_location":{"id":"doi:10.1109/tcad.2022.3166108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcad.2022.3166108","pdf_url":null,"source":{"id":"https://openalex.org/S100835903","display_name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","issn_l":"0278-0070","issn":["0278-0070","1937-4151"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and 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/A5090354528","display_name":"Arjun Chaudhuri","orcid":"https://orcid.org/0000-0001-9353-6397"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arjun Chaudhuri","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA"],"raw_orcid":"https://orcid.org/0000-0001-9353-6397","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017274857","display_name":"Jonti Talukdar","orcid":"https://orcid.org/0000-0001-7079-5281"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonti Talukdar","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101754630","display_name":"Fei Su","orcid":"https://orcid.org/0000-0002-3536-8126"},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fei Su","raw_affiliation_strings":["Design Engineering Group, Intel Corporation, Folsom, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Design Engineering Group, Intel Corporation, Folsom, CA, USA","institution_ids":["https://openalex.org/I1343180700"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033880864","display_name":"Krishnendu Chakrabarty","orcid":"https://orcid.org/0000-0003-4475-6435"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Krishnendu Chakrabarty","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA"],"raw_orcid":"https://orcid.org/0000-0003-4475-6435","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2369,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.77447492,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"41","issue":"12","first_page":"5657","last_page":"5670"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11005","display_name":"Radiation Effects in Electronics","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11005","display_name":"Radiation Effects in Electronics","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9923999905586243,"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/criticality","display_name":"Criticality","score":0.8353760242462158},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7768217325210571},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6008234620094299},{"id":"https://openalex.org/keywords/failure-mode-effects-and-criticality-analysis","display_name":"Failure mode, effects, and criticality analysis","score":0.5742993950843811},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5464240312576294},{"id":"https://openalex.org/keywords/netlist","display_name":"Netlist","score":0.5347031354904175},{"id":"https://openalex.org/keywords/systolic-array","display_name":"Systolic array","score":0.512505054473877},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4672427475452423},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.4375777542591095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39551055431365967},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3697679042816162},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.25413787364959717},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10465940833091736},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08877506852149963}],"concepts":[{"id":"https://openalex.org/C125611927","wikidata":"https://www.wikidata.org/wiki/Q17008131","display_name":"Criticality","level":2,"score":0.8353760242462158},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7768217325210571},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6008234620094299},{"id":"https://openalex.org/C30098461","wikidata":"https://www.wikidata.org/wiki/Q909342","display_name":"Failure mode, effects, and criticality analysis","level":3,"score":0.5742993950843811},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5464240312576294},{"id":"https://openalex.org/C177650935","wikidata":"https://www.wikidata.org/wiki/Q1760303","display_name":"Netlist","level":2,"score":0.5347031354904175},{"id":"https://openalex.org/C150741067","wikidata":"https://www.wikidata.org/wiki/Q2377218","display_name":"Systolic array","level":3,"score":0.512505054473877},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4672427475452423},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.4375777542591095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39551055431365967},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3697679042816162},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.25413787364959717},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10465940833091736},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08877506852149963},{"id":"https://openalex.org/C185544564","wikidata":"https://www.wikidata.org/wiki/Q81197","display_name":"Nuclear physics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C14580979","wikidata":"https://www.wikidata.org/wiki/Q876049","display_name":"Very-large-scale integration","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcad.2022.3166108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcad.2022.3166108","pdf_url":null,"source":{"id":"https://openalex.org/S100835903","display_name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","issn_l":"0278-0070","issn":["0278-0070","1937-4151"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W86317129","https://openalex.org/W613690151","https://openalex.org/W2039824819","https://openalex.org/W2099471712","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2137061486","https://openalex.org/W2139923370","https://openalex.org/W2173520492","https://openalex.org/W2289252105","https://openalex.org/W2294567968","https://openalex.org/W2498672755","https://openalex.org/W2506467271","https://openalex.org/W2604319603","https://openalex.org/W2606722458","https://openalex.org/W2612076670","https://openalex.org/W2758375579","https://openalex.org/W2767260595","https://openalex.org/W2801748224","https://openalex.org/W2809188712","https://openalex.org/W2911491685","https://openalex.org/W2944349874","https://openalex.org/W2954535151","https://openalex.org/W2963037989","https://openalex.org/W2963153810","https://openalex.org/W2963684088","https://openalex.org/W2963703197","https://openalex.org/W2964108906","https://openalex.org/W2990200213","https://openalex.org/W2999414607","https://openalex.org/W3006692106","https://openalex.org/W3007788310","https://openalex.org/W3008838787","https://openalex.org/W3193311994","https://openalex.org/W3205165858","https://openalex.org/W4320013936","https://openalex.org/W6639379271","https://openalex.org/W6685352114","https://openalex.org/W6696879442","https://openalex.org/W6751037545","https://openalex.org/W6758823024","https://openalex.org/W6800333540","https://openalex.org/W6802408539"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2361355225","https://openalex.org/W2030439800","https://openalex.org/W1582034041","https://openalex.org/W2094868523","https://openalex.org/W2352957805","https://openalex.org/W125625301","https://openalex.org/W2384212105","https://openalex.org/W1979768108","https://openalex.org/W4239638359"],"abstract_inverted_index":{"The":[0],"ubiquitous":[1],"application":[2],"of":[3,35,49,72,102,123,134,157,169,193],"deep":[4],"neural":[5],"networks":[6,176],"(DNNs)":[7],"has":[8],"led":[9],"to":[10,94,152,183],"a":[11,29,73,108,115,127,146,161],"rise":[12],"in":[13,53,67,107,126,160],"demand":[14],"for":[15,38,78,119],"artificial":[16],"intelligence":[17],"(AI)":[18],"accelerators.":[19,43],"For":[20],"example,":[21],"the":[22,47,68,79,95,103,121,132,154,167],"tensor":[23],"processing":[24,69],"unit":[25],"from":[26],"Google\u2013based":[27],"on":[28,58,139],"systolic":[30,74],"array\u2013and":[31],"its":[32],"variants":[33],"are":[34,110],"considerable":[36],"interest":[37],"DNN":[39],"inferencing":[40],"using":[41],"AI":[42],"This":[44],"article":[45],"studies":[46],"problem":[48,168],"classifying":[50],"structural":[51,105,194],"faults":[52,66,106,125,159],"such":[54],"an":[55],"accelerator":[56],"based":[57,138],"their":[59],"functional":[60,155,190],"criticality.":[61],"We":[62,113,143,165],"first":[63],"analyze":[64,131],"pin-level":[65,104],"elements":[70],"(PEs)":[71],"array.":[75],"Simulation":[76],"results":[77],"LeNet":[80],"network":[81],"with":[82],"8-bit":[83],"fixed-point,":[84],"16-bit":[85],"floating-point":[86],"(FP),":[87],"and":[88,130],"32-bit":[89],"FP":[90],"data":[91],"paths":[92],"applied":[93],"MNIST":[96],"dataset":[97],"show":[98],"that":[99],"over":[100],"93%":[101],"PE":[109,128],"functionally":[111],"benign.":[112],"present":[114,145],"greedy":[116],"iterative":[117],"framework":[118],"determining":[120],"criticality":[122,135,156,180,191],"stuck-at":[124,158],"netlist":[129],"limitations":[133],"analysis":[136],"methods":[137],"repeated":[140],"fault":[141],"simulations.":[142],"next":[144],"scalable":[147],"two-tier":[148],"machine-learning":[149],"(ML)-based":[150],"method":[151],"assess":[153],"computationally":[162],"efficient":[163],"manner.":[164],"address":[166],"minimizing":[170],"misclassification":[171],"by":[172],"utilizing":[173],"generative":[174],"adversarial":[175],"(GANs).":[177],"Two-tier":[178],"ML/GAN-based":[179],"assessment":[181],"leads":[182],"less":[184],"than":[185],"1%":[186],"test":[187],"escapes":[188],"during":[189],"evaluation":[192],"faults.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
