{"id":"https://openalex.org/W4287882780","doi":"https://doi.org/10.1109/isie51582.2022.9831549","title":"Reliability Assessment of Neural Networks in GPUs: A Framework For Permanent Faults Injections","display_name":"Reliability Assessment of Neural Networks in GPUs: A Framework For Permanent Faults Injections","publication_year":2022,"publication_date":"2022-06-01","ids":{"openalex":"https://openalex.org/W4287882780","doi":"https://doi.org/10.1109/isie51582.2022.9831549"},"language":"en","primary_location":{"id":"doi:10.1109/isie51582.2022.9831549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isie51582.2022.9831549","pdf_url":null,"source":{"id":"https://openalex.org/S4363605663","display_name":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","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/A5046650816","display_name":"Juan-David Guerrero-Balaguera","orcid":"https://orcid.org/0000-0001-6852-2372"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Juan-David Guerrero-Balaguera","raw_affiliation_strings":["Politecnico di Torino, Department of Control and Computer Engineering (DAUIN)"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Department of Control and Computer Engineering (DAUIN)","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014223408","display_name":"Luigi Galasso","orcid":null},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luigi Galasso","raw_affiliation_strings":["Politecnico di Torino, Department of Control and Computer Engineering (DAUIN)"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Department of Control and Computer Engineering (DAUIN)","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006252702","display_name":"Robert Limas Sierra","orcid":"https://orcid.org/0000-0001-5206-3757"},"institutions":[{"id":"https://openalex.org/I222202552","display_name":"Pedagogical and Technological University of Colombia","ror":"https://ror.org/04vdmbk59","country_code":"CO","type":"education","lineage":["https://openalex.org/I222202552"]}],"countries":["CO"],"is_corresponding":false,"raw_author_name":"Robert Limas Sierra","raw_affiliation_strings":["Universidad Pedagogica y Tecnologica de Colombia (UPTC), Electronics Engineering School"],"affiliations":[{"raw_affiliation_string":"Universidad Pedagogica y Tecnologica de Colombia (UPTC), Electronics Engineering School","institution_ids":["https://openalex.org/I222202552"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058555274","display_name":"M. Sonza Reorda","orcid":"https://orcid.org/0000-0003-2899-7669"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Matteo Sonza Reorda","raw_affiliation_strings":["Politecnico di Torino, Department of Control and Computer Engineering (DAUIN)"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Department of Control and Computer Engineering (DAUIN)","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5046650816"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":2.2556,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.88855412,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"959","last_page":"962"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11005","display_name":"Radiation Effects in Electronics","score":0.9991000294685364,"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":0.9991000294685364,"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/T10472","display_name":"Semiconductor materials and devices","score":0.9977999925613403,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9943000078201294,"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/fault-injection","display_name":"Fault injection","score":0.855437695980072},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7529635429382324},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.7329248189926147},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7234007120132446},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.5918557047843933},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5902287364006042},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.543216347694397},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.5110145807266235},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.510608971118927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4668126106262207},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.46662840247154236},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4568323791027069},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4224367141723633},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3664458096027374},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3428424596786499},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32262352108955383},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12907305359840393},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.1006990373134613}],"concepts":[{"id":"https://openalex.org/C2775928411","wikidata":"https://www.wikidata.org/wiki/Q2041312","display_name":"Fault injection","level":3,"score":0.855437695980072},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7529635429382324},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.7329248189926147},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7234007120132446},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.5918557047843933},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5902287364006042},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.543216347694397},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.5110145807266235},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.510608971118927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4668126106262207},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.46662840247154236},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4568323791027069},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4224367141723633},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3664458096027374},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3428424596786499},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32262352108955383},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12907305359840393},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.1006990373134613},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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:10.1109/isie51582.2022.9831549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isie51582.2022.9831549","pdf_url":null,"source":{"id":"https://openalex.org/S4363605663","display_name":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2735162286","https://openalex.org/W2748528844","https://openalex.org/W2800017313","https://openalex.org/W2801748224","https://openalex.org/W2896334750","https://openalex.org/W2907463061","https://openalex.org/W2909608027","https://openalex.org/W3002446690","https://openalex.org/W3023609977","https://openalex.org/W3106174138","https://openalex.org/W3110144974","https://openalex.org/W3128598968","https://openalex.org/W3175938008","https://openalex.org/W3187552919","https://openalex.org/W3194300811","https://openalex.org/W3203814528"],"related_works":["https://openalex.org/W4382644535","https://openalex.org/W2522768275","https://openalex.org/W2352938035","https://openalex.org/W2604133224","https://openalex.org/W2351672553","https://openalex.org/W2373392303","https://openalex.org/W2765894405","https://openalex.org/W1884735063","https://openalex.org/W2372668238","https://openalex.org/W2045155990"],"abstract_inverted_index":{"Currently,":[0],"Deep":[1],"learning":[2],"and":[3,29,134],"especially":[4],"Convolutional":[5],"Neural":[6],"Networks":[7],"(CNNs)":[8],"have":[9,69,90],"become":[10],"a":[11,17,110,114,152],"fundamental":[12],"computational":[13,38],"approach":[14],"applied":[15],"in":[16,78],"wide":[18],"range":[19],"of":[20,36,45,56,75,81,87,102,148,157],"domains,":[21],"including":[22],"some":[23],"safety-critical":[24],"applications":[25],"(e.g.,":[26],"automotive,":[27],"robotics,":[28],"healthcare":[30],"equipment).":[31],"Therefore,":[32],"the":[33,59,64,73,79,85,94,100,103,127,131,135,142,146,155],"reliability":[34,43,74,147],"evaluation":[35,44],"those":[37],"systems":[39],"is":[40,47],"mandatory.":[41],"The":[42],"CNNs":[46,149],"performed":[48],"by":[49],"fault":[50,120],"injection":[51,121],"campaigns":[52],"at":[53,93],"different":[54,124],"levels":[55],"abstraction,":[57],"from":[58],"application":[60,95],"level":[61],"down":[62],"to":[63,108,113,118],"hardware":[65],"level.":[66],"Many":[67],"works":[68],"focused":[70],"on":[71,151],"evaluating":[72],"neural":[76],"networks":[77],"presence":[80,156],"transient":[82],"faults.":[83,159],"However,":[84],"effects":[86],"permanent":[88,158],"faults":[89],"been":[91],"investigated":[92],"level,":[96],"only,":[97],"e.g.,":[98],"targeting":[99,123],"parameters":[101],"network.":[104],"This":[105,138],"paper":[106],"intends":[107],"propose":[109],"framework,":[111],"resorting":[112],"binary":[115],"instrumentation":[116],"tool":[117],"perform":[119],"campaigns,":[122],"components":[125],"inside":[126],"GPU,":[128],"such":[129],"as":[130],"register":[132],"files":[133],"functional":[136],"units.":[137],"environment":[139],"allows":[140],"for":[141],"first":[143],"time":[144],"assessing":[145],"deployed":[150],"GPU":[153],"considering":[154]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
