{"id":"https://openalex.org/W4399144004","doi":"https://doi.org/10.1109/vts60656.2024.10538531","title":"Drop-Connect as a Fault-Tolerance Approach for RRAM-based Deep Neural Network Accelerators","display_name":"Drop-Connect as a Fault-Tolerance Approach for RRAM-based Deep Neural Network Accelerators","publication_year":2024,"publication_date":"2024-04-22","ids":{"openalex":"https://openalex.org/W4399144004","doi":"https://doi.org/10.1109/vts60656.2024.10538531"},"language":"en","primary_location":{"id":"doi:10.1109/vts60656.2024.10538531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts60656.2024.10538531","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 42nd VLSI Test Symposium (VTS)","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/A5100556351","display_name":"Mingyuan Xiang","orcid":null},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mingyuan Xiang","raw_affiliation_strings":["University of Chicago,Department of Computer Science,Chicago,IL,USA,60637"],"affiliations":[{"raw_affiliation_string":"University of Chicago,Department of Computer Science,Chicago,IL,USA,60637","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104288047","display_name":"Xuhan Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuhan Xie","raw_affiliation_strings":["University of Chicago,Department of Computer Science,Chicago,IL,USA,60637"],"affiliations":[{"raw_affiliation_string":"University of Chicago,Department of Computer Science,Chicago,IL,USA,60637","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085741578","display_name":"Pedro Savarese","orcid":null},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pedro Savarese","raw_affiliation_strings":["Toyota Technological Institute at Chicago,Chicago,IL,USA,60637"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute at Chicago,Chicago,IL,USA,60637","institution_ids":["https://openalex.org/I160992636"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015431603","display_name":"Xin Yuan","orcid":"https://orcid.org/0000-0002-8311-7524"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Yuan","raw_affiliation_strings":["University of Chicago,Department of Computer Science,Chicago,IL,USA,60637"],"affiliations":[{"raw_affiliation_string":"University of Chicago,Department of Computer Science,Chicago,IL,USA,60637","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001371942","display_name":"Michael Maire","orcid":"https://orcid.org/0000-0002-9778-6673"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Maire","raw_affiliation_strings":["University of Chicago,Department of Computer Science,Chicago,IL,USA,60637"],"affiliations":[{"raw_affiliation_string":"University of Chicago,Department of Computer Science,Chicago,IL,USA,60637","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101989053","display_name":"Yanjing Li","orcid":"https://orcid.org/0000-0003-0124-0463"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanjing Li","raw_affiliation_strings":["University of Chicago,Department of Computer Science,Chicago,IL,USA,60637"],"affiliations":[{"raw_affiliation_string":"University of Chicago,Department of Computer Science,Chicago,IL,USA,60637","institution_ids":["https://openalex.org/I40347166"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100556351"],"corresponding_institution_ids":["https://openalex.org/I40347166"],"apc_list":null,"apc_paid":null,"fwci":1.3841,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80586898,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"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/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9997000098228455,"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":0.9937999844551086,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/resistive-random-access-memory","display_name":"Resistive random-access memory","score":0.9413691759109497},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.655838131904602},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6408505439758301},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5375456809997559},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5127835869789124},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4530212879180908},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4385078549385071},{"id":"https://openalex.org/keywords/fault-tolerance","display_name":"Fault tolerance","score":0.4172786772251129},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41445210576057434},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3928166925907135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3391779661178589},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.19377672672271729},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1762934923171997},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.1673523187637329},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.1314581036567688},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.07930904626846313}],"concepts":[{"id":"https://openalex.org/C182019814","wikidata":"https://www.wikidata.org/wiki/Q1143830","display_name":"Resistive random-access memory","level":3,"score":0.9413691759109497},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.655838131904602},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6408505439758301},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5375456809997559},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5127835869789124},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4530212879180908},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4385078549385071},{"id":"https://openalex.org/C63540848","wikidata":"https://www.wikidata.org/wiki/Q3140932","display_name":"Fault tolerance","level":2,"score":0.4172786772251129},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41445210576057434},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3928166925907135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3391779661178589},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.19377672672271729},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1762934923171997},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.1673523187637329},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.1314581036567688},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.07930904626846313},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vts60656.2024.10538531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts60656.2024.10538531","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 42nd VLSI Test Symposium (VTS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1516501267","https://openalex.org/W1971319818","https://openalex.org/W2024894333","https://openalex.org/W2112796928","https://openalex.org/W2125223858","https://openalex.org/W2194775991","https://openalex.org/W2369514888","https://openalex.org/W2560674852","https://openalex.org/W2612375349","https://openalex.org/W2618530766","https://openalex.org/W2625840880","https://openalex.org/W2626719825","https://openalex.org/W2911496292","https://openalex.org/W2914881228","https://openalex.org/W2963163009","https://openalex.org/W3006150812","https://openalex.org/W3033667356","https://openalex.org/W3091374255","https://openalex.org/W3162727751","https://openalex.org/W3184263515","https://openalex.org/W3211559491","https://openalex.org/W4226176885","https://openalex.org/W4243519499","https://openalex.org/W4247950230","https://openalex.org/W4308477919","https://openalex.org/W6600213771","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W2545245183","https://openalex.org/W2054635671","https://openalex.org/W2017425642","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128"],"abstract_inverted_index":{"Resistive":[0],"random-access":[1],"memory":[2],"(RRAM)":[3],"is":[4],"widely":[5],"recognized":[6],"as":[7,171,173],"a":[8,34,46,81,90],"promising":[9],"emerging":[10],"hardware":[11,30],"platform":[12],"for":[13,58],"deep":[14],"neural":[15,69],"networks":[16],"(DNNs).":[17],"Yet,":[18],"due":[19],"to":[20,29,37,99,105,107,118,122,162,178],"manufacturing":[21],"limitations,":[22],"current":[23],"RRAM":[24,56,123],"devices":[25],"are":[26,97],"highly":[27],"susceptible":[28],"defects,":[31],"which":[32],"poses":[33],"significant":[35],"challenge":[36],"their":[38],"practical":[39],"applicability.":[40],"In":[41],"this":[42],"paper,":[43],"we":[44],"present":[45],"machine":[47],"learning":[48],"technique":[49],"that":[50,179],"enables":[51],"the":[52,64,68,86,113,116,126,133,136,154,164,181],"deployment":[53],"of":[54,67,89,95,135,156,166,180],"defect-prone":[55],"accelerators":[57],"DNN":[59,114,167],"applications,":[60],"without":[61],"necessitating":[62],"modifying":[63],"hardware,":[65],"retraining":[66],"network,":[70],"or":[71],"implementing":[72],"additional":[73],"detection":[74],"circuitry/logic.":[75],"The":[76],"key":[77],"idea":[78],"involves":[79],"incorporating":[80],"drop-connect":[82],"inspired":[83],"approach":[84],"during":[85],"training":[87],"phase":[88],"DNN,":[91],"where":[92],"random":[93],"subsets":[94],"weights":[96],"selected":[98],"emulate":[100],"fault":[101,128],"effects":[102],"(e.g.,":[103,160],"set":[104],"zero":[106],"mimic":[108],"stuck-at-1":[109],"faults),":[110],"thereby":[111],"equipping":[112],"with":[115,125,140],"ability":[117],"learn":[119],"and":[120,143,146],"adapt":[121],"defects":[124],"corresponding":[127],"rates.":[129],"Our":[130],"results":[131],"demonstrate":[132],"viability":[134],"dropconnect":[137],"approach,":[138],"coupled":[139],"various":[141],"algorithm":[142],"system-level":[144,187],"design":[145],"trade-off":[147],"considerations.":[148],"We":[149],"show":[150],"that,":[151],"even":[152],"in":[153],"presence":[155],"high":[157],"defect":[158],"rates":[159],"up":[161],"30%),":[163],"degradation":[165],"accuracy":[168],"can":[169],"be":[170],"low":[172],"less":[174],"than":[175],"1%":[176],"compared":[177],"fault-free":[182],"version,":[183],"while":[184],"incurring":[185],"minimal":[186],"runtime/energy":[188],"costs.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
