{"id":"https://openalex.org/W2601128462","doi":"https://doi.org/10.1109/tvlsi.2017.2682885","title":"Resilience-Aware Frequency Tuning for Neural-Network-Based Approximate Computing Chips","display_name":"Resilience-Aware Frequency Tuning for Neural-Network-Based Approximate Computing Chips","publication_year":2017,"publication_date":"2017-03-31","ids":{"openalex":"https://openalex.org/W2601128462","doi":"https://doi.org/10.1109/tvlsi.2017.2682885","mag":"2601128462"},"language":"en","primary_location":{"id":"doi:10.1109/tvlsi.2017.2682885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvlsi.2017.2682885","pdf_url":null,"source":{"id":"https://openalex.org/S37538908","display_name":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","issn_l":"1063-8210","issn":["1063-8210","1557-9999"],"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 Very Large Scale Integration (VLSI) 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/A5100346965","display_name":"Ying Wang","orcid":"https://orcid.org/0000-0001-5172-4736"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"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":"Ying Wang","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5172-4736","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043488012","display_name":"Jiachao Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"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":"Jiachao Deng","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022246777","display_name":"Yuntan Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"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":"Yuntan Fang","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100768288","display_name":"Huawei Li","orcid":"https://orcid.org/0000-0001-8082-4218"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"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":"Huawei Li","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023380073","display_name":"Xiaowei Li","orcid":"https://orcid.org/0000-0002-0874-814X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"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":"Xiaowei Li","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100346965"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"],"apc_list":null,"apc_paid":null,"fwci":1.6072,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.84259773,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"25","issue":"10","first_page":"2736","last_page":"2748"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"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":0.9998999834060669,"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/T10363","display_name":"Low-power high-performance VLSI design","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/T10472","display_name":"Semiconductor materials and 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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7598117589950562},{"id":"https://openalex.org/keywords/retiming","display_name":"Retiming","score":0.7296384572982788},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5468894243240356},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5274127721786499},{"id":"https://openalex.org/keywords/electronic-circuit","display_name":"Electronic circuit","score":0.4788672626018524},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.46546411514282227},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.4368608593940735},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.4141799509525299},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3309639096260071},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2600287199020386},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1362781524658203},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.08999329805374146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7598117589950562},{"id":"https://openalex.org/C41112130","wikidata":"https://www.wikidata.org/wiki/Q2146175","display_name":"Retiming","level":2,"score":0.7296384572982788},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5468894243240356},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5274127721786499},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.4788672626018524},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.46546411514282227},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.4368608593940735},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.4141799509525299},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3309639096260071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2600287199020386},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1362781524658203},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.08999329805374146},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvlsi.2017.2682885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvlsi.2017.2682885","pdf_url":null,"source":{"id":"https://openalex.org/S37538908","display_name":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","issn_l":"1063-8210","issn":["1063-8210","1557-9999"],"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 Very Large Scale Integration (VLSI) Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.4699999988079071,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G1051257415","display_name":null,"funder_award_id":"61432017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1727459820","display_name":null,"funder_award_id":"61402146","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2122852399","display_name":null,"funder_award_id":"61532017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4242556522","display_name":null,"funder_award_id":"61504153","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4853362136","display_name":null,"funder_award_id":"61572470","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8380396287","display_name":null,"funder_award_id":"61521092","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1535041666","https://openalex.org/W1677182931","https://openalex.org/W1967519200","https://openalex.org/W1996431812","https://openalex.org/W2003957094","https://openalex.org/W2006312753","https://openalex.org/W2008684926","https://openalex.org/W2009354889","https://openalex.org/W2010069327","https://openalex.org/W2082738287","https://openalex.org/W2097117768","https://openalex.org/W2098335003","https://openalex.org/W2109492604","https://openalex.org/W2117539524","https://openalex.org/W2125169487","https://openalex.org/W2129212061","https://openalex.org/W2138565468","https://openalex.org/W2143283746","https://openalex.org/W2148605318","https://openalex.org/W2150283124","https://openalex.org/W2150853784","https://openalex.org/W2155893237","https://openalex.org/W2156425544","https://openalex.org/W2163605009","https://openalex.org/W2166250385","https://openalex.org/W2167677193","https://openalex.org/W2167872527","https://openalex.org/W2187230075","https://openalex.org/W2265166184","https://openalex.org/W2403646140","https://openalex.org/W2429549959","https://openalex.org/W3120740533","https://openalex.org/W3151762208","https://openalex.org/W4231091214","https://openalex.org/W4234461763","https://openalex.org/W4234808521","https://openalex.org/W4240268885","https://openalex.org/W6632149132","https://openalex.org/W6642147921","https://openalex.org/W6651700774","https://openalex.org/W6652670974","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2134549436","https://openalex.org/W233224440","https://openalex.org/W2160236198","https://openalex.org/W1951668625","https://openalex.org/W2903287280","https://openalex.org/W3140976369","https://openalex.org/W2132158474","https://openalex.org/W1937646452","https://openalex.org/W2161928569","https://openalex.org/W4238503248"],"abstract_inverted_index":{"Unlike":[0],"conventional":[1],"ICs,":[2],"approximate":[3,71,143],"computing":[4,72,144],"chips":[5],"are":[6],"less":[7],"sensitive":[8],"to":[9,18,90,196],"hardware":[10],"errors.":[11],"This":[12],"fascinating":[13],"feature":[14],"can":[15,87,170,181],"be":[16,88,171,193],"utilized":[17],"improve":[19],"the":[20,28,42,51,80,99,148,152,179,188],"performance":[21],"of":[22,32,44,118,202],"chip":[23],"design":[24,35],"and":[25,49,65,126,137,154],"even":[26],"change":[27],"timing":[29,63,105,119,165],"closure":[30],"procedure":[31],"digital":[33],"circuit":[34,46,134],"flow.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40],"study":[41],"potential":[43],"resilience-aware":[45],"clocking":[47,185],"scheme,":[48],"demonstrate":[50],"methodology":[52,149],"with":[53,98,115,150,205],"advanced":[54],"neural":[55,153,168],"network":[56],"(NN)-based":[57],"accelerator.":[58],"We":[59,146],"propose":[60],"a":[61,199],"novel":[62],"analysis":[64,106],"frequency":[66,100,136,203],"setting":[67],"method":[68,131],"for":[69,142,174],"NN-based":[70,85],"circuits":[73,169,180],"based":[74],"on":[75],"in-field":[76],"NN":[77],"retraining.":[78],"With":[79],"proposed":[81],"iterative":[82],"retiming-and-retraining":[83,130],"framework,":[84],"accelerator":[86],"retrained":[89],"operate":[91,182],"safely":[92],"at":[93,183,198],"aggressive":[94],"operating":[95,135],"frequencies":[96],"compared":[97],"decided":[101],"purely":[102],"by":[103,122],"statistical":[104],"or":[107,192],"Monto":[108],"Carlo":[109],"analysis.":[110],"For":[111],"nanometer":[112],"process":[113,123],"technology":[114],"increasing":[116],"threats":[117],"errors":[120,166],"induced":[121],"variation,":[124],"noises,":[125],"so":[127,177],"on,":[128],"our":[129],"enables":[132,138],"higher":[133,184],"dynamic":[139],"precision/frequency":[140],"adjustment":[141],"circuits.":[145],"evaluate":[147],"both":[151],"deep":[155],"learning":[156],"accelerators":[157],"in":[158,167],"experiments.":[159],"The":[160],"experimental":[161],"results":[162],"show":[163],"that":[164,178],"effectively":[172],"tamed":[173],"different":[175],"applications,":[176],"rates":[186],"under":[187],"specified":[189],"quality":[190],"constraint":[191],"dynamically":[194],"scaled":[195],"work":[197],"wide":[200],"range":[201],"states":[204],"only":[206],"minor":[207],"accuracy":[208],"losses.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
