{"id":"https://openalex.org/W3081320461","doi":"https://doi.org/10.1109/tvlsi.2020.3016939","title":"ADIC: Anomaly Detection Integrated Circuit in 65-nm CMOS Utilizing Approximate Computing","display_name":"ADIC: Anomaly Detection Integrated Circuit in 65-nm CMOS Utilizing Approximate Computing","publication_year":2020,"publication_date":"2020-09-02","ids":{"openalex":"https://openalex.org/W3081320461","doi":"https://doi.org/10.1109/tvlsi.2020.3016939","mag":"3081320461"},"language":"en","primary_location":{"id":"doi:10.1109/tvlsi.2020.3016939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvlsi.2020.3016939","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.09442","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018201663","display_name":"Bapi Kar","orcid":"https://orcid.org/0000-0001-9140-0816"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bapi Kar","raw_affiliation_strings":["Mentor Graphics, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"Mentor Graphics, Bengaluru, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060345086","display_name":"P. K. Gopalakrishnan","orcid":"https://orcid.org/0000-0001-6597-6141"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Pradeep Kumar Gopalakrishnan","raw_affiliation_strings":["Delta-NTU Corporate Laboratory for Cyber-Physical Systems, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Delta-NTU Corporate Laboratory for Cyber-Physical Systems, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040579466","display_name":"Sumon Kumar Bose","orcid":"https://orcid.org/0000-0002-7583-972X"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Sumon Kumar Bose","raw_affiliation_strings":["Delta-NTU Corporate Laboratory for Cyber-Physical Systems, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Delta-NTU Corporate Laboratory for Cyber-Physical Systems, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082017465","display_name":"Mohendra Roy","orcid":"https://orcid.org/0000-0001-5815-3294"},"institutions":[{"id":"https://openalex.org/I33586908","display_name":"Pandit Deendayal Energy University","ror":"https://ror.org/02nsv5p42","country_code":"IN","type":"education","lineage":["https://openalex.org/I33586908"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mohendra Roy","raw_affiliation_strings":["Department of Information and Communication Technology (ICT), Pandit Deendayal Petroleum University, Gandhinagar, India","Department of Science, Pandit Deendayal Petroleum University, Gandhinagar, India"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Technology (ICT), Pandit Deendayal Petroleum University, Gandhinagar, India","institution_ids":["https://openalex.org/I33586908"]},{"raw_affiliation_string":"Department of Science, Pandit Deendayal Petroleum University, Gandhinagar, India","institution_ids":["https://openalex.org/I33586908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002380437","display_name":"Arindam Basu","orcid":"https://orcid.org/0000-0003-1035-8770"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Arindam Basu","raw_affiliation_strings":["Delta-NTU Corporate Laboratory for Cyber-Physical Systems, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Delta-NTU Corporate Laboratory for Cyber-Physical Systems, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018201663"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7262,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.70737714,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"28","issue":"12","first_page":"2518","last_page":"2529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10558","display_name":"Advancements in Semiconductor Devices and Circuit Design","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/T10558","display_name":"Advancements in Semiconductor Devices and Circuit Design","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/T12676","display_name":"Machine Learning and ELM","score":0.9984999895095825,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9975000023841858,"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":0.6509859561920166},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5866793990135193},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.584073543548584},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.5653648376464844},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5140015482902527},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.501507043838501},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.45039457082748413},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3847965598106384},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35792601108551025},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32419300079345703},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1936110258102417},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.17802345752716064}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6509859561920166},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5866793990135193},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.584073543548584},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.5653648376464844},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5140015482902527},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.501507043838501},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.45039457082748413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3847965598106384},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35792601108551025},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32419300079345703},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1936110258102417},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.17802345752716064}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tvlsi.2020.3016939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvlsi.2020.3016939","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"},{"id":"pmh:oai:arXiv.org:2008.09442","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.09442","pdf_url":"https://arxiv.org/pdf/2008.09442","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/160503","is_oa":false,"landing_page_url":"https://hdl.handle.net/10356/160503","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2008.09442","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.09442","pdf_url":"https://arxiv.org/pdf/2008.09442","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8299999833106995}],"awards":[],"funders":[{"id":"https://openalex.org/F4320307110","display_name":"Delta","ror":"https://ror.org/03g9c1e75"},{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W563268501","https://openalex.org/W1530232915","https://openalex.org/W1974511160","https://openalex.org/W2002034577","https://openalex.org/W2027764190","https://openalex.org/W2041970641","https://openalex.org/W2076698365","https://openalex.org/W2111072639","https://openalex.org/W2123395972","https://openalex.org/W2132265582","https://openalex.org/W2138061685","https://openalex.org/W2142047467","https://openalex.org/W2142889610","https://openalex.org/W2158054309","https://openalex.org/W2160732108","https://openalex.org/W2174164007","https://openalex.org/W2186910770","https://openalex.org/W2289252105","https://openalex.org/W2474046725","https://openalex.org/W2534066147","https://openalex.org/W2554061044","https://openalex.org/W2565960208","https://openalex.org/W2575612002","https://openalex.org/W2592389822","https://openalex.org/W2747730547","https://openalex.org/W2766143712","https://openalex.org/W2768475350","https://openalex.org/W2790556218","https://openalex.org/W2792607576","https://openalex.org/W2799969407","https://openalex.org/W2804841412","https://openalex.org/W2898723834","https://openalex.org/W2902061487","https://openalex.org/W2910207417","https://openalex.org/W2924453407","https://openalex.org/W2952671592","https://openalex.org/W2997303620","https://openalex.org/W3024621361","https://openalex.org/W3104422614","https://openalex.org/W4236476483","https://openalex.org/W4297814361","https://openalex.org/W6678945949","https://openalex.org/W6720514713","https://openalex.org/W6748877789","https://openalex.org/W6749349402"],"related_works":["https://openalex.org/W3014521742","https://openalex.org/W2617868873","https://openalex.org/W3204141294","https://openalex.org/W4386230336","https://openalex.org/W4306968100","https://openalex.org/W2171986175","https://openalex.org/W2089791793","https://openalex.org/W2038858740","https://openalex.org/W1491218245","https://openalex.org/W2562383580"],"abstract_inverted_index":{"In":[0,47],"this":[1],"article,":[2],"we":[3],"present":[4],"a":[5,15,27,58,76,105,128],"low-power":[6],"(LP)":[7],"anomaly":[8,146],"detection":[9],"integrated":[10],"circuit":[11],"(ADIC)":[12],"based":[13,144],"on":[14,98,145,192],"one-class":[16],"classifier":[17,107],"(OCC)":[18],"neural":[19,60,141],"network.":[20],"The":[21],"ADIC":[22,153],"achieves":[23],"LP":[24],"operation":[25],"through":[26],"combination":[28],"of:":[29],"1)":[30],"careful":[31],"choice":[32],"of":[33,79,90,101,104,111,115,130,200,209,217],"algorithm":[34],"for":[35,62,84,207],"online":[36,49],"learning":[37,125,172],"and":[38,64,165,168,173],"2)":[39],"approximate":[40,135],"computing":[41,136,225],"techniques":[42],"to":[43,56,94,123,213],"lower":[44],"average":[45],"energy.":[46],"particular,":[48],"pseudoinverse":[50],"update":[51],"method":[52,81],"(OPIUM)":[53],"is":[54,82,121],"used":[55,83],"train":[57],"randomized":[59],"network":[61,142],"quick":[63],"resource-efficient":[65],"learning.":[66],"An":[67],"additional":[68],"42%":[69],"energy":[70,215],"saving":[71],"can":[72,203],"be":[73,204],"achieved":[74],"when":[75,184],"lighter":[77],"version":[78],"OPIUM":[80],"training":[85],"with":[86,108,159],"the":[87,99,140,152,193,201,210,236],"same":[88],"number":[89,110],"data":[91,196],"samples":[92],"lead":[93],"no":[95],"significant":[96],"compromise":[97],"quality":[100],"inference.":[102],"Instead":[103],"single":[106],"large":[109],"neurons,":[112],"an":[113,214,220],"ensemble":[114],"K":[116,155],"base":[117],"learner":[118],"(BL)":[119],"approach":[120],"chosen":[122],"reduce":[124],"memory":[126],"by":[127,137],"factor":[129],"K.":[131],"This":[132],"also":[133],"enables":[134],"dynamically":[138],"varying":[139],"size":[143],"detection.":[147],"Fabricated":[148],"in":[149,162],"65-nm":[150],"CMOS,":[151],"has":[154],"=":[156,181,232],"7":[157],"BLs":[158,187],"32":[160],"neurons":[161],"each":[163],"BL":[164],"dissipates":[166],"11.87":[167],"3.35":[169],"pJ/OP":[170],"during":[171],"inference,":[174],"respectively,":[175],"at":[176,227],"V":[177,183,228,234],"<sub":[178,229],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[179,230],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">dd</sub>":[180,231],"0.75":[182],"all":[185],"seven":[186],"are":[188],"enabled.":[189],"Furthermore,":[190],"evaluated":[191],"NASA":[194],"bearing":[195],"set,":[197],"approximately":[198],"80%":[199],"chip":[202],"shut":[205],"down":[206],"99%":[208],"lifetime":[211],"leading":[212],"efficiency":[216],"0.48":[218],"pJ/OP,":[219],"18.5\u00d7":[221],"reduction":[222],"over":[223],"full-precision":[224],"running":[226],"1.2":[233],"throughout":[235],"lifetime.":[237]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2020-09-01T00:00:00"}