{"id":"https://openalex.org/W4213221357","doi":"https://doi.org/10.1109/asp-dac52403.2022.9712525","title":"Reliable Memristive Neural Network Accelerators Based on Early Denoising and Sparsity Induction","display_name":"Reliable Memristive Neural Network Accelerators Based on Early Denoising and Sparsity Induction","publication_year":2022,"publication_date":"2022-01-17","ids":{"openalex":"https://openalex.org/W4213221357","doi":"https://doi.org/10.1109/asp-dac52403.2022.9712525"},"language":"en","primary_location":{"id":"doi:10.1109/asp-dac52403.2022.9712525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac52403.2022.9712525","pdf_url":null,"source":{"id":"https://openalex.org/S4363608500","display_name":"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)","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 27th Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5087147041","display_name":"Anlan Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anlan Yu","raw_affiliation_strings":["Lehigh University,Department of Electrical and Computer Engineering","Department of Electrical and Computer Engineering, Lehigh University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lehigh University,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I186143895"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Lehigh University","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102953733","display_name":"Ning Lyu","orcid":null},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ning Lyu","raw_affiliation_strings":["Lehigh University,Department of Electrical and Computer Engineering","Department of Electrical and Computer Engineering, Lehigh University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lehigh University,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I186143895"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Lehigh University","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067226050","display_name":"Wujie Wen","orcid":"https://orcid.org/0000-0003-0011-0675"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wujie Wen","raw_affiliation_strings":["Lehigh University,Department of Electrical and Computer Engineering","Department of Electrical and Computer Engineering, Lehigh University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lehigh University,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I186143895"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Lehigh University","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101582861","display_name":"Zhiyuan Yan","orcid":"https://orcid.org/0000-0003-2286-2771"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiyuan Yan","raw_affiliation_strings":["Lehigh University,Department of Electrical and Computer Engineering","Department of Electrical and Computer Engineering, Lehigh University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lehigh University,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I186143895"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Lehigh University","institution_ids":["https://openalex.org/I186143895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I186143895"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"598","last_page":"603"},"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":0.9962999820709229,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/crossbar-switch","display_name":"Crossbar switch","score":0.821821928024292},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7529634237289429},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6748540997505188},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6623693704605103},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.47014549374580383},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46920862793922424},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4354642331600189},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.411914587020874},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3622482419013977},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30487778782844543}],"concepts":[{"id":"https://openalex.org/C29984679","wikidata":"https://www.wikidata.org/wiki/Q1929149","display_name":"Crossbar switch","level":2,"score":0.821821928024292},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7529634237289429},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6748540997505188},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6623693704605103},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.47014549374580383},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46920862793922424},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4354642331600189},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.411914587020874},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3622482419013977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30487778782844543},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asp-dac52403.2022.9712525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac52403.2022.9712525","pdf_url":null,"source":{"id":"https://openalex.org/S4363608500","display_name":"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)","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 27th Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4394989467","display_name":null,"funder_award_id":"CCF-2006748,CCF-2011236,ECCS-1835278","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1971319818","https://openalex.org/W2004823737","https://openalex.org/W2056507634","https://openalex.org/W2063689849","https://openalex.org/W2155954834","https://openalex.org/W2405578611","https://openalex.org/W2474119684","https://openalex.org/W2518281301","https://openalex.org/W2530386080","https://openalex.org/W2608111952","https://openalex.org/W2612375349","https://openalex.org/W2735426554","https://openalex.org/W2795127895","https://openalex.org/W2883929540","https://openalex.org/W2890964092","https://openalex.org/W2899915146","https://openalex.org/W2923010225","https://openalex.org/W2945387900","https://openalex.org/W2946522000","https://openalex.org/W2951094271","https://openalex.org/W2971622202","https://openalex.org/W2973798619","https://openalex.org/W2997019200","https://openalex.org/W3048152613","https://openalex.org/W3208788005","https://openalex.org/W4292169167","https://openalex.org/W6713835734","https://openalex.org/W6720547715","https://openalex.org/W6737781249","https://openalex.org/W6803284059"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W2750384547","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W4389249638","https://openalex.org/W4386216112","https://openalex.org/W1636374761","https://openalex.org/W3141540147"],"abstract_inverted_index":{"Implementing":[0],"deep":[1],"neural":[2],"networks":[3],"(DNNs)":[4],"in":[5,106,123],"hardware":[6],"is":[7,48,96,117,176],"challenging":[8],"due":[9],"to":[10,30,44,78,98,162,185,189],"the":[11,100,107,111,118,124,138,164,171,191,202,205,229],"requirements":[12],"of":[13,37,59,75,102,113,166,170,204],"huge":[14],"memory":[15],"and":[16,64,179,231],"computation":[17,63,105,140],"associated":[18],"with":[19],"DNNs'":[20],"primary":[21,57],"operation\u2014matrix-vector":[22],"multiplications":[23],"(MVMs).":[24],"Memristive":[25],"crossbar":[26,129,139],"shows":[27],"great":[28],"potential":[29],"accelerate":[31],"MVMs":[32],"by":[33,55,147,159],"leveraging":[34],"its":[35,81],"capability":[36],"in-memory":[38],"computation.":[39],"However,":[40],"one":[41],"critical":[42],"obstacle":[43],"such":[45],"a":[46,73,87,155,195],"technique":[47],"potentially":[49],"significant":[50],"inference":[51],"accuracy":[52,226],"degradation":[53],"caused":[54,146],"two":[56],"sources":[58],"errors\u2014the":[60],"variations":[61,103],"during":[62,104],"stuck-at-faults":[65],"(SAFs).":[66],"To":[67,110],"overcome":[68],"this":[69,116],"obstacle,":[70],"we":[71,153,183],"propose":[72,154,184],"set":[74],"dedicated":[76],"schemes":[77,222],"significantly":[79],"enhance":[80],"tolerance":[82],"against":[83],"these":[84],"errors.":[85],"First,":[86],"minimum":[88],"mean":[89],"square":[90],"error":[91],"(MMSE)":[92],"based":[93],"denoising":[94,122,134,215],"scheme":[95,158,175],"proposed":[97,172,206],"diminish":[99],"impact":[101,165],"intermediate":[108,125],"layers.":[109],"best":[112],"our":[114,221],"knowledge,":[115],"first":[119],"work":[120],"considering":[121],"layers":[126],"without":[127],"extra":[128],"resources.":[130],"Furthermore,":[131],"MMSE":[132],"early":[133,214],"not":[135,198],"only":[136,199],"stabilizes":[137],"results":[141,218],"but":[142,210],"also":[143,211],"mitigates":[144],"errors":[145],"low":[148],"resolution":[149],"analog-to-digital":[150],"converters.":[151],"Second,":[152],"weights-to-crossbar":[156],"mapping":[157],"inverting":[160],"bits":[161],"mitigate":[163],"SAFs.":[167],"The":[168],"effectiveness":[169,203],"bit":[173,207],"inversion":[174,208],"analyzed":[177],"theoretically":[178],"demonstrated":[180],"experimentally.":[181],"Finally,":[182],"use":[186],"L1":[187],"regularization":[188],"increase":[190],"network":[192],"sparsity,":[193],"as":[194],"greater":[196],"sparsity":[197],"further":[200],"enhances":[201],"scheme,":[209],"facilitates":[212],"other":[213],"mechanisms.":[216],"Experimental":[217],"show":[219],"that":[220],"can":[223],"achieve":[224],"40%-78%":[225],"improvement,":[227],"for":[228],"MNIST":[230],"CIFAR10":[232],"classification":[233],"tasks":[234],"under":[235],"different":[236],"networks.":[237]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}