{"id":"https://openalex.org/W3013896150","doi":"https://doi.org/10.1109/asp-dac47756.2020.9045101","title":"Representable Matrices: Enabling High Accuracy Analog Computation for Inference of DNNs using Memristors","display_name":"Representable Matrices: Enabling High Accuracy Analog Computation for Inference of DNNs using Memristors","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3013896150","doi":"https://doi.org/10.1109/asp-dac47756.2020.9045101","mag":"3013896150"},"language":"en","primary_location":{"id":"doi:10.1109/asp-dac47756.2020.9045101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac47756.2020.9045101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th 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/A5103237642","display_name":"Baogang Zhang","orcid":"https://orcid.org/0000-0002-5305-4331"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baogang Zhang","raw_affiliation_strings":["University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081266557","display_name":"Necati Uysal","orcid":"https://orcid.org/0000-0002-9543-3823"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Necati Uysal","raw_affiliation_strings":["University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047916979","display_name":"Deliang Fan","orcid":"https://orcid.org/0000-0002-7989-6297"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deliang Fan","raw_affiliation_strings":["Arizona State University, Tempe, AZ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014892277","display_name":"Rickard Ewetz","orcid":"https://orcid.org/0000-0002-4183-6926"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rickard Ewetz","raw_affiliation_strings":["University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"538","last_page":"543"},"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9972000122070312,"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/memristor","display_name":"Memristor","score":0.8109192848205566},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6400346755981445},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5716542601585388},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5058495998382568},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5021252632141113},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.4996006488800049},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4924124479293823},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4775703549385071},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46010836958885193},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4567883610725403},{"id":"https://openalex.org/keywords/matrix-multiplication","display_name":"Matrix multiplication","score":0.4561521112918854},{"id":"https://openalex.org/keywords/crossbar-switch","display_name":"Crossbar switch","score":0.4279882311820984},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3246651887893677},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.2663460969924927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18143832683563232},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09251371026039124}],"concepts":[{"id":"https://openalex.org/C150072547","wikidata":"https://www.wikidata.org/wiki/Q212923","display_name":"Memristor","level":2,"score":0.8109192848205566},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6400346755981445},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5716542601585388},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5058495998382568},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5021252632141113},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.4996006488800049},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4924124479293823},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4775703549385071},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46010836958885193},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4567883610725403},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.4561521112918854},{"id":"https://openalex.org/C29984679","wikidata":"https://www.wikidata.org/wiki/Q1929149","display_name":"Crossbar switch","level":2,"score":0.4279882311820984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3246651887893677},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.2663460969924927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18143832683563232},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09251371026039124},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asp-dac47756.2020.9045101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac47756.2020.9045101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC)","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":12,"referenced_works":["https://openalex.org/W1986273360","https://openalex.org/W2014402164","https://openalex.org/W2021383442","https://openalex.org/W2082311137","https://openalex.org/W2091777687","https://openalex.org/W2399958287","https://openalex.org/W2508602506","https://openalex.org/W2518281301","https://openalex.org/W2613989746","https://openalex.org/W2919115771","https://openalex.org/W3099743262","https://openalex.org/W4245731639"],"related_works":["https://openalex.org/W3164474614","https://openalex.org/W2171130799","https://openalex.org/W2005875039","https://openalex.org/W2015477599","https://openalex.org/W2548135880","https://openalex.org/W2144085790","https://openalex.org/W3177379469","https://openalex.org/W2516929886","https://openalex.org/W4253441086","https://openalex.org/W2942778963"],"abstract_inverted_index":{"Analog":[0],"computing":[1],"based":[2,46],"on":[3,47,209],"memristor":[4,31,84,136],"technology":[5],"is":[6,23,45,78,102,111,150,172,211],"a":[7,30,48,65,88,160,203],"promising":[8],"solution":[9],"to":[10,24,29,53,69,114,117,152,174,215],"accelerating":[11],"the":[12,37,55,71,83,93,100,104,118,124,128,131,134,140,143,147,183,186,199],"inference":[13],"phase":[14],"of":[15,99,123,133,142,162,202],"deep":[16],"neural":[17,206],"networks":[18],"(DNNs).":[19],"A":[20],"fundamental":[21],"problem":[22],"map":[25],"an":[26,109],"arbitrary":[27],"matrix":[28,106],"crossbar":[32],"array":[33],"(MCA)":[34],"while":[35],"maximizing":[36],"resulting":[38],"computational":[39],"accuracy.":[40],"The":[41,96,121,194],"state-of-the-art":[42,184],"mapping":[43,188],"technique":[44,66,161],"heuristic":[49],"that":[50,67,103,198],"only":[51,112],"guarantees":[52],"produce":[54,70],"correct":[56,72],"output":[57,73],"for":[58,74],"two":[59,129],"input":[60,76],"vectors.":[61],"In":[62],"this":[63],"paper,":[64],"aims":[68],"every":[75],"vector":[77],"proposed,":[79],"which":[80],"involves":[81],"specifying":[82],"conductance":[85,105,137,164],"values":[86,165],"and":[87,139,155,169],"scaling":[89,125,148],"factor":[90,126,149],"realized":[91,107],"by":[92,108],"peripheral":[94],"circuitry.":[95],"key":[97],"insight":[98],"paper":[101],"MCA":[110],"required":[113],"be":[115],"proportional":[116],"target":[119,144],"matrix.":[120,145],"selection":[122],"between":[127],"regulates":[130],"utilization":[132],"programmable":[135],"range":[138,157],"representability":[141],"Consequently,":[146],"set":[151],"balance":[153],"precision":[154],"value":[156],"errors.":[158,193],"Moreover,":[159],"converting":[163],"into":[166,197],"state":[167],"variables":[168],"vice":[170],"versa":[171],"proposed":[173,187],"handle":[175],"memristors":[176],"with":[177,182],"non-ideal":[178],"device":[179],"characteristics.":[180],"Compared":[181],"technique,":[185],"results":[189],"in":[190],"4X-9X":[191],"smaller":[192],"improvements":[195],"translate":[196],"classification":[200],"accuracy":[201],"seven-layer":[204],"convolutional":[205],"network":[207],"(CNN)":[208],"CIFAR-10":[210],"improved":[212],"from":[213],"20.5%":[214],"71.8%.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
