{"id":"https://openalex.org/W3158277821","doi":"https://doi.org/10.1109/iscas51556.2021.9401758","title":"A Comparative Analysis of Time-Domain and Digital-Domain Hardware Accelerators for Neural Networks","display_name":"A Comparative Analysis of Time-Domain and Digital-Domain Hardware Accelerators for Neural Networks","publication_year":2021,"publication_date":"2021-04-27","ids":{"openalex":"https://openalex.org/W3158277821","doi":"https://doi.org/10.1109/iscas51556.2021.9401758","mag":"3158277821"},"language":"en","primary_location":{"id":"doi:10.1109/iscas51556.2021.9401758","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas51556.2021.9401758","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5025512202","display_name":"Hamza Al Maharmeh","orcid":"https://orcid.org/0000-0001-9270-9049"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hamza Al Maharmeh","raw_affiliation_strings":["WINCAS Research Center, Wayne State University, Detroit, USA"],"affiliations":[{"raw_affiliation_string":"WINCAS Research Center, Wayne State University, Detroit, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074152935","display_name":"Nabil J. Sarhan","orcid":"https://orcid.org/0000-0002-0527-5666"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nabil J. Sarhan","raw_affiliation_strings":["WINCAS Research Center, Wayne State University, Detroit, USA"],"affiliations":[{"raw_affiliation_string":"WINCAS Research Center, Wayne State University, Detroit, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010248769","display_name":"Chung-Chih Hung","orcid":"https://orcid.org/0000-0002-5817-712X"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chung-Chih Hung","raw_affiliation_strings":["National Chiao Tung University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020983859","display_name":"Mohammed Ismail","orcid":"https://orcid.org/0000-0001-9574-0949"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammed Ismail","raw_affiliation_strings":["WINCAS Research Center, Wayne State University, Detroit, USA"],"affiliations":[{"raw_affiliation_string":"WINCAS Research Center, Wayne State University, Detroit, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071540979","display_name":"Mohammad Alhawari","orcid":"https://orcid.org/0000-0002-5015-5081"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Alhawari","raw_affiliation_strings":["WINCAS Research Center, Wayne State University, Detroit, USA"],"affiliations":[{"raw_affiliation_string":"WINCAS Research Center, Wayne State University, Detroit, USA","institution_ids":["https://openalex.org/I185443292"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5025512202"],"corresponding_institution_ids":["https://openalex.org/I185443292"],"apc_list":null,"apc_paid":null,"fwci":0.7019,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.68759432,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9990000128746033,"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/throughput","display_name":"Throughput","score":0.80573570728302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7203655242919922},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6798972487449646},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6753586530685425},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.5520393252372742},{"id":"https://openalex.org/keywords/power-consumption","display_name":"Power consumption","score":0.5348104238510132},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.5122243762016296},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4803253710269928},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.449513703584671},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.4365774691104889},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.42732134461402893},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.38690754771232605},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.38569411635398865},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3696305751800537},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.33757323026657104},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24198287725448608},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.20207509398460388},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.1398274302482605},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.12419670820236206},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11523336172103882},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08751016855239868},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0747230052947998}],"concepts":[{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.80573570728302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7203655242919922},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6798972487449646},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6753586530685425},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.5520393252372742},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.5348104238510132},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.5122243762016296},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4803253710269928},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.449513703584671},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.4365774691104889},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.42732134461402893},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.38690754771232605},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.38569411635398865},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3696305751800537},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.33757323026657104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24198287725448608},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.20207509398460388},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.1398274302482605},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.12419670820236206},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11523336172103882},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08751016855239868},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0747230052947998},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas51556.2021.9401758","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas51556.2021.9401758","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.9100000262260437}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2007283083","https://openalex.org/W2112796928","https://openalex.org/W2553345846","https://openalex.org/W2725092576","https://openalex.org/W2740857766","https://openalex.org/W2753909399","https://openalex.org/W2773522834","https://openalex.org/W2903841424","https://openalex.org/W2905659884","https://openalex.org/W2942683366","https://openalex.org/W2943365647","https://openalex.org/W2945323101","https://openalex.org/W2981240739","https://openalex.org/W3083140625","https://openalex.org/W3083205222","https://openalex.org/W6741876214","https://openalex.org/W6746706034"],"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/W2464627195","https://openalex.org/W2171986175","https://openalex.org/W2118008391","https://openalex.org/W4241314868","https://openalex.org/W3013241373"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,37,81],"comprehensive":[4],"analysis":[5],"of":[6,59,77,83],"hardware":[7],"accelerators":[8,31],"for":[9,54,116,130,153],"neural":[10,43,155],"networks":[11,156],"in":[12,36,48,57],"both":[13],"the":[14,20,49,73,90,98,102,133,136,141,148],"digital":[15,50,87,149],"and":[16,26,34,51,64,122,140,157],"time":[17,52],"domains,":[18],"where":[19,132],"latter":[21],"includes":[22],"spatially":[23],"unrolled":[24],"(SU)":[25],"recursive":[27],"(REC)":[28],"architectures.":[29],"All":[30],"are":[32],"implemented":[33,47],"synthesized":[35],"65nm":[38],"CMOS":[39],"technology.":[40],"An":[41],"identical":[42],"network":[44],"model":[45],"is":[46,89,97,101,113,127,135,143,151],"domain":[53],"comparative":[55],"purposes":[56],"terms":[58],"throughput,":[60],"power":[61,120],"consumption,":[62],"area,":[63],"energy":[65,75],"efficiency.":[66],"Post-synthesis":[67],"results":[68],"show":[69],"that":[70,160],"SU":[71,112],"achieves":[72],"highest":[74],"efficiency":[76],"145":[78],"TOp/s/W":[79],"with":[80,118],"throughput":[82,142],"4":[84],"GOp/s.":[85],"The":[86],"core":[88,150],"fastest":[91],"among":[92],"other":[93],"cores,":[94],"whereas":[95],"REC":[96,126],"slowest":[99],"but":[100],"most":[103,137],"area-efficient,":[104],"occupying":[105],"0.114":[106],"mm":[107],"<sup":[108],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[109],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[110],".":[111],"more":[114],"suited":[115,129],"applications":[117,131,159],"stringent":[119],"constraints":[121],"average":[123],"performance,":[124],"while":[125],"better":[128],"area":[134],"important":[138],"requirement":[139],"less":[144],"significant.":[145],"In":[146],"contrast,":[147],"preferable":[152],"large":[154],"critical":[158],"require":[161],"high":[162],"performance.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}