{"id":"https://openalex.org/W4396686550","doi":"https://doi.org/10.1587/transele.2023ecp5051","title":"Area-Efficient Binarized Neural Network Inference Accelerator Based on Time-Multiplexed XNOR Multiplier Using Loadless 4T SRAM","display_name":"Area-Efficient Binarized Neural Network Inference Accelerator Based on Time-Multiplexed XNOR Multiplier Using Loadless 4T SRAM","publication_year":2024,"publication_date":"2024-05-07","ids":{"openalex":"https://openalex.org/W4396686550","doi":"https://doi.org/10.1587/transele.2023ecp5051"},"language":"en","primary_location":{"id":"doi:10.1587/transele.2023ecp5051","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transele.2023ecp5051","pdf_url":"https://www.jstage.jst.go.jp/article/transele/advpub/0/advpub_2023ECP5051/_pdf","source":{"id":"https://openalex.org/S2489501747","display_name":"IEICE Transactions on Electronics","issn_l":"0916-8524","issn":["0916-8524","1745-1353"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Electronics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.jstage.jst.go.jp/article/transele/advpub/0/advpub_2023ECP5051/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012695055","display_name":"Yihan Zhu","orcid":"https://orcid.org/0000-0002-8150-7350"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yihan ZHU","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040832283","display_name":"Takashi Ohsawa","orcid":"https://orcid.org/0000-0002-8409-1792"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takashi OHSAWA","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5012695055"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04293519,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"E107.C","issue":"12","first_page":"545","last_page":"556"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9855999946594238,"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":0.9855999946594238,"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/T10320","display_name":"Neural Networks and Applications","score":0.9747999906539917,"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/T13182","display_name":"Quantum-Dot Cellular Automata","score":0.970300018787384,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/xnor-gate","display_name":"XNOR gate","score":0.786229133605957},{"id":"https://openalex.org/keywords/static-random-access-memory","display_name":"Static random-access memory","score":0.7557767629623413},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.657426118850708},{"id":"https://openalex.org/keywords/multiplexing","display_name":"Multiplexing","score":0.6408265829086304},{"id":"https://openalex.org/keywords/multiplier","display_name":"Multiplier (economics)","score":0.5784158706665039},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5568888783454895},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.552808940410614},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.37057769298553467},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.34249186515808105},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33429545164108276},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.251171350479126},{"id":"https://openalex.org/keywords/logic-gate","display_name":"Logic gate","score":0.20263192057609558},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15052396059036255}],"concepts":[{"id":"https://openalex.org/C57684291","wikidata":"https://www.wikidata.org/wiki/Q1336142","display_name":"XNOR gate","level":4,"score":0.786229133605957},{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.7557767629623413},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.657426118850708},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.6408265829086304},{"id":"https://openalex.org/C124584101","wikidata":"https://www.wikidata.org/wiki/Q1053266","display_name":"Multiplier (economics)","level":2,"score":0.5784158706665039},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5568888783454895},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.552808940410614},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.37057769298553467},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34249186515808105},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33429545164108276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.251171350479126},{"id":"https://openalex.org/C131017901","wikidata":"https://www.wikidata.org/wiki/Q170451","display_name":"Logic gate","level":2,"score":0.20263192057609558},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15052396059036255},{"id":"https://openalex.org/C124296912","wikidata":"https://www.wikidata.org/wiki/Q575178","display_name":"NAND gate","level":3,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transele.2023ecp5051","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transele.2023ecp5051","pdf_url":"https://www.jstage.jst.go.jp/article/transele/advpub/0/advpub_2023ECP5051/_pdf","source":{"id":"https://openalex.org/S2489501747","display_name":"IEICE Transactions on Electronics","issn_l":"0916-8524","issn":["0916-8524","1745-1353"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Electronics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transele.2023ecp5051","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transele.2023ecp5051","pdf_url":"https://www.jstage.jst.go.jp/article/transele/advpub/0/advpub_2023ECP5051/_pdf","source":{"id":"https://openalex.org/S2489501747","display_name":"IEICE Transactions on Electronics","issn_l":"0916-8524","issn":["0916-8524","1745-1353"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Electronics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396686550.pdf","grobid_xml":"https://content.openalex.org/works/W4396686550.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W421161464","https://openalex.org/W1982118543","https://openalex.org/W2003358164","https://openalex.org/W2122435992","https://openalex.org/W2139451137","https://openalex.org/W2491955681","https://openalex.org/W2544585458","https://openalex.org/W2588191434","https://openalex.org/W2609881373","https://openalex.org/W2793009352","https://openalex.org/W2898665561","https://openalex.org/W2898913080","https://openalex.org/W2904299207","https://openalex.org/W2920326572","https://openalex.org/W2920866490","https://openalex.org/W3000301330","https://openalex.org/W3017968097","https://openalex.org/W3135906938","https://openalex.org/W3138084750","https://openalex.org/W3139521791","https://openalex.org/W3164913974","https://openalex.org/W3201541172","https://openalex.org/W4200551659","https://openalex.org/W4210463344","https://openalex.org/W4226402784","https://openalex.org/W4251722996","https://openalex.org/W4285718438","https://openalex.org/W4300171661","https://openalex.org/W4309311741","https://openalex.org/W4386493391","https://openalex.org/W4390762986"],"related_works":["https://openalex.org/W2108719777","https://openalex.org/W2910771446","https://openalex.org/W2966758645","https://openalex.org/W2559054477","https://openalex.org/W2122693377","https://openalex.org/W2532170798","https://openalex.org/W4320854861","https://openalex.org/W3048955117","https://openalex.org/W2166656370","https://openalex.org/W4283787567"],"abstract_inverted_index":{"A":[0,24],"binarized":[1],"neural":[2],"network":[3],"(BNN)":[4],"inference":[5,70,120],"accelerator":[6,71],"is":[7,33,54,72,132,150,153],"designed":[8],"in":[9,14,45,109],"which":[10,35,122,152],"weights":[11],"are":[12,97,123],"stores":[13],"loadless":[15,38],"four-transistor":[16],"static":[17],"random":[18],"access":[19],"memory":[20],"(4T":[21],"SRAM)":[22],"cells.":[23],"time-multiplexed":[25],"exclusive":[26],"NOR":[27],"(XNOR)":[28],"multiplier":[29],"with":[30,50,80,113],"switched":[31],"capacitors":[32],"proposed":[34,56],"prevents":[36],"the":[37,46,59,75,88,90,94,114,128,140,156,159],"4T":[39],"SRAM":[40,116,160],"cell":[41,117,130,141,161],"from":[42],"being":[43],"destroyed":[44],"operation.":[47],"An":[48],"accumulator":[49],"current":[51],"sensing":[52],"scheme":[53],"also":[55],"to":[57,74,99,125,134,155],"make":[58],"multiply-accumulate":[60],"operation":[61],"(MAC)":[62],"completely":[63],"linear":[64],"and":[65,87,93,103,139],"read-disturb":[66],"free.":[67],"The":[68],"BNN":[69,119,163],"applied":[73],"MNIST":[76],"dataset":[77],"recognition":[78],"problem":[79],"accuracy":[81],"of":[82,158],"96.2%":[83],"for":[84],"500":[85],"data":[86],"throughput,":[89],"energy":[91],"efficiency":[92,96,142],"area":[95],"confirmed":[98],"be":[100],"15.50TOPS,":[101],"72.17TOPS/W":[102],"50.13TOPS/mm2,":[104],"respectively,":[105],"by":[106],"HSPICE":[107],"simulation":[108],"32nm":[110,126],"technology.":[111],"Compared":[112],"conventional":[115],"based":[118,162],"accelerators":[121],"scaled":[124],"technology,":[127],"synapse":[129],"size":[131],"reduced":[133],"less":[135],"than":[136],"16%":[137],"(0.235\u03bcm2)":[138],"(synapse":[143],"array":[144,146],"area/synapse":[145],"plus":[147],"peripheral":[148],"circuits)":[149],"73.27%":[151],"equivalent":[154],"state-of-the-art":[157],"accelerators.":[164]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
