{"id":"https://openalex.org/W3200753201","doi":"https://doi.org/10.1109/icufn49451.2021.9528655","title":"A High Accuracy Low Power Convolution Operator with 12T SRAM for CNN","display_name":"A High Accuracy Low Power Convolution Operator with 12T SRAM for CNN","publication_year":2021,"publication_date":"2021-08-17","ids":{"openalex":"https://openalex.org/W3200753201","doi":"https://doi.org/10.1109/icufn49451.2021.9528655","mag":"3200753201"},"language":"en","primary_location":{"id":"doi:10.1109/icufn49451.2021.9528655","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icufn49451.2021.9528655","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN)","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/A5080653761","display_name":"Tae Seob Oh","orcid":null},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Tae Seob Oh","raw_affiliation_strings":["Sungkyunkwan University, Suwon, South Korea"],"affiliations":[{"raw_affiliation_string":"Sungkyunkwan University, Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071917383","display_name":"YoungGun Pu","orcid":"https://orcid.org/0000-0001-5190-4462"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"YoungGun Pu","raw_affiliation_strings":["Sungkyunkwan University, Suwon, South Korea"],"affiliations":[{"raw_affiliation_string":"Sungkyunkwan University, Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080690290","display_name":"Kang\u2010Yoon Lee","orcid":"https://orcid.org/0000-0001-9777-6953"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kang-Yoon Lee","raw_affiliation_strings":["Sungkyunkwan University, Suwon, South Korea"],"affiliations":[{"raw_affiliation_string":"Sungkyunkwan University, Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080653761"],"corresponding_institution_ids":["https://openalex.org/I848706"],"apc_list":null,"apc_paid":null,"fwci":0.1003,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.43392719,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"295","last_page":"298"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9991000294685364,"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/T10502","display_name":"Advanced Memory and Neural Computing","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/T13182","display_name":"Quantum-Dot Cellular Automata","score":0.9944000244140625,"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"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9902999997138977,"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/static-random-access-memory","display_name":"Static random-access memory","score":0.9261553287506104},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6941158175468445},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.6085985898971558},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5517426133155823},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.4927957355976105},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.459408164024353},{"id":"https://openalex.org/keywords/random-access-memory","display_name":"Random access memory","score":0.4565039575099945},{"id":"https://openalex.org/keywords/inverter","display_name":"Inverter","score":0.41489535570144653},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.2997453808784485},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24865266680717468},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08153295516967773},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06066599488258362},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.05936908721923828}],"concepts":[{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.9261553287506104},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6941158175468445},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.6085985898971558},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5517426133155823},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.4927957355976105},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.459408164024353},{"id":"https://openalex.org/C2994168587","wikidata":"https://www.wikidata.org/wiki/Q5295","display_name":"Random access memory","level":2,"score":0.4565039575099945},{"id":"https://openalex.org/C11190779","wikidata":"https://www.wikidata.org/wiki/Q664575","display_name":"Inverter","level":3,"score":0.41489535570144653},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.2997453808784485},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24865266680717468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08153295516967773},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06066599488258362},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.05936908721923828},{"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/icufn49451.2021.9528655","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icufn49451.2021.9528655","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2904299207","https://openalex.org/W3011306351","https://openalex.org/W3089326051"],"related_works":["https://openalex.org/W98453623","https://openalex.org/W2340624421","https://openalex.org/W1909296377","https://openalex.org/W2089002058","https://openalex.org/W2626140143","https://openalex.org/W3185029353","https://openalex.org/W3116379964","https://openalex.org/W2766443086","https://openalex.org/W2793465010","https://openalex.org/W1985899440"],"abstract_inverted_index":{"To":[0],"get":[1],"high":[2],"accuracy,":[3],"various":[4],"weight":[5,17,47],"should":[6],"be":[7,42,50],"stored":[8,51],"in":[9,52,63],"memory.":[10],"For":[11],"this,":[12],"this":[13],"paper":[14],"presents":[15],"tri-state":[16],"static":[18],"random":[19],"access":[20],"memory(SRAM).":[21],"12T":[22,53],"SRAM":[23,54,88],"is":[24,57,83,92],"a":[25,64],"form":[26],"of":[27,73],"power":[28,37],"gating":[29],"on":[30],"the":[31,39,71,80,86,90],"conventional":[32,87],"10T":[33],"SRAM.":[34],"By":[35],"using":[36],"gating,":[38],"inverter":[40,56],"can":[41,49],"turned":[43,58],"off.":[44,59],"The":[45,60],"new":[46],"(0)":[48],"when":[55],"operator":[61],"fabricated":[62],"0.18-\u00b5m":[65],"CMOS":[66],"process":[67],"dissipates":[68],"172.3\u00b5W":[69],"with":[70],"supply":[72],"1.8V":[74],"while":[75],"convolution.":[76],"Even":[77],"without":[78],"sizing,":[79],"writing":[81],"margin":[82],"better":[84],"than":[85],"and":[89],"accuracy":[91],"improved":[93],"by":[94],"23.2%.":[95]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
