{"id":"https://openalex.org/W2953146400","doi":"https://doi.org/10.1109/vlsi-dat.2019.8742044","title":"Cases for Analog Mixed Signal Computing Integrated Circuits for Deep Neural Networks","display_name":"Cases for Analog Mixed Signal Computing Integrated Circuits for Deep Neural Networks","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2953146400","doi":"https://doi.org/10.1109/vlsi-dat.2019.8742044","mag":"2953146400"},"language":"en","primary_location":{"id":"doi:10.1109/vlsi-dat.2019.8742044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vlsi-dat.2019.8742044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)","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/A5011887658","display_name":"Mingoo Seok","orcid":"https://orcid.org/0000-0002-9722-0979"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mingoo Seok","raw_affiliation_strings":["Columbia University"],"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056559993","display_name":"Minhao Yang","orcid":"https://orcid.org/0000-0003-1141-4818"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minhao Yang","raw_affiliation_strings":["Columbia University"],"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046317279","display_name":"Zhewei Jiang","orcid":"https://orcid.org/0000-0002-7893-9208"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhewei Jiang","raw_affiliation_strings":["Columbia University"],"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040758341","display_name":"Aurel A. Lazar","orcid":"https://orcid.org/0000-0003-4261-8709"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aurel A. Lazar","raw_affiliation_strings":["Columbia University"],"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007690955","display_name":"Jae-sun Seo","orcid":"https://orcid.org/0000-0002-4551-7789"},"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":"Jae-Sun Seo","raw_affiliation_strings":["Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5011887658"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":0.4769,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.64694345,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"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":0.9998000264167786,"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/T10363","display_name":"Low-power high-performance VLSI design","score":0.9991999864578247,"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/computer-science","display_name":"Computer science","score":0.7804056406021118},{"id":"https://openalex.org/keywords/mixed-signal-integrated-circuit","display_name":"Mixed-signal integrated circuit","score":0.6741583943367004},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.5277348756790161},{"id":"https://openalex.org/keywords/analogue-electronics","display_name":"Analogue electronics","score":0.5125858187675476},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5091432929039001},{"id":"https://openalex.org/keywords/electronic-circuit","display_name":"Electronic circuit","score":0.4951302111148834},{"id":"https://openalex.org/keywords/static-random-access-memory","display_name":"Static random-access memory","score":0.4917660057544708},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47775998711586},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45183122158050537},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4411298334598541},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.35769087076187134},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.2793640196323395},{"id":"https://openalex.org/keywords/integrated-circuit","display_name":"Integrated circuit","score":0.27894625067710876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24563932418823242},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.15289261937141418},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11845779418945312}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7804056406021118},{"id":"https://openalex.org/C62907940","wikidata":"https://www.wikidata.org/wiki/Q1541329","display_name":"Mixed-signal integrated circuit","level":3,"score":0.6741583943367004},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.5277348756790161},{"id":"https://openalex.org/C29074008","wikidata":"https://www.wikidata.org/wiki/Q174925","display_name":"Analogue electronics","level":3,"score":0.5125858187675476},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5091432929039001},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.4951302111148834},{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.4917660057544708},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47775998711586},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45183122158050537},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4411298334598541},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.35769087076187134},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.2793640196323395},{"id":"https://openalex.org/C530198007","wikidata":"https://www.wikidata.org/wiki/Q80831","display_name":"Integrated circuit","level":2,"score":0.27894625067710876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24563932418823242},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.15289261937141418},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11845779418945312},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vlsi-dat.2019.8742044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vlsi-dat.2019.8742044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)","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":0.8999999761581421}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320924","display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","ror":"https://ror.org/00yjd3n13"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2046857741","https://openalex.org/W2460688588","https://openalex.org/W2513383105","https://openalex.org/W2591601611","https://openalex.org/W2593073395","https://openalex.org/W2593197369","https://openalex.org/W2743243049","https://openalex.org/W2756683889","https://openalex.org/W2766623884","https://openalex.org/W2791524226","https://openalex.org/W2898665561","https://openalex.org/W2913050741","https://openalex.org/W2944216546"],"related_works":["https://openalex.org/W4242258007","https://openalex.org/W2155285526","https://openalex.org/W2007222089","https://openalex.org/W2394022884","https://openalex.org/W2185815555","https://openalex.org/W2071235072","https://openalex.org/W1924227955","https://openalex.org/W4242038055","https://openalex.org/W1493881961","https://openalex.org/W2375192119"],"abstract_inverted_index":{"Computing":[0],"technology":[1],"has":[2],"been":[3],"a":[4,58],"backbone":[5],"of":[6,36],"our":[7,43],"society.":[8],"Its":[9],"importance":[10,21],"is":[11],"hard":[12],"to":[13,83],"overemphasize.":[14],"Today,":[15],"we":[16,73],"again":[17],"confirm":[18],"its":[19],"extreme":[20],"with":[22],"recent":[23,91],"advances":[24],"in":[25,61,102],"deep":[26,125],"neural":[27,126],"networks.":[28,127],"Those":[29],"emerging":[30,77],"workloads":[31],"impose":[32],"an":[33],"unprecedented":[34],"amount":[35],"arithmetic":[37],"complexity":[38],"and":[39,52,79,105,108,124],"data":[40],"access":[41],"beyond":[42],"existing":[44],"computing":[45,54,64,121],"systems":[46,55],"can":[47],"barely":[48],"handle.":[49],"Particularly,":[50],"mobile":[51],"embedded":[53,113],"will":[56,74,88],"face":[57],"major":[59],"challenge":[60],"achieving":[62],"energy-efficient":[63],"for":[65,122],"truly":[66],"enabling":[67],"intelligent":[68],"systems.":[69],"In":[70],"this":[71],"talk,":[72],"discuss":[75,89],"the":[76,98,109,112],"analog":[78,104],"mixed-signal":[80],"circuit":[81],"techniques":[82],"improve":[84],"energy":[85],"efficiency.":[86],"We":[87],"two":[90],"cases":[92],"using":[93],"such":[94],"techniques,":[95],"one":[96],"on":[97,111],"speech":[99],"recognition":[100],"processor":[101],"hybrid":[103],"digital":[106],"circuits":[107,115],"other":[110],"SRAM":[114],"that":[116],"support":[117],"analog-mixed-signal":[118],"in-memory":[119],"(in-bitcell)":[120],"convolutional":[123]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}