{"id":"https://openalex.org/W2793168176","doi":"https://doi.org/10.1109/isscc.2018.8310264","title":"An always-on 3.8\u03bcJ/86% CIFAR-10 mixed-signal binary CNN processor with all memory on chip in 28nm CMOS","display_name":"An always-on 3.8\u03bcJ/86% CIFAR-10 mixed-signal binary CNN processor with all memory on chip in 28nm CMOS","publication_year":2018,"publication_date":"2018-02-01","ids":{"openalex":"https://openalex.org/W2793168176","doi":"https://doi.org/10.1109/isscc.2018.8310264","mag":"2793168176"},"language":"en","primary_location":{"id":"doi:10.1109/isscc.2018.8310264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isscc.2018.8310264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Solid - State Circuits Conference - (ISSCC)","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/A5011350393","display_name":"Daniel Bankman","orcid":"https://orcid.org/0000-0002-0327-1813"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Daniel Bankman","raw_affiliation_strings":["Stantord University, Stanford, CA"],"affiliations":[{"raw_affiliation_string":"Stantord University, Stanford, CA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025506278","display_name":"Lita Yang","orcid":"https://orcid.org/0000-0001-6684-7069"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lita Yang","raw_affiliation_strings":["Stantord University, Stanford, CA"],"affiliations":[{"raw_affiliation_string":"Stantord University, Stanford, CA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061910461","display_name":"Bert Moons","orcid":"https://orcid.org/0000-0002-0136-8232"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Bert Moons","raw_affiliation_strings":["KU Leuven, Leuven, Belgium"],"affiliations":[{"raw_affiliation_string":"KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012150553","display_name":"Marian Verhelst","orcid":"https://orcid.org/0000-0003-3495-9263"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Marian Verhelst","raw_affiliation_strings":["KU Leuven, Leuven, Belgium"],"affiliations":[{"raw_affiliation_string":"KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029806914","display_name":"Boris Murmann","orcid":"https://orcid.org/0000-0003-3417-8782"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boris Murmann","raw_affiliation_strings":["Stantord University, Stanford, CA"],"affiliations":[{"raw_affiliation_string":"Stantord University, Stanford, CA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5011350393"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":18.9707,"has_fulltext":false,"cited_by_count":165,"citation_normalized_percentile":{"value":0.99552839,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"222","last_page":"224"},"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":0.9994999766349792,"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":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8303394317626953},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6408384442329407},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.5794947743415833},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5353842973709106},{"id":"https://openalex.org/keywords/dataflow","display_name":"Dataflow","score":0.5138802528381348},{"id":"https://openalex.org/keywords/memory-bandwidth","display_name":"Memory bandwidth","score":0.5038394331932068},{"id":"https://openalex.org/keywords/dram","display_name":"Dram","score":0.48587673902511597},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44697439670562744},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3848823606967926},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.340675413608551},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2730695605278015}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8303394317626953},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6408384442329407},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.5794947743415833},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5353842973709106},{"id":"https://openalex.org/C96324660","wikidata":"https://www.wikidata.org/wiki/Q205446","display_name":"Dataflow","level":2,"score":0.5138802528381348},{"id":"https://openalex.org/C188045654","wikidata":"https://www.wikidata.org/wiki/Q17148339","display_name":"Memory bandwidth","level":2,"score":0.5038394331932068},{"id":"https://openalex.org/C7366592","wikidata":"https://www.wikidata.org/wiki/Q1255620","display_name":"Dram","level":2,"score":0.48587673902511597},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44697439670562744},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3848823606967926},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.340675413608551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2730695605278015}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isscc.2018.8310264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isscc.2018.8310264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Solid - State Circuits Conference - (ISSCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8899999856948853,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2289252105","https://openalex.org/W2314470091","https://openalex.org/W2319920447","https://openalex.org/W2527492855","https://openalex.org/W2745228312","https://openalex.org/W3024621361","https://openalex.org/W6727867346"],"related_works":["https://openalex.org/W2950475743","https://openalex.org/W4386603768","https://openalex.org/W2886711096","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W2590796488","https://openalex.org/W4389249638","https://openalex.org/W2734358244","https://openalex.org/W4388700941","https://openalex.org/W2293118914"],"abstract_inverted_index":{"The":[0,28],"trend":[1],"of":[2,13,86,101,148],"pushing":[3],"deep":[4,23],"learning":[5],"from":[6],"cloud":[7],"to":[8,11,39,69,96,124],"edge":[9,63],"due":[10,68],"concerns":[12],"latency,":[14],"bandwidth,":[15],"and":[16,92,121,132,157],"privacy":[17],"has":[18],"created":[19],"demand":[20],"for":[21,54,117],"low-energy":[22],"convolutional":[24],"neural":[25],"networks":[26],"(CNNs).":[27],"single-layer":[29],"classifier":[30],"in":[31],"[1]":[32],"achieves":[33],"sub-nJ":[34],"operation,":[35],"but":[36,62],"is":[37],"limited":[38],"moderate":[40,87],"accuracy":[41],"on":[42,46,90],"low-complexity":[43],"tasks":[44,56],"(90%":[45],"MNIST).":[47],"Larger":[48],"CNN":[49,80],"chips":[50],"provide":[51],"dataflow":[52],"computing":[53,95],"high-complexity":[55],"(AlexNet)":[57],"at":[58],"mJ":[59],"energy":[60,100],"[2],":[61],"deployment":[64],"remains":[65],"a":[66,77,98,103],"challenge":[67,147],"off-chip":[70],"DRAM":[71],"access":[72],"energy.":[73],"This":[74],"paper":[75],"describes":[76],"mixed-signal":[78],"binary":[79],"processor":[81],"that":[82,144],"performs":[83],"image":[84],"classification":[85,99],"complexity":[88],"(86%":[89],"CIFAR-10)":[91],"employs":[93],"near-memory":[94],"achieve":[97],"3.8\u03bcJ,":[102],"40\u00d7":[104],"improvement":[105],"over":[106],"TrueNorth":[107],"[3].":[108],"We":[109],"accomplish":[110],"this":[111],"using":[112],"(1)":[113],"the":[114],"BinaryNet":[115],"algorithm":[116],"CNNs":[118],"with":[119],"weights":[120],"activations":[122],"constrained":[123],"+1/-1":[125],"[4],":[126],"which":[127],"drastically":[128],"simplifies":[129],"multiplications":[130],"(XNOR)":[131],"allows":[133],"integrating":[134],"all":[135],"memory":[136],"on-chip;":[137],"(2)":[138],"an":[139],"energy-efficient":[140],"switched-capacitor":[141],"(SC)":[142],"neuron":[143],"addresses":[145],"BinaryNet's":[146],"wide":[149],"vector":[150],"summation;":[151],"(3)":[152],"architectural":[153],"parallelism,":[154],"parameter":[155],"reuse,":[156],"locality.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":33},{"year":2020,"cited_by_count":48},{"year":2019,"cited_by_count":43},{"year":2018,"cited_by_count":21}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
