{"id":"https://openalex.org/W3177180018","doi":"https://doi.org/10.1145/3469116.3470011","title":"Are Mobile DNN Accelerators Accelerating DNNs?","display_name":"Are Mobile DNN Accelerators Accelerating DNNs?","publication_year":2021,"publication_date":"2021-06-24","ids":{"openalex":"https://openalex.org/W3177180018","doi":"https://doi.org/10.1145/3469116.3470011","mag":"3177180018"},"language":"en","primary_location":{"id":"doi:10.1145/3469116.3470011","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469116.3470011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Workshop on Embedded and Mobile Deep Learning","raw_type":"proceedings-article"},"type":"conference-paper","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/A5076244567","display_name":"Qingqing Cao","orcid":"https://orcid.org/0000-0002-9306-0306"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qingqing Cao","raw_affiliation_strings":["Stony Brook University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stony Brook University","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087079359","display_name":"Alexandru Eugen Irimiea","orcid":"https://orcid.org/0000-0002-2864-6845"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alexandru E. Irimiea","raw_affiliation_strings":["University of Oxford"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oxford","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010814272","display_name":"Mohamed S. Abdelfattah","orcid":"https://orcid.org/0000-0002-4568-8932"},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohamed Abdelfattah","raw_affiliation_strings":["Samsung AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung AI","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048867459","display_name":"Aruna Balasubramanian","orcid":"https://orcid.org/0000-0003-3720-2215"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aruna Balasubramanian","raw_affiliation_strings":["Stony Brook University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stony Brook University","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045638679","display_name":"Nicholas D. Lane","orcid":"https://orcid.org/0000-0002-2728-8273"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]},{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Nicholas D. Lane","raw_affiliation_strings":["University of Cambridge and Samsung AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Cambridge and Samsung AI","institution_ids":["https://openalex.org/I241749","https://openalex.org/I4210101778"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9972000122070312,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9919999837875366,"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":0.85909104347229},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.7028343081474304},{"id":"https://openalex.org/keywords/mobile-processor","display_name":"Mobile processor","score":0.6742455363273621},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5833702683448792},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5779292583465576},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5292985439300537},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.4986135959625244},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.46374329924583435},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4541555941104889},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4517029821872711},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.4347476661205292},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.40550506114959717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30083543062210083},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.22901096940040588},{"id":"https://openalex.org/keywords/mobile-technology","display_name":"Mobile technology","score":0.19221025705337524},{"id":"https://openalex.org/keywords/mobile-web","display_name":"Mobile Web","score":0.18160328269004822},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.17965799570083618},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11152154207229614}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.85909104347229},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.7028343081474304},{"id":"https://openalex.org/C1665295","wikidata":"https://www.wikidata.org/wiki/Q6887219","display_name":"Mobile processor","level":5,"score":0.6742455363273621},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5833702683448792},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5779292583465576},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5292985439300537},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4986135959625244},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.46374329924583435},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4541555941104889},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4517029821872711},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.4347476661205292},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.40550506114959717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30083543062210083},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.22901096940040588},{"id":"https://openalex.org/C60952562","wikidata":"https://www.wikidata.org/wiki/Q6887246","display_name":"Mobile technology","level":3,"score":0.19221025705337524},{"id":"https://openalex.org/C516764902","wikidata":"https://www.wikidata.org/wiki/Q1043805","display_name":"Mobile Web","level":4,"score":0.18160328269004822},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.17965799570083618},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11152154207229614},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3469116.3470011","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469116.3470011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Workshop on Embedded and Mobile Deep Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8999999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1905882502","https://openalex.org/W1933349210","https://openalex.org/W2002555321","https://openalex.org/W2071879227","https://openalex.org/W2117539524","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2285660444","https://openalex.org/W2289252105","https://openalex.org/W2297325673","https://openalex.org/W2442974303","https://openalex.org/W2513554817","https://openalex.org/W2515080096","https://openalex.org/W2554197840","https://openalex.org/W2963163009","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963884515","https://openalex.org/W2970231061","https://openalex.org/W3034727271","https://openalex.org/W3105753409"],"related_works":["https://openalex.org/W2390348052","https://openalex.org/W2065566231","https://openalex.org/W3034529322","https://openalex.org/W2390600871","https://openalex.org/W2113597336","https://openalex.org/W2363399630","https://openalex.org/W2115913271","https://openalex.org/W2146894470","https://openalex.org/W2038675678","https://openalex.org/W2185570015"],"abstract_inverted_index":{"Deep":[0],"neural":[1,46,99],"networks":[2,100],"(DNNs)":[3],"are":[4,25,137],"running":[5],"on":[6,122],"many":[7,43],"mobile":[8,53,70,116,127,133],"and":[9,18,30,55,87,105,120,125],"embedded":[10],"devices":[11],"with":[12],"the":[13,40,72,85,115,143,154],"goal":[14],"of":[15,42,65,68,84,89,95],"energy":[16,88],"efficiency":[17],"highest":[19],"possible":[20],"performance.":[21],"However,":[22],"DNN":[23],"workloads":[24],"getting":[26],"more":[27],"computationally":[28],"intensive,":[29],"simultaneously":[31],"their":[32],"deployment":[33],"is":[34],"ever-increasing.":[35],"This":[36],"has":[37],"led":[38],"to":[39,48,114,141,157],"creation":[41],"purpose-built":[44],"low-power":[45],"accelerators":[47,134],"replace":[49],"or":[50],"augment":[51],"traditional":[52],"CPUs":[54],"GPUs.":[56],"In":[57],"this":[58,90],"work,":[59],"we":[60],"provide":[61,142],"an":[62],"in-depth":[63],"study":[64,83,130],"one":[66],"set":[67],"commercially-available":[69],"accelerators,":[71],"Intel":[73],"Neural":[74],"Compute":[75],"Sticks":[76],"(NCS).":[77],"We":[78,112,147],"perform":[79],"a":[80,93,123,126],"systematic":[81],"measurement":[82],"latency":[86],"accelerator":[91],"under":[92],"variety":[94],"DNNs":[96],"including":[97],"convolutional":[98],"(CNNs)":[101],"for":[102,109],"vision":[103],"tasks":[104],"attention-based":[106],"Transformer":[107],"models":[108],"NLP":[110],"tasks.":[111],"compare":[113],"processors":[117],"(CPU,":[118],"GPU,":[119],"DSP)":[121],"smartphone":[124],"board.":[128],"Our":[129],"shows":[131],"commercial":[132],"like":[135],"NCS":[136],"not":[138],"ready":[139],"yet":[140],"performance":[144],"as":[145],"claimed.":[146],"also":[148],"point":[149],"out":[150],"directions":[151],"in":[152],"optimizing":[153],"model":[155],"architectures":[156],"better":[158],"suit":[159],"these":[160],"accelerators.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
