{"id":"https://openalex.org/W4324116704","doi":"https://doi.org/10.1109/tmc.2023.3255822","title":"NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution","display_name":"NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution","publication_year":2023,"publication_date":"2023-03-13","ids":{"openalex":"https://openalex.org/W4324116704","doi":"https://doi.org/10.1109/tmc.2023.3255822"},"language":"en","primary_location":{"id":"doi:10.1109/tmc.2023.3255822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2023.3255822","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Mobile Computing","raw_type":"journal-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/A5033442931","display_name":"Stylianos I. Venieris","orcid":"https://orcid.org/0000-0001-5181-6251"},"institutions":[{"id":"https://openalex.org/I4210117523","display_name":"Samsung (United Kingdom)","ror":"https://ror.org/01w6gjq94","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210117523"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Stylianos I. Venieris","raw_affiliation_strings":["Samsung AI Center, Cambridge, U.K"],"raw_orcid":"https://orcid.org/0000-0001-5181-6251","affiliations":[{"raw_affiliation_string":"Samsung AI Center, Cambridge, U.K","institution_ids":["https://openalex.org/I4210117523"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062180957","display_name":"Mario Almeida","orcid":"https://orcid.org/0000-0002-5394-5951"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mario Almeida","raw_affiliation_strings":["Rain Instant Pay, Nashville, TN, USA"],"raw_orcid":"https://orcid.org/0000-0002-5394-5951","affiliations":[{"raw_affiliation_string":"Rain Instant Pay, Nashville, TN, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026267258","display_name":"Royson Lee","orcid":"https://orcid.org/0000-0002-6716-7994"},"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/I4210117523","display_name":"Samsung (United Kingdom)","ror":"https://ror.org/01w6gjq94","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210117523"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Royson Lee","raw_affiliation_strings":["University of Cambridge, Cambridge, U.K","Samsung AI Center, Cambridge, U.K"],"raw_orcid":"https://orcid.org/0000-0002-6716-7994","affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, U.K","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"Samsung AI Center, Cambridge, U.K","institution_ids":["https://openalex.org/I4210117523"]}]},{"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/I4210117523","display_name":"Samsung (United Kingdom)","ror":"https://ror.org/01w6gjq94","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210117523"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nicholas D. Lane","raw_affiliation_strings":["University of Cambridge, Cambridge, U.K","Samsung AI Center, Cambridge, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, U.K","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"Samsung AI Center, Cambridge, U.K","institution_ids":["https://openalex.org/I4210117523"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9573,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.76503762,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"23","issue":"3","first_page":"2367","last_page":"2381"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9994000196456909,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9994000196456909,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9939000010490417,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.859607458114624},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.8002278804779053},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.667209267616272},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.6155223846435547},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.464909166097641},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4586484730243683},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.44353336095809937},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4433099925518036},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.434908926486969},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36854174733161926},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3499237895011902},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3221451938152313},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.214432030916214},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.18019583821296692},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1476224660873413},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10922670364379883}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.859607458114624},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.8002278804779053},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.667209267616272},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.6155223846435547},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.464909166097641},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4586484730243683},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.44353336095809937},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4433099925518036},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.434908926486969},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36854174733161926},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3499237895011902},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3221451938152313},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.214432030916214},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.18019583821296692},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1476224660873413},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10922670364379883}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmc.2023.3255822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2023.3255822","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":75,"referenced_works":["https://openalex.org/W1559215823","https://openalex.org/W1861537833","https://openalex.org/W1885185971","https://openalex.org/W1930824406","https://openalex.org/W1970200030","https://openalex.org/W1976944900","https://openalex.org/W2024060531","https://openalex.org/W2047920195","https://openalex.org/W2087264502","https://openalex.org/W2121058967","https://openalex.org/W2121927366","https://openalex.org/W2133665775","https://openalex.org/W2160561682","https://openalex.org/W2476548250","https://openalex.org/W2555248751","https://openalex.org/W2616014673","https://openalex.org/W2739757502","https://openalex.org/W2768814045","https://openalex.org/W2795024892","https://openalex.org/W2803549871","https://openalex.org/W2866634454","https://openalex.org/W2883780447","https://openalex.org/W2891158090","https://openalex.org/W2911581663","https://openalex.org/W2915364523","https://openalex.org/W2916004337","https://openalex.org/W2921967969","https://openalex.org/W2931743911","https://openalex.org/W2945856475","https://openalex.org/W2962890454","https://openalex.org/W2963122961","https://openalex.org/W2963125010","https://openalex.org/W2963372104","https://openalex.org/W2963645458","https://openalex.org/W2965032453","https://openalex.org/W2971002981","https://openalex.org/W2971595222","https://openalex.org/W2976718572","https://openalex.org/W2982041622","https://openalex.org/W2982479999","https://openalex.org/W2997884640","https://openalex.org/W2998506323","https://openalex.org/W2999276659","https://openalex.org/W3015391117","https://openalex.org/W3034938110","https://openalex.org/W3035302306","https://openalex.org/W3040522390","https://openalex.org/W3046761316","https://openalex.org/W3047589404","https://openalex.org/W3087814885","https://openalex.org/W3089138886","https://openalex.org/W3096641820","https://openalex.org/W3098418424","https://openalex.org/W3100741579","https://openalex.org/W3105888187","https://openalex.org/W3106656598","https://openalex.org/W3107781032","https://openalex.org/W3110378228","https://openalex.org/W3139549852","https://openalex.org/W3163767593","https://openalex.org/W3173515979","https://openalex.org/W3177328703","https://openalex.org/W3190761184","https://openalex.org/W3201845268","https://openalex.org/W3206412810","https://openalex.org/W3210764291","https://openalex.org/W4297775537","https://openalex.org/W6737664043","https://openalex.org/W6751349269","https://openalex.org/W6754887999","https://openalex.org/W6756040472","https://openalex.org/W6770425567","https://openalex.org/W6784110152","https://openalex.org/W6795991173","https://openalex.org/W6838398888"],"related_works":["https://openalex.org/W4221139464","https://openalex.org/W4289827464","https://openalex.org/W2928062709","https://openalex.org/W3183118997","https://openalex.org/W3214410901","https://openalex.org/W3204400881","https://openalex.org/W3204296682","https://openalex.org/W2917767146","https://openalex.org/W2929170389","https://openalex.org/W2748428003"],"abstract_inverted_index":{"In":[0],"recent":[1,54],"years,":[2],"image":[3,104],"and":[4,50,100,167,182,197],"video":[5],"delivery":[6],"systems":[7,61,174],"have":[8],"begun":[9],"integrating":[10],"deep":[11],"learning":[12],"super-resolution":[13],"(SR)":[14],"approaches,":[15],"leveraging":[16],"their":[17],"unprecedented":[18],"visual":[19,64,146,217],"enhancement":[20],"capabilities":[21,110],"while":[22,120],"reducing":[23],"reliance":[24],"on":[25,32,56,153,216],"networking":[26],"conditions.":[27],"Nevertheless,":[28],"deploying":[29],"these":[30],"solutions":[31],"mobile":[33,113],"devices":[34],"still":[35],"remains":[36],"an":[37,161,192],"active":[38],"challenge":[39],"as":[40],"SR":[41,58,92,138,173],"models":[42],"are":[43],"excessively":[44],"demanding":[45],"with":[46,141],"respect":[47],"to":[48,67,117,135],"workload":[49],"memory":[51],"footprint.":[52],"Despite":[53],"progress":[55],"on-device":[57,89,172],"frameworks,":[59],"existing":[60],"either":[62],"penalize":[63],"quality,":[65,218],"lead":[66],"excessive":[68],"energy":[69],"consumption":[70],"or":[71],"make":[72],"inefficient":[73],"use":[74,176],"of":[75,91,111,164,194,214,227],"the":[76,87,108,129,137,170,211,224],"available":[77],"resources.":[78],"This":[79],"work":[80],"presents":[81],"NAWQ-SR,":[82],"a":[83,95,101,220],"novel":[84,96],"framework":[85],"for":[86],"efficient":[88],"execution":[90],"models.":[93],"Through":[94],"hybrid-precision":[97],"quantization":[98,215],"technique":[99],"runtime":[102],"neural":[103],"codec,":[105],"NAWQ-SR":[106,126,159,190],"exploits":[107],"multi-precision":[109],"modern":[112],"NPUs":[114],"in":[115,223],"order":[116],"minimize":[118],"latency,":[119],"meeting":[121],"user-specified":[122],"quality":[123,147,226],"constraints.":[124],"Moreover,":[125],"selectively":[127],"adapts":[128],"arithmetic":[130],"precision":[131],"at":[132],"run":[133],"time":[134],"equip":[136],"DNN's":[139],"layers":[140],"wider":[142],"representational":[143],"power,":[144],"improving":[145],"beyond":[148],"what":[149],"was":[150],"previously":[151],"possible":[152],"NPUs.":[154],"<styled-content":[155,186],"style=\"color:#000000\"":[156,187],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[157,188],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Altogether,":[158],"achieves":[160],"average":[162,193],"speedup":[163,196],"7.9\u00d7,":[165],"3\u00d7":[166],"1.91\u00d7":[168],"over":[169,202],"state-of-the-art":[171,222],"that":[175],"heterogeneous":[177],"processors":[178],"(MobiSR),":[179],"CPU":[180],"(SplitSR)":[181],"NPU":[183,205],"(XLSR),":[184],"respectively.</styled-content>":[185],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Furthermore,":[189],"delivers":[191],"3.2\u00d7":[195],"0.39":[198],"dB":[199],"higher":[200],"PSNR":[201],"status-quo":[203],"INT8":[204],"designs,":[206],"but":[207],"most":[208],"importantly":[209],"mitigates":[210],"negative":[212],"effects":[213],"setting":[219],"new":[221],"attainable":[225],"NPU-based":[228],"SR.</styled-content>":[229]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}