{"id":"https://openalex.org/W3165698711","doi":"https://doi.org/10.1145/3458864.3467882","title":"nn-Meter","display_name":"nn-Meter","publication_year":2021,"publication_date":"2021-06-22","ids":{"openalex":"https://openalex.org/W3165698711","doi":"https://doi.org/10.1145/3458864.3467882","mag":"3165698711"},"language":"en","primary_location":{"id":"doi:10.1145/3458864.3467882","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3458864.3467882","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","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/A5047883479","display_name":"Li Lyna Zhang","orcid":"https://orcid.org/0000-0003-0779-8310"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Li Lyna Zhang","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062955154","display_name":"Shihao Han","orcid":null},"institutions":[{"id":"https://openalex.org/I192578771","display_name":"Rose\u2013Hulman Institute of Technology","ror":"https://ror.org/00mp6e841","country_code":"US","type":"education","lineage":["https://openalex.org/I192578771"]},{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Shihao Han","raw_affiliation_strings":["Microsoft Research and Rose-Hulman Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research and Rose-Hulman Institute of Technology","institution_ids":["https://openalex.org/I192578771","https://openalex.org/I4210124949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071351577","display_name":"Jianyu Wei","orcid":"https://orcid.org/0009-0009-0830-044X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianyu Wei","raw_affiliation_strings":["Microsoft Research and University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research and University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018118687","display_name":"Ningxin Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ningxin Zheng","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101945161","display_name":"Ting Cao","orcid":"https://orcid.org/0000-0002-7675-0882"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ting Cao","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115593321","display_name":"Yuqing Yang","orcid":"https://orcid.org/0009-0007-7325-7981"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yuqing Yang","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102880548","display_name":"Yunxin Liu","orcid":"https://orcid.org/0000-0001-7352-8955"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunxin Liu","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.0905,"has_fulltext":false,"cited_by_count":162,"citation_normalized_percentile":{"value":0.98791955,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"81","last_page":"93"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10036","display_name":"Advanced Neural Network Applications","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/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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.8359472751617432},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7750663757324219},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.7722166180610657},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.56496262550354},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.522057056427002},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5194548964500427},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.509517252445221},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4817247688770294},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.44893747568130493},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4457905888557434},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.42578592896461487},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.421461820602417},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3667060136795044},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3582109808921814},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.1088840663433075},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.08630678057670593},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07965618371963501},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07631444931030273}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8359472751617432},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7750663757324219},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.7722166180610657},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.56496262550354},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.522057056427002},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5194548964500427},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.509517252445221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4817247688770294},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.44893747568130493},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4457905888557434},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.42578592896461487},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.421461820602417},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3667060136795044},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3582109808921814},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.1088840663433075},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.08630678057670593},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07965618371963501},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07631444931030273},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3458864.3467882","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3458864.3467882","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W2147657366","https://openalex.org/W2155575073","https://openalex.org/W2295598076","https://openalex.org/W2560674852","https://openalex.org/W2766975872","https://openalex.org/W2810075754","https://openalex.org/W2897830517","https://openalex.org/W2902251695","https://openalex.org/W2903650079","https://openalex.org/W2911964244","https://openalex.org/W2949251082","https://openalex.org/W2949941638","https://openalex.org/W2961619211","https://openalex.org/W2962995671","https://openalex.org/W2963125010","https://openalex.org/W2963918968","https://openalex.org/W2964299589","https://openalex.org/W2967733054","https://openalex.org/W2975429091","https://openalex.org/W2980137827","https://openalex.org/W2994749257","https://openalex.org/W2999270366","https://openalex.org/W3035130950","https://openalex.org/W3101164610","https://openalex.org/W3102476541","https://openalex.org/W3102510044"],"related_works":["https://openalex.org/W4322761281","https://openalex.org/W4238233472","https://openalex.org/W4313526662","https://openalex.org/W4312996489","https://openalex.org/W3111395152","https://openalex.org/W3106131444","https://openalex.org/W3216099748","https://openalex.org/W4205963435","https://openalex.org/W4313463379","https://openalex.org/W3214037210"],"abstract_inverted_index":{"With":[0],"the":[1,45,88,94],"recent":[2],"trend":[3],"of":[4,33,84],"on-device":[5],"deep":[6],"learning,":[7],"inference":[8,36],"latency":[9,31,46,63,91],"has":[10],"become":[11],"a":[12,66,81],"crucial":[13],"metric":[14],"in":[15],"running":[16],"Deep":[17],"Neural":[18],"Network":[19],"(DNN)":[20],"models":[21,61],"on":[22,47,97],"various":[23],"mobile":[24],"and":[25,75],"edge":[26,99],"devices.":[27,100],"To":[28],"this":[29],"end,":[30],"prediction":[32],"DNN":[34,60],"model":[35],"is":[37,50,72],"highly":[38],"desirable":[39],"for":[40,58],"many":[41],"tasks":[42],"where":[43],"measuring":[44],"real":[48],"devices":[49],"infeasible":[51],"or":[52],"too":[53],"costly,":[54],"such":[55],"as":[56],"searching":[57],"efficient":[59],"with":[62],"constraints":[64],"from":[65],"huge":[67],"model-design":[68],"space.":[69],"Yet":[70],"it":[71],"very":[73],"challenging":[74],"existing":[76],"approaches":[77],"fail":[78],"to":[79,87],"achieve":[80],"high":[82],"accuracy":[83],"prediction,":[85],"due":[86],"varying":[89],"model-inference":[90],"caused":[92],"by":[93],"runtime":[95],"optimizations":[96],"diverse":[98]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":47},{"year":2024,"cited_by_count":35},{"year":2023,"cited_by_count":39},{"year":2022,"cited_by_count":27},{"year":2021,"cited_by_count":3}],"updated_date":"2026-06-12T08:23:45.883708","created_date":"2021-06-07T00:00:00"}
