{"id":"https://openalex.org/W4220917304","doi":"https://doi.org/10.1145/3529706.3529712","title":"nn-METER","display_name":"nn-METER","publication_year":2022,"publication_date":"2022-03-30","ids":{"openalex":"https://openalex.org/W4220917304","doi":"https://doi.org/10.1145/3529706.3529712"},"language":"en","primary_location":{"id":"doi:10.1145/3529706.3529712","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3529706.3529712","pdf_url":null,"source":{"id":"https://openalex.org/S4210227886","display_name":"GetMobile Mobile Computing and Communications","issn_l":"2375-0529","issn":["2375-0529","2375-0537"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GetMobile: Mobile Computing and Communications","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/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":true,"raw_author_name":"Li Lyna Zhang","raw_affiliation_strings":["Microsoft Research"],"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, Rose-Hulman Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, 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, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, 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"],"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"],"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":["Institute for AI Industry Research (AIR), Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Institute for AI Industry Research (AIR), Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5047883479"],"corresponding_institution_ids":["https://openalex.org/I4210164937"],"apc_list":null,"apc_paid":null,"fwci":0.403,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.57400574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"25","issue":"4","first_page":"19","last_page":"23"},"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":0.9968000054359436,"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/T13553","display_name":"Age of Information Optimization","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.7959923148155212},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7703834772109985},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.6762640476226807},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5271967053413391},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5037519335746765},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5026068687438965},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.47331130504608154},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4286581873893738},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4279767870903015},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3721098303794861},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32405465841293335},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11914753913879395},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.11734557151794434},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.08020803332328796}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7959923148155212},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7703834772109985},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.6762640476226807},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5271967053413391},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5037519335746765},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5026068687438965},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.47331130504608154},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4286581873893738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4279767870903015},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3721098303794861},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32405465841293335},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11914753913879395},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.11734557151794434},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.08020803332328796},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3529706.3529712","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3529706.3529712","pdf_url":null,"source":{"id":"https://openalex.org/S4210227886","display_name":"GetMobile Mobile Computing and Communications","issn_l":"2375-0529","issn":["2375-0529","2375-0537"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GetMobile: Mobile Computing and Communications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W2886851211","https://openalex.org/W2903650079","https://openalex.org/W2967733054","https://openalex.org/W6600336938"],"related_works":["https://openalex.org/W2752178021","https://openalex.org/W2973622361","https://openalex.org/W3176282186","https://openalex.org/W4387489555","https://openalex.org/W3185576471","https://openalex.org/W4288024917","https://openalex.org/W4293053895","https://openalex.org/W2983364019","https://openalex.org/W2998183476","https://openalex.org/W3215372595"],"abstract_inverted_index":{"Inference":[0],"latency":[1,23,37,67,96,169],"has":[2],"become":[3],"a":[4,57,85,108,119,144,162],"crucial":[5],"metric":[6],"in":[7],"running":[8],"Deep":[9],"Neural":[10],"Network":[11],"(DNN)":[12],"models":[13],"on":[14,38,73,97,118,177],"various":[15],"mobile":[16],"and":[17,51,82,87,121,150],"edge":[18,75,99,181],"devices.":[19,76,100,182],"To":[20],"this":[21,78],"end,":[22],"prediction":[24,175],"of":[25,60,104,140,146,180],"DNN":[26,94],"inference":[27,95,111,142],"is":[28,41,48,106],"highly":[29],"desirable":[30],"for":[31],"many":[32],"tasks":[33],"where":[34],"measuring":[35],"the":[36,64,70,93,115,137,157],"real":[39],"devices":[40],"infeasible":[42],"or":[43],"too":[44],"costly.":[45],"Yet":[46],"it":[47],"very":[49],"challenging":[50],"existing":[52],"approaches":[53],"fail":[54],"to":[55,63,90,134,154,165],"achieve":[56],"high":[58,174],"accuracy":[59,176],"prediction,":[61],"due":[62],"varying":[65],"model-inference":[66],"caused":[68],"by":[69],"runtime":[71],"optimizations":[72],"diverse":[74,98],"In":[77],"paper,":[79],"we":[80],"propose":[81],"develop":[83],"nn-Meter,":[84],"novel":[86],"efficient":[88],"system":[89],"accurately":[91],"predict":[92],"The":[101],"key":[102,129],"idea":[103],"nn-Meter":[105,125,171],"dividing":[107],"whole":[109],"model":[110,141],"into":[112],"kernels,":[113],"i.e.,":[114],"execution":[116,138],"units":[117],"device,":[120],"conducting":[122],"kernel-level":[123,168],"prediction.":[124],"builds":[126],"atop":[127],"two":[128],"techniques:":[130],"(i)":[131],"kernel":[132],"detection":[133],"automatically":[135],"detect":[136],"unit":[139],"via":[143],"set":[145],"well-designed":[147],"test":[148],"cases;":[149],"(ii)":[151],"adaptive":[152],"sampling":[153],"efficiently":[155],"sample":[156],"most":[158],"beneficial":[159],"configurations":[160],"from":[161],"large":[163],"space":[164],"build":[166],"accurate":[167],"predictors.":[170],"achieves":[172],"significant":[173],"four":[178],"types":[179]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-04-03T00:00:00"}
