{"id":"https://openalex.org/W4380489077","doi":"https://doi.org/10.1145/3589610.3596284","title":"Synchronization-Aware NAS for an Efficient Collaborative Inference on Mobile Platforms","display_name":"Synchronization-Aware NAS for an Efficient Collaborative Inference on Mobile Platforms","publication_year":2023,"publication_date":"2023-06-13","ids":{"openalex":"https://openalex.org/W4380489077","doi":"https://doi.org/10.1145/3589610.3596284"},"language":"en","primary_location":{"id":"doi:10.1145/3589610.3596284","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589610.3596284","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems","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/A5007460665","display_name":"Beom Woo Kang","orcid":"https://orcid.org/0000-0001-7502-163X"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Beom Woo Kang","raw_affiliation_strings":["Hanyang University, South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092156353","display_name":"Junho Wohn","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junho Wohn","raw_affiliation_strings":["Hanyang University, South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102947768","display_name":"Seongju Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seongju Lee","raw_affiliation_strings":["Hanyang University, South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102806371","display_name":"Sunghyun Park","orcid":"https://orcid.org/0009-0006-1056-2826"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sunghyun Park","raw_affiliation_strings":["University of Michigan, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021287644","display_name":"Yung\u2010Kyun Noh","orcid":"https://orcid.org/0000-0002-6372-9267"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]},{"id":"https://openalex.org/I125608817","display_name":"Korea Institute for Advanced Study","ror":"https://ror.org/041hz9568","country_code":"KR","type":"facility","lineage":["https://openalex.org/I125608817"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yung-Kyun Noh","raw_affiliation_strings":["Hanyang University, South Korea / Korea Institute for Advanced Study, South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University, South Korea / Korea Institute for Advanced Study, South Korea","institution_ids":["https://openalex.org/I125608817","https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086980677","display_name":"Yongjun Park","orcid":"https://orcid.org/0000-0003-3725-0380"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongjun Park","raw_affiliation_strings":["Yonsei University, South Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University, South Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5007460665"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":null,"apc_paid":null,"fwci":0.1194,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.38386145,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9983999729156494,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9965999722480774,"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":0.8564529418945312},{"id":"https://openalex.org/keywords/synchronization","display_name":"Synchronization (alternating current)","score":0.6396322846412659},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5642593502998352},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5547008514404297},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.551862895488739},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5444887280464172},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.4903688430786133},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43347927927970886},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3589988946914673},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3021736741065979},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.19369179010391235},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10877570509910583}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8564529418945312},{"id":"https://openalex.org/C2778562939","wikidata":"https://www.wikidata.org/wiki/Q1298791","display_name":"Synchronization (alternating current)","level":3,"score":0.6396322846412659},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5642593502998352},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5547008514404297},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.551862895488739},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5444887280464172},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.4903688430786133},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43347927927970886},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3589988946914673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3021736741065979},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.19369179010391235},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10877570509910583},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","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},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589610.3596284","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589610.3596284","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G2026054926","display_name":null,"funder_award_id":"2021R1C1C1011613","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G8817798873","display_name":null,"funder_award_id":"2021-0-00310","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1625390266","https://openalex.org/W1971713783","https://openalex.org/W2020135152","https://openalex.org/W2108598243","https://openalex.org/W2126316555","https://openalex.org/W2194775991","https://openalex.org/W2396961959","https://openalex.org/W2605258629","https://openalex.org/W2612193523","https://openalex.org/W2789758093","https://openalex.org/W2799197246","https://openalex.org/W2804815240","https://openalex.org/W2808938483","https://openalex.org/W2883780447","https://openalex.org/W2886851211","https://openalex.org/W2896180420","https://openalex.org/W2931092525","https://openalex.org/W2931743911","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963918968","https://openalex.org/W2964081807","https://openalex.org/W2965658867","https://openalex.org/W2967733054","https://openalex.org/W2982083293","https://openalex.org/W2983440318","https://openalex.org/W2996874060","https://openalex.org/W2999803881","https://openalex.org/W3015362971","https://openalex.org/W3037543177","https://openalex.org/W3041133507","https://openalex.org/W3092334294","https://openalex.org/W3104849992","https://openalex.org/W3109946440","https://openalex.org/W3149839747","https://openalex.org/W3162668736","https://openalex.org/W3166225737","https://openalex.org/W3168298428","https://openalex.org/W3204336764","https://openalex.org/W4206914189","https://openalex.org/W4249932213","https://openalex.org/W4287715829","https://openalex.org/W4380489077","https://openalex.org/W6712451147","https://openalex.org/W6786080308"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W3128807919","https://openalex.org/W3176411177"],"abstract_inverted_index":{"Previous":[0],"neural":[1,17,114],"architecture":[2],"search":[3,131,141,152,204],"(NAS)":[4],"approaches":[5],"for":[6,73,93,112,133,212],"mobile":[7,37,81],"platforms":[8],"have":[9],"achieved":[10],"great":[11],"success":[12],"in":[13,210],"designing":[14],"a":[15,24,30,80,124,129],"slim-but-accurate":[16],"network":[18],"that":[19,116],"is":[20,49,86],"generally":[21],"well-matched":[22],"to":[23,50,87,105,144,178,190,208],"single":[25],"computing":[26,43,121],"unit":[27],"such":[28],"as":[29,35],"CPU":[31],"or":[32],"GPU.":[33],"However,":[34],"recent":[36],"devices":[38],"consist":[39],"of":[40,109,119,199],"multiple":[41,59],"heterogeneous":[42,120],"units,":[44],"the":[45,89,107,146,151,168,173,191,213],"next":[46],"main":[47,84],"challenge":[48,85],"maximize":[51,117],"both":[52,95],"accuracy":[53,165,184],"and":[54,97,136,149,194],"efficiency":[55,148],"by":[56,206],"fully":[57],"utilizing":[58],"available":[60],"resources.":[61],"We":[62,127],"propose":[63,103],"an":[64,197],"ensemble-like":[65],"approach":[66],"with":[67],"intermediate":[68],"feature":[69],"aggregations,":[70],"namely":[71],"synchronizations,":[72],"active":[74],"collaboration":[75],"between":[76],"individual":[77],"models":[78],"on":[79,123,160],"device.":[82,126],"A":[83],"determine":[88],"optimal":[90,214],"synchronization":[91,110,134],"strategies":[92,111],"achieving":[94],"performance":[96],"efficiency.":[98],"To":[99],"this":[100],"end,":[101],"we":[102],"SyncNAS":[104,201],"automate":[106],"exploration":[108],"collaborative":[113,157],"architectures":[115],"utilization":[118,193],"units":[122],"target":[125,175],"introduce":[128],"novel":[130],"space":[132],"strategy":[135],"apply":[137],"Monte":[138],"Carlo":[139],"tree":[140],"(MCTS)":[142],"algorithm":[143],"improve":[145],"sampling":[147],"reduce":[150],"cost.":[153],"On":[154],"ImageNet,":[155],"our":[156,180],"model":[158,181],"based":[159],"MobileNetV2":[161],"achieves":[162],"2.7%":[163],"top-1":[164],"improvement":[166],"within":[167],"baseline":[169,187],"latency":[170,176],"budget.":[171],"Under":[172],"reduced":[174],"down":[177],"half,":[179],"maintains":[182],"higher":[183],"than":[185],"its":[186,203],"model,":[188],"owing":[189],"enhanced":[192],"collaboration.":[195],"As":[196],"impact":[198],"MCTS,":[200],"reduces":[202],"cost":[205],"up":[207],"21x":[209],"searching":[211],"strategy.":[215]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
