{"id":"https://openalex.org/W4225423538","doi":"https://doi.org/10.48550/arxiv.2205.00841","title":"GPUNet: Searching the Deployable Convolution Neural Networks for GPUs","display_name":"GPUNet: Searching the Deployable Convolution Neural Networks for GPUs","publication_year":2022,"publication_date":"2022-04-26","ids":{"openalex":"https://openalex.org/W4225423538","doi":"https://doi.org/10.48550/arxiv.2205.00841"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2205.00841","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.00841","pdf_url":"https://arxiv.org/pdf/2205.00841","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2205.00841","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001397800","display_name":"Linnan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wang, Linnan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102334657","display_name":"Chenhan D. Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Chenhan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043460682","display_name":"Satish Salian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salian, Satish","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043075397","display_name":"Slawomir Kierat","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kierat, Slawomir","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031316782","display_name":"Szymon Migacz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Migacz, Szymon","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5030793031","display_name":"Alex Fit Florea","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Florea, Alex Fit","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5001397800"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.8072216510772705},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7971996068954468},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.72788006067276},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5137156248092651},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.49909305572509766},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.49761703610420227},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46399542689323425},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44017738103866577},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3964957594871521},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3708379864692688},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3359526991844177},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3341125249862671},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3225903809070587},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08737161755561829}],"concepts":[{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.8072216510772705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7971996068954468},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.72788006067276},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5137156248092651},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.49909305572509766},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.49761703610420227},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46399542689323425},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44017738103866577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3964957594871521},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3708379864692688},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3359526991844177},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3341125249862671},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3225903809070587},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08737161755561829},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2205.00841","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.00841","pdf_url":"https://arxiv.org/pdf/2205.00841","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2205.00841","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2205.00841","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2205.00841","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.00841","pdf_url":"https://arxiv.org/pdf/2205.00841","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2109940557","https://openalex.org/W2466832359","https://openalex.org/W1582019636","https://openalex.org/W1499005795","https://openalex.org/W3172493050","https://openalex.org/W4385420271","https://openalex.org/W4312192618","https://openalex.org/W2593798266","https://openalex.org/W4385414918","https://openalex.org/W2964954556"],"abstract_inverted_index":{"Customizing":[0],"Convolution":[1],"Neural":[2,39],"Networks":[3],"(CNN)":[4],"for":[5,13],"production":[6],"use":[7],"has":[8],"been":[9],"a":[10,25,49,56,84,158],"challenging":[11],"task":[12],"DL":[14,166],"practitioners.":[15],"This":[16],"paper":[17],"intends":[18],"to":[19,53,65,144,156],"expedite":[20],"the":[21,30,76],"model":[22,26],"customization":[23],"with":[24,104],"hub":[27],"that":[28,60,136,165],"contains":[29],"optimized":[31,78],"models":[32,79,171],"tiered":[33],"by":[34],"their":[35],"inference":[36,90],"latency":[37,67,91,128,162],"using":[38],"Architecture":[40],"Search":[41],"(NAS).":[42],"To":[43],"achieve":[44],"this":[45,150],"goal,":[46],"we":[47,71,74,153],"build":[48],"distributed":[50],"NAS":[51,77,138,151],"system":[52,139],"search":[54,58],"on":[55,112,122],"novel":[57],"space":[59],"consists":[61],"of":[62,132,161],"prominent":[63],"factors":[64],"impact":[66],"and":[68,92,102,115,120,129,142],"accuracy.":[69,93,107,130],"Since":[70],"target":[72],"GPU,":[73],"name":[75],"as":[80],"GPUNet,":[81],"which":[82],"establishes":[83],"new":[85],"SOTA":[86],"Pareto":[87],"frontier":[88],"in":[89,126,173],"Within":[94],"1$ms$,":[95],"GPUNet":[96,111,116,155],"is":[97,140],"2x":[98],"faster":[99],"than":[100],"EfficientNet-X":[101,119],"FBNetV3":[103,121],"even":[105],"better":[106],"We":[108],"also":[109],"validate":[110,135],"detection":[113,124],"tasks,":[114],"consistently":[117],"outperforms":[118],"COCO":[123],"tasks":[125],"both":[127],"All":[131],"these":[133],"data":[134],"our":[137,170],"effective":[141],"generic":[143],"handle":[145],"different":[146,174],"design":[147],"tasks.":[148],"With":[149],"system,":[152],"expand":[154],"cover":[157],"wide":[159],"range":[160],"targets":[163],"such":[164],"practitioners":[167],"can":[168],"deploy":[169],"directly":[172],"scenarios.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}