{"id":"https://openalex.org/W4360831858","doi":"https://doi.org/10.1109/hpca56546.2023.10070935","title":"eNODE: Energy-Efficient and Low-Latency Edge Inference and Training of Neural ODEs","display_name":"eNODE: Energy-Efficient and Low-Latency Edge Inference and Training of Neural ODEs","publication_year":2023,"publication_date":"2023-02-01","ids":{"openalex":"https://openalex.org/W4360831858","doi":"https://doi.org/10.1109/hpca56546.2023.10070935"},"language":"en","primary_location":{"id":"doi:10.1109/hpca56546.2023.10070935","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/hpca56546.2023.10070935","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA)","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/A5023769380","display_name":"Junkang Zhu","orcid":"https://orcid.org/0000-0002-4296-1358"},"institutions":[{"id":"https://openalex.org/I4210140958","display_name":"Ann Arbor Center for Independent Living","ror":"https://ror.org/045pcya52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140958"]},{"id":"https://openalex.org/I4210114445","display_name":"Michigan Medicine","ror":"https://ror.org/01zcpa714","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210114445"]},{"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":true,"raw_author_name":"Junkang Zhu","raw_affiliation_strings":["University of Michigan, Ann Arbor,Ann Arbor,Michigan,USA","University of Michigan, Ann Arbor, Ann Arbor, Michigan, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor,Ann Arbor,Michigan,USA","institution_ids":["https://openalex.org/I27837315","https://openalex.org/I4210140958","https://openalex.org/I4210114445"]},{"raw_affiliation_string":"University of Michigan, Ann Arbor, Ann Arbor, Michigan, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072208883","display_name":"Yaoyu Tao","orcid":"https://orcid.org/0000-0001-7500-5250"},"institutions":[{"id":"https://openalex.org/I4210140958","display_name":"Ann Arbor Center for Independent Living","ror":"https://ror.org/045pcya52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140958"]},{"id":"https://openalex.org/I4210114445","display_name":"Michigan Medicine","ror":"https://ror.org/01zcpa714","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210114445"]},{"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":"Yaoyu Tao","raw_affiliation_strings":["University of Michigan, Ann Arbor,Ann Arbor,Michigan,USA","University of Michigan, Ann Arbor, Ann Arbor, Michigan, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor,Ann Arbor,Michigan,USA","institution_ids":["https://openalex.org/I27837315","https://openalex.org/I4210140958","https://openalex.org/I4210114445"]},{"raw_affiliation_string":"University of Michigan, Ann Arbor, Ann Arbor, Michigan, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038110244","display_name":"Zhengya Zhang","orcid":"https://orcid.org/0000-0001-5963-9018"},"institutions":[{"id":"https://openalex.org/I4210140958","display_name":"Ann Arbor Center for Independent Living","ror":"https://ror.org/045pcya52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140958"]},{"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"]},{"id":"https://openalex.org/I4210114445","display_name":"Michigan Medicine","ror":"https://ror.org/01zcpa714","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210114445"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengya Zhang","raw_affiliation_strings":["University of Michigan, Ann Arbor,Ann Arbor,Michigan,USA","University of Michigan, Ann Arbor, Ann Arbor, Michigan, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor,Ann Arbor,Michigan,USA","institution_ids":["https://openalex.org/I27837315","https://openalex.org/I4210140958","https://openalex.org/I4210114445"]},{"raw_affiliation_string":"University of Michigan, Ann Arbor, Ann Arbor, Michigan, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5023769380"],"corresponding_institution_ids":["https://openalex.org/I27837315","https://openalex.org/I4210114445","https://openalex.org/I4210140958"],"apc_list":null,"apc_paid":null,"fwci":0.4997,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58333749,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"802","last_page":"813"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9914000034332275,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9751999974250793,"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":0.7678935527801514},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.592258095741272},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5865101218223572},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5369965434074402},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5025253295898438},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5021178722381592},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4630774259567261},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4543357491493225},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.44701871275901794},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3679562509059906},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.35250234603881836},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.33313360810279846},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3251459002494812},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.2524600028991699},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23912060260772705},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10967251658439636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7678935527801514},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.592258095741272},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5865101218223572},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5369965434074402},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5025253295898438},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5021178722381592},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4630774259567261},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4543357491493225},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.44701871275901794},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3679562509059906},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.35250234603881836},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.33313360810279846},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3251459002494812},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.2524600028991699},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23912060260772705},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10967251658439636},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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:10.1109/hpca56546.2023.10070935","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/hpca56546.2023.10070935","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W768639568","https://openalex.org/W1979395357","https://openalex.org/W1993166169","https://openalex.org/W1998583908","https://openalex.org/W2007339694","https://openalex.org/W2034861439","https://openalex.org/W2061011338","https://openalex.org/W2194775991","https://openalex.org/W2302255633","https://openalex.org/W2559655401","https://openalex.org/W2593564159","https://openalex.org/W2921126577","https://openalex.org/W2962737770","https://openalex.org/W2963163009","https://openalex.org/W2963359731","https://openalex.org/W2963446712","https://openalex.org/W2964137095","https://openalex.org/W2965543245","https://openalex.org/W2999905431","https://openalex.org/W3046996896","https://openalex.org/W3183954477","https://openalex.org/W3204999877","https://openalex.org/W4240805545","https://openalex.org/W4249932213","https://openalex.org/W6729059855","https://openalex.org/W6731278065","https://openalex.org/W6734171162","https://openalex.org/W6747381837","https://openalex.org/W6752307458","https://openalex.org/W6760979436","https://openalex.org/W6768936351","https://openalex.org/W6774419874","https://openalex.org/W6779009413","https://openalex.org/W6779570212","https://openalex.org/W6781004505","https://openalex.org/W6790121894","https://openalex.org/W6973559833"],"related_works":["https://openalex.org/W2058965144","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":{"Neural":[0],"ordinary":[1,24],"differential":[2,25],"equations":[3,26],"(NODEs)":[4],"provide":[5],"better":[6,186,193],"modeling":[7],"performance":[8],"with":[9,158],"smaller":[10],"amount":[11],"of":[12,113,140],"model":[13],"parameters":[14],"in":[15,23,34,171],"many":[16],"tasks":[17],"by":[18,56,102],"embedding":[19],"neural":[20],"networks":[21],"(NNs)":[22],"(ODEs).":[27],"They":[28],"have":[29,64],"been":[30],"shown":[31],"to":[32,93,105,161,184],"outperform":[33],"representing":[35],"continuous-time":[36],"data":[37],"and":[38,42,48,58,61,78,82,87,89,108,111,120,132,155,179,192],"learning":[39],"dynamic":[40,95],"systems,":[41],"are":[43,72],"promising":[44],"for":[45,75,84,123,177],"on-device":[46],"inference":[47,86,110],"training.":[49],"However,":[50],"an":[51],"edge":[52],"device":[53],"is":[54,144,169],"limited":[55],"area":[57,194],"energy":[59,125,187],"budget,":[60],"real-time":[62],"operations":[63],"a":[65,133,172,197],"tight":[66],"latency":[67,96],"requirement.":[68],"State-of-the-art":[69],"NN":[70,135],"accelerators":[71],"not":[73],"optimized":[74],"the":[76,91,138,164],"area-":[77],"power-hungry":[79],"memory":[80],"storage":[81],"access":[83],"NODE":[85],"training,":[88],"lack":[90],"flexibility":[92],"incorporate":[94],"reduction":[97],"techniques.":[98],"We":[99,147],"present":[100],"eNODE":[101,115,181],"architecture-algorithm":[103],"co-design":[104],"achieve":[106],"efficient":[107],"fast":[109],"training":[112,122],"NODEs.":[114],"adopts":[116],"compact-size":[117],"depth-first":[118,121,142],"integration":[119],"higher":[124,190],"efficiency.":[126],"Through":[127],"function":[128],"reuse,":[129],"packetized":[130],"processing":[131,143,157],"unified":[134],"core":[136],"design,":[137],"efficiency":[139],"eNODE\u2019s":[141],"further":[145],"enhanced.":[146],"propose":[148],"algorithm":[149],"innovations,":[150],"including":[151],"slope-adaptive":[152],"stepsize":[153],"search":[154],"priority":[156],"early":[159],"stop,":[160],"substantially":[162],"shorten":[163],"latency.":[165],"A":[166],"hardware":[167],"prototype":[168],"synthesized":[170],"28":[173],"nm":[174],"CMOS":[175],"technology":[176],"evaluation":[178],"benchmarking.":[180],"demonstrates":[182],"up":[183],"6.59\u00d7":[185],"efficiency,":[188],"2.38\u00d7":[189],"speed,":[191],"scalability":[195],"over":[196],"SIMD":[198],"ASIC":[199],"baseline.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}