{"id":"https://openalex.org/W2967531349","doi":"https://doi.org/10.1109/access.2019.2935389","title":"Real-Time Control for Power Cost Efficient Deep Learning Processing With Renewable Generation","display_name":"Real-Time Control for Power Cost Efficient Deep Learning Processing With Renewable Generation","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2967531349","doi":"https://doi.org/10.1109/access.2019.2935389","mag":"2967531349"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2935389","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2935389","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08798637.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08798637.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091359312","display_name":"Dong-Ki Kang","orcid":"https://orcid.org/0000-0003-1314-8189"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong-Ki Kang","raw_affiliation_strings":["School of Electrical Engineering, KAIST, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-1314-8189","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045403869","display_name":"Chan\u2010Hyun Youn","orcid":"https://orcid.org/0000-0002-3970-7308"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chan-Hyun Youn","raw_affiliation_strings":["School of Electrical Engineering, KAIST, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.397,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.64637318,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"7","issue":null,"first_page":"114909","last_page":"114922"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"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":0.9991000294685364,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9980000257492065,"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/T12676","display_name":"Machine Learning and ELM","score":0.9958999752998352,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.821194052696228},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5173858404159546},{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.509044349193573},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.4671062231063843},{"id":"https://openalex.org/keywords/renewable-energy","display_name":"Renewable energy","score":0.4461541771888733},{"id":"https://openalex.org/keywords/electricity-generation","display_name":"Electricity generation","score":0.4425894618034363},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41680824756622314},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3830651044845581},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.31706953048706055},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2690942883491516},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.22077873349189758},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.08940327167510986}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.821194052696228},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5173858404159546},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.509044349193573},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.4671062231063843},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.4461541771888733},{"id":"https://openalex.org/C423512","wikidata":"https://www.wikidata.org/wiki/Q383973","display_name":"Electricity generation","level":3,"score":0.4425894618034363},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41680824756622314},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3830651044845581},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.31706953048706055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2690942883491516},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.22077873349189758},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.08940327167510986},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2935389","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2935389","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08798637.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:82b9232dd43c4b7cbf556824ae07483c","is_oa":true,"landing_page_url":"https://doaj.org/article/82b9232dd43c4b7cbf556824ae07483c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 114909-114922 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2935389","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2935389","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08798637.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8899999856948853,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G762644068","display_name":null,"funder_award_id":"2017-0-00294","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2967531349.pdf","grobid_xml":"https://content.openalex.org/works/W2967531349.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1468576370","https://openalex.org/W1553670958","https://openalex.org/W1686810756","https://openalex.org/W1978969737","https://openalex.org/W1981585916","https://openalex.org/W2044795764","https://openalex.org/W2057308010","https://openalex.org/W2074084090","https://openalex.org/W2108598243","https://openalex.org/W2123585936","https://openalex.org/W2140054687","https://openalex.org/W2149416133","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2186339937","https://openalex.org/W2194775991","https://openalex.org/W2478490256","https://openalex.org/W2513554817","https://openalex.org/W2534771912","https://openalex.org/W2562420464","https://openalex.org/W2610077734","https://openalex.org/W2622263826","https://openalex.org/W2730150110","https://openalex.org/W2754184362","https://openalex.org/W2760837370","https://openalex.org/W2766940648","https://openalex.org/W2797462110","https://openalex.org/W2801576564","https://openalex.org/W2807731816","https://openalex.org/W2808980893","https://openalex.org/W2891123429","https://openalex.org/W2892341857","https://openalex.org/W2901621510","https://openalex.org/W2902073811","https://openalex.org/W2902257695","https://openalex.org/W2905626117","https://openalex.org/W2910603649","https://openalex.org/W2919115771","https://openalex.org/W2931283745","https://openalex.org/W2944278233","https://openalex.org/W4211147054","https://openalex.org/W4301014524","https://openalex.org/W4400830393","https://openalex.org/W6628746399","https://openalex.org/W6633057607","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6739622702","https://openalex.org/W6744262393","https://openalex.org/W6761160871"],"related_works":["https://openalex.org/W1990079087","https://openalex.org/W3202234113","https://openalex.org/W2101188133","https://openalex.org/W4248731570","https://openalex.org/W2381210024","https://openalex.org/W3093216143","https://openalex.org/W2993707183","https://openalex.org/W2897931424","https://openalex.org/W1990062858","https://openalex.org/W2900183140"],"abstract_inverted_index":{"The":[0,25],"explosive":[1],"increase":[2],"in":[3,18,105,129,162,219],"deep":[4,163],"learning":[5],"(DL)":[6],"deployment":[7],"has":[8,215],"led":[9],"GPU":[10,41,77,106,112],"power":[11,42,63,78,96,127,224],"usage":[12],"to":[13,46,122,131,191,229],"become":[14],"a":[15,94],"major":[16],"factor":[17],"operational":[19],"cost":[20,74,101,225],"of":[21,28,62,90,204,221],"modern":[22],"HPC":[23],"clusters.":[24,108],"complex":[26],"mixture":[27],"DL":[29,81,103,126,146,222],"processing,":[30],"fluctuated":[31],"renewable":[32,133,205],"generation,":[33],"and":[34,68,135,177,207,217,226],"dynamic":[35,132],"electricity":[36,136,208],"price":[37],"impedes":[38],"the":[39,60,73,87,111,125,139,144,171,181,212],"elaborate":[40],"control,":[43],"so":[44],"as":[45,86],"lead":[47],"an":[48],"undesirable":[49],"cost.":[50],"However,":[51],"most":[52],"previous":[53],"studies":[54],"have":[55,69],"been":[56],"concerned":[57],"only":[58],"with":[59],"design":[61,110],"management":[64],"method":[65,190],"using":[66,200],"DL,":[67],"not":[70],"care":[71],"about":[72],"caused":[75],"by":[76,149],"consumption":[79,128],"for":[80,100],"processing":[82,104,223],"itself.":[83],"This":[84],"paper,":[85],"opposite":[88],"direction":[89],"these":[91],"trends,":[92],"proposes":[93],"real-time":[95],"controller":[97],"called":[98],"DeepPow-CTR":[99,214],"efficient":[102],"based":[107,116,185],"We":[109],"frequency":[113],"scaling":[114],"algorithm":[115],"on":[117,197],"model":[118,167],"predictive":[119],"control":[120],"(MPC),":[121],"delicately":[123],"tune":[124],"response":[130],"generation":[134,206],"price.":[137],"At":[138],"same":[140],"time,":[141],"we":[142,179],"avoid":[143],"unacceptable":[145],"performance":[147],"degradation":[148],"regulating":[150],"memory-access":[151],"/":[152,154],"feed-forward":[153],"back-propagation":[155],"(MFB)":[156],"time":[157],"per":[158],"each":[159],"minibatch":[160],"data":[161,203],"neural":[164],"network":[165],"(DNN)":[166],"training.":[168],"To":[169],"solve":[170],"designed":[172],"nonlinear":[173],"MPC":[174],"problem":[175],"rapidly":[176],"accurately,":[178],"apply":[180],"damped":[182],"Broyden-Fletcher-Goldfarb-Shanno":[183],"(BFGS)":[184],"sequential":[186],"quadratic":[187],"programming":[188],"(SQP)":[189],"our":[192],"DeepPow-CTR.":[193],"Our":[194],"experimental":[195],"results":[196],"lab-scale":[198],"testbed":[199],"real":[201],"trace":[202],"price,":[209],"demonstrate":[210],"that":[211],"proposed":[213],"superiority":[216],"practicality":[218],"terms":[220],"performance,":[227],"compared":[228],"existing":[230],"methods.":[231]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}