{"id":"https://openalex.org/W4415744623","doi":"https://doi.org/10.1109/ccci65983.2025.11215145","title":"MAGNETO: A Genetic Algorithm-Based Power-Aware Mapping Optimization Framework for Mobile NPUs","display_name":"MAGNETO: A Genetic Algorithm-Based Power-Aware Mapping Optimization Framework for Mobile NPUs","publication_year":2025,"publication_date":"2025-10-15","ids":{"openalex":"https://openalex.org/W4415744623","doi":"https://doi.org/10.1109/ccci65983.2025.11215145"},"language":null,"primary_location":{"id":"doi:10.1109/ccci65983.2025.11215145","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccci65983.2025.11215145","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","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/A5100630689","display_name":"Eunjin Lee","orcid":"https://orcid.org/0000-0003-4085-9664"},"institutions":[{"id":"https://openalex.org/I138925566","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05","country_code":"KR","type":"education","lineage":["https://openalex.org/I138925566"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Eunjin Lee","raw_affiliation_strings":["Ewha Womans University,Artificial Intelligence Convergence,Seoul,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Ewha Womans University,Artificial Intelligence Convergence,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I138925566"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100685124","display_name":"Jiho Lee","orcid":"https://orcid.org/0000-0003-2359-0990"},"institutions":[{"id":"https://openalex.org/I138925566","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05","country_code":"KR","type":"education","lineage":["https://openalex.org/I138925566"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jiho Lee","raw_affiliation_strings":["Ewha Womans University,Dept. of Computer Science and Engineering,Seoul,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Ewha Womans University,Dept. of Computer Science and Engineering,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I138925566"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hayoung Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I138925566","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05","country_code":"KR","type":"education","lineage":["https://openalex.org/I138925566"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hayoung Lim","raw_affiliation_strings":["Ewha Womans University,Artificial Intelligence Convergence,Seoul,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Ewha Womans University,Artificial Intelligence Convergence,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I138925566"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013362846","display_name":"Jaehyeong Sim","orcid":"https://orcid.org/0000-0001-8722-8486"},"institutions":[{"id":"https://openalex.org/I138925566","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05","country_code":"KR","type":"education","lineage":["https://openalex.org/I138925566"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaehyeong Sim","raw_affiliation_strings":["Ewha Womans University,Dept. of Computer Science and Engineering,Seoul,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Ewha Womans University,Dept. of Computer Science and Engineering,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I138925566"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100630689"],"corresponding_institution_ids":["https://openalex.org/I138925566"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29999325,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12238","display_name":"Green IT and Sustainability","score":0.16009999811649323,"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"}},"topics":[{"id":"https://openalex.org/T12238","display_name":"Green IT and Sustainability","score":0.16009999811649323,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.1128000020980835,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.10559999942779541,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/inference","display_name":"Inference","score":0.5782999992370605},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5058000087738037},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4733000099658966},{"id":"https://openalex.org/keywords/matrix-multiplication","display_name":"Matrix multiplication","score":0.4616999924182892},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4269999861717224},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4027999937534332},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.37450000643730164},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.3662000000476837},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.36090001463890076}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6816999912261963},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5782999992370605},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5058000087738037},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4733000099658966},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.4616999924182892},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4027999937534332},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.37450000643730164},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3662000000476837},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.36090001463890076},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3262999951839447},{"id":"https://openalex.org/C142685569","wikidata":"https://www.wikidata.org/wiki/Q1086961","display_name":"Bilinear map","level":3,"score":0.32190001010894775},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.3009999990463257},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C2780595030","wikidata":"https://www.wikidata.org/wiki/Q3860309","display_name":"Multiplication (music)","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2863999903202057},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2840000092983246},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C177225278","wikidata":"https://www.wikidata.org/wiki/Q192674","display_name":"Factoring","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2676999866962433},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.25760000944137573},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccci65983.2025.11215145","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccci65983.2025.11215145","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321365","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1979527452","https://openalex.org/W2067523571","https://openalex.org/W2289252105","https://openalex.org/W2606722458","https://openalex.org/W2936278485","https://openalex.org/W2940862705","https://openalex.org/W2963341956","https://openalex.org/W2998732502","https://openalex.org/W3017521908","https://openalex.org/W3097528158","https://openalex.org/W3112293503","https://openalex.org/W3133635270","https://openalex.org/W4226323948","https://openalex.org/W4393171381"],"related_works":[],"abstract_inverted_index":{"MAGNETO":[0,21,51,84,98],"is":[1],"a":[2,23,110],"power-aware":[3],"genetic":[4],"search":[5,38],"framework":[6],"for":[7,133],"mapping":[8,37,49,54,129],"deep":[9],"neural":[10,14],"network":[11],"layers":[12],"onto":[13],"processing":[15],"units":[16],"with":[17],"strict":[18,111],"power":[19,114,131],"constraints.":[20],"incorporates":[22],"penalty-based":[24],"constraint":[25],"enforcement":[26],"mechanism":[27],"and":[28,44,65,80,93,104],"an":[29],"energy-delay":[30],"product-oriented":[31],"fitness":[32],"function":[33],"to":[34,56,61],"guide":[35],"the":[36,125],"toward":[39],"solutions":[40],"that":[41,83],"balance":[42],"latency":[43,103],"energy":[45,106],"efficiency.":[46],"Unlike":[47],"traditional":[48],"strategies,":[50],"dynamically":[52],"explores":[53],"configurations":[55],"discover":[57],"high-quality":[58],"mappings":[59],"tailored":[60],"each":[62],"layer\u2019s":[63],"computational":[64],"memory":[66],"access":[67],"characteristics.Extensive":[68],"experiments":[69],"across":[70],"various":[71],"layer":[72],"types\u2014including":[73],"convolutional":[74],"layers,":[75,79],"general":[76],"matrix":[77],"multiplication":[78],"linear":[81],"layers\u2014demonstrate":[82],"consistently":[85],"outperforms":[86],"baseline":[87],"strategies":[88],"in":[89,139],"terms":[90],"of":[91,127],"TOPS/W":[92],"Energy":[94],"per":[95],"MAC.":[96],"Notably,":[97],"also":[99],"achieves":[100],"both":[101],"low":[102],"efficient":[105],"usage":[107],"even":[108],"under":[109,130],"1":[112],"W":[113],"budget,":[115],"showing":[116],"competitive":[117],"or":[118],"superior":[119],"latency-energy":[120],"trade-offs.":[121],"Our":[122],"results":[123],"highlight":[124],"potential":[126],"search-based":[128],"constraints":[132],"real-time,":[134],"energy-efficient":[135],"inference":[136],"on":[137],"NPUs":[138],"edge":[140],"environments.":[141]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-31T00:00:00"}
