{"id":"https://openalex.org/W4413755590","doi":"https://doi.org/10.1109/isvlsi65124.2025.11130214","title":"Hardware-Accelerated On-Device Learning: Training, Partitioning, and Compilation for Constrained Edge AI","display_name":"Hardware-Accelerated On-Device Learning: Training, Partitioning, and Compilation for Constrained Edge AI","publication_year":2025,"publication_date":"2025-07-06","ids":{"openalex":"https://openalex.org/W4413755590","doi":"https://doi.org/10.1109/isvlsi65124.2025.11130214"},"language":"en","primary_location":{"id":"doi:10.1109/isvlsi65124.2025.11130214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isvlsi65124.2025.11130214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","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/A5098537161","display_name":"Iuliia Topko","orcid":null},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Iuliia Topko","raw_affiliation_strings":["Karlsruhe Institute of Technology,Karlsruhe,Germany"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology,Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114068443","display_name":"Alexey Serdyuk","orcid":null},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alexey Serdyuk","raw_affiliation_strings":["Karlsruhe Institute of Technology,Karlsruhe,Germany"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology,Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053259767","display_name":"Tanja Harbaum","orcid":"https://orcid.org/0000-0001-7310-567X"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tanja Harbaum","raw_affiliation_strings":["Karlsruhe Institute of Technology,Karlsruhe,Germany"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology,Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024739574","display_name":"J\u00fcrgen Becker","orcid":"https://orcid.org/0000-0002-5082-5487"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J\u00fcrgen Becker","raw_affiliation_strings":["Karlsruhe Institute of Technology,Karlsruhe,Germany"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology,Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5098537161"],"corresponding_institution_ids":["https://openalex.org/I102335020"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3035343,"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":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.7591000199317932,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.7591000199317932,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.7376999855041504,"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"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.7095000147819519,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.7486780881881714},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6803869009017944},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6539357900619507},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4634653627872467},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4406968057155609},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4198065996170044},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.35456424951553345},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.352486252784729},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.27754834294319153}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7486780881881714},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6803869009017944},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6539357900619507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4634653627872467},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4406968057155609},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4198065996170044},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.35456424951553345},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.352486252784729},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.27754834294319153},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isvlsi65124.2025.11130214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isvlsi65124.2025.11130214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311687","display_name":"Ministry of Education","ror":"https://ror.org/03m01yf64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2037465995","https://openalex.org/W2108598243","https://openalex.org/W2940862705","https://openalex.org/W2998732502","https://openalex.org/W3035172746","https://openalex.org/W3117204317","https://openalex.org/W3122286897","https://openalex.org/W3176714321","https://openalex.org/W4285167314","https://openalex.org/W4321636603","https://openalex.org/W4362723189","https://openalex.org/W4386566659","https://openalex.org/W4386742057","https://openalex.org/W4394824370","https://openalex.org/W4400081497","https://openalex.org/W4401642802","https://openalex.org/W4402111642","https://openalex.org/W4402835864"],"related_works":["https://openalex.org/W4313339048","https://openalex.org/W3176734149","https://openalex.org/W3201779876","https://openalex.org/W3113627641","https://openalex.org/W3191964704","https://openalex.org/W2918879532","https://openalex.org/W3083220997","https://openalex.org/W2885461866","https://openalex.org/W3162654428","https://openalex.org/W2901937988"],"abstract_inverted_index":{"Real-world":[0],"applications,":[1],"such":[2],"as":[3],"autonomous":[4],"driv-":[5],"ing,":[6],"require":[7],"continuous":[8],"adaptation":[9,57],"of":[10,23,47,127],"Deep":[11],"Neural":[12],"Networks":[13],"(DNNs)":[14],"to":[15,20,36,80,95],"local":[16],"environments.":[17],"In":[18],"addition":[19],"the":[21,60,65,81,87],"growth":[22],"DNNs":[24],"in":[25],"recent":[26],"years,":[27],"Transfer":[28,146],"Learning":[29,92],"methods":[30,49],"that":[31,111],"adapt":[32],"a":[33,37,76],"pre-trained":[34],"model":[35,56,119,133],"new":[38],"domain":[39,61],"have":[40],"become":[41],"more":[42],"widespread.":[43],"A":[44],"further":[45],"improvement":[46],"these":[48],"is":[50,98],"on-":[51],"device":[52],"learning,":[53],"which":[54],"allows":[55],"based":[58],"on":[59,64,71],"data":[62],"directly":[63],"device.":[66],"However,":[67],"efficient":[68],"on-device":[69,108,141],"training":[70],"constrained":[72],"edge":[73],"AI":[74],"remains":[75],"challenging":[77],"task,":[78],"due":[79],"limited":[82],"available":[83],"compute":[84],"resources.":[85],"Currently,":[86],"deployment":[88],"process,":[89],"from":[90],"Machine":[91],"(ML)":[93],"frameworks":[94],"hardware":[96,124],"accelerators,":[97],"mainly":[99],"optimized":[100],"for":[101,118,139],"inference.":[102],"This":[103],"paper":[104],"proposes":[105],"an":[106,131],"end-to-end":[107],"learning":[109],"strategy":[110],"considers":[112],"three":[113],"main":[114],"aspects:":[115],"algorithmic":[116],"techniques":[117],"adaptation,":[120],"ML":[121],"compilation,":[122],"and":[123],"architectures":[125],"capable":[126],"training.":[128],"We":[129],"present":[130],"initial":[132],"analysis":[134],"highlighting":[135],"potential":[136],"partitioning":[137],"points":[138],"hardware-accelerated":[140],"learning.":[142],"Index":[143],"Terms-Machine":[144],"Learning,":[145,147,149],"Ondevice":[148],"Hardware":[150],"Accelerator":[151]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
