{"id":"https://openalex.org/W6992893188","doi":null,"title":"Neural network partitioning for resource-limited environments","display_name":"Neural network partitioning for resource-limited environments","publication_year":2023,"publication_date":"2023-05-02","ids":{"openalex":"https://openalex.org/W6992893188"},"language":"en","primary_location":{"id":"pmh:oai:tudelft.nl:uuid:e39ca6fc-cdd0-40c1-97ed-cca7ff7232c8","doi":null,"is_oa":true,"landing_page_url":"http://resolver.tudelft.nl/uuid:e39ca6fc-cdd0-40c1-97ed-cca7ff7232c8","pdf_url":"https://repository.tudelft.nl/file/File_8f1a4911-11bc-4505-a81f-4542f312d813","source":{"id":"https://openalex.org/S4306400906","display_name":"Research Repository (Delft University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I98358874","host_organization_name":"Delft University of Technology","host_organization_lineage":["https://openalex.org/I98358874"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"master thesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://repository.tudelft.nl/file/File_8f1a4911-11bc-4505-a81f-4542f312d813","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028956576","display_name":"Patrick Geel","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Geel, Patrick (author)","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5028956576"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"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":true,"primary_topic":{"id":"https://openalex.org/T10904","display_name":"Embedded Systems Design Techniques","score":0.9496999979019165,"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"}},"topics":[{"id":"https://openalex.org/T10904","display_name":"Embedded Systems Design Techniques","score":0.9496999979019165,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.04010000079870224,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.003000000026077032,"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/neural-network-partitioning","display_name":"neural network partitioning","score":0.9769999980926514},{"id":"https://openalex.org/keywords/edge-computing","display_name":"edge computing","score":0.7580000162124634},{"id":"https://openalex.org/keywords/resource-constrained-devices","display_name":"resource-constrained devices","score":0.8610000014305115},{"id":"https://openalex.org/keywords/fpga-acceleration","display_name":"FPGA acceleration","score":0.7440000176429749},{"id":"https://openalex.org/keywords/mobilenetv1","display_name":"MobileNetV1","score":0.8379999995231628},{"id":"https://openalex.org/keywords/model-offloading","display_name":"model offloading","score":0.7689999938011169},{"id":"https://openalex.org/keywords/runtime-optimization","display_name":"runtime optimization","score":0.4959999918937683},{"id":"https://openalex.org/keywords/embedded-machine-learning","display_name":"embedded machine learning","score":0.46399998664855957}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7789999842643738},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7017999887466431},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.5763000249862671},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5669000148773193},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4921000003814697},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4471000134944916},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.4009999930858612},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.366100013256073},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3255000114440918},{"id":"https://openalex.org/C49154492","wikidata":"https://www.wikidata.org/wiki/Q5300","display_name":"Central processing unit","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.322299987077713},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.3174999952316284},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2858000099658966},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26910001039505005},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2599000036716461}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:tudelft.nl:uuid:e39ca6fc-cdd0-40c1-97ed-cca7ff7232c8","doi":null,"is_oa":true,"landing_page_url":"http://resolver.tudelft.nl/uuid:e39ca6fc-cdd0-40c1-97ed-cca7ff7232c8","pdf_url":"https://repository.tudelft.nl/file/File_8f1a4911-11bc-4505-a81f-4542f312d813","source":{"id":"https://openalex.org/S4306400906","display_name":"Research Repository (Delft University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I98358874","host_organization_name":"Delft University of Technology","host_organization_lineage":["https://openalex.org/I98358874"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"master thesis"}],"best_oa_location":{"id":"pmh:oai:tudelft.nl:uuid:e39ca6fc-cdd0-40c1-97ed-cca7ff7232c8","doi":null,"is_oa":true,"landing_page_url":"http://resolver.tudelft.nl/uuid:e39ca6fc-cdd0-40c1-97ed-cca7ff7232c8","pdf_url":"https://repository.tudelft.nl/file/File_8f1a4911-11bc-4505-a81f-4542f312d813","source":{"id":"https://openalex.org/S4306400906","display_name":"Research Repository (Delft University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I98358874","host_organization_name":"Delft University of Technology","host_organization_lineage":["https://openalex.org/I98358874"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"master thesis"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5378999710083008,"display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W6992893188.pdf","grobid_xml":"https://content.openalex.org/works/W6992893188.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W143363577","https://openalex.org/W1979081194","https://openalex.org/W2040870580","https://openalex.org/W2119144962","https://openalex.org/W2159139478","https://openalex.org/W2565125333","https://openalex.org/W2574640725","https://openalex.org/W2755741562","https://openalex.org/W2804032941","https://openalex.org/W2809370239","https://openalex.org/W2887936511","https://openalex.org/W2949650786","https://openalex.org/W2954859667","https://openalex.org/W2966086598","https://openalex.org/W2989331028","https://openalex.org/W3008730548","https://openalex.org/W3010156474","https://openalex.org/W3143590514","https://openalex.org/W3208821873","https://openalex.org/W4283069574","https://openalex.org/W4288043073","https://openalex.org/W4313549783","https://openalex.org/W6892885860"],"related_works":["https://openalex.org/W4416958506","https://openalex.org/W4414720976","https://openalex.org/W7124282531","https://openalex.org/W4313211050","https://openalex.org/W4403018073","https://openalex.org/W3091279645","https://openalex.org/W4318969875","https://openalex.org/W4385270478","https://openalex.org/W4393284219","https://openalex.org/W4390871989"],"abstract_inverted_index":{"The":[0,132],"demand":[1],"for":[2,58,72,152,166],"implementing":[3],"neural":[4,39,96,161],"networks":[5,162],"on":[6,30,98],"edge":[7,31],"devices":[8],"has":[9],"rapidly":[10],"increased":[11],"as":[12],"they":[13],"allow":[14],"designers":[15],"to":[16,25,36,51,83,93,159],"move":[17],"away":[18],"from":[19],"expensive":[20,167],"server-grade":[21,168],"hardware.":[22,169],"However,":[23],"due":[24,50],"the":[26,44,65,70,76,84,111,139,164],"limited":[27],"resources":[28],"available":[29],"devices,":[32],"it":[33,90],"is":[34,142],"challenging":[35],"implement":[37,94],"complex":[38],"networks.":[40],"This":[41,146],"study":[42,133],"selected":[43],"Kria":[45],"SoM":[46],"KV260":[47],"hardware":[48,56,66],"platform":[49],"its":[52],"affordability":[53],"and":[54,79,104],"sufficient":[55],"capabilities":[57,68],"creating":[59],"a":[60,95,99,115,118,125,143,149],"resource-constrained":[61],"environment.":[62],"By":[63],"leveraging":[64],"acceleration":[67],"of":[69,75,102,122,138],"FPGA":[71],"specific":[73],"nodes":[74,82],"MobileNetv1":[77,112,140],"model":[78,113,141],"offloading":[80],"other":[81],"onboard":[85],"quad-core":[86],"ARM":[87],"cortex-A53":[88],"CPU,":[89],"was":[91],"feasible":[92],"network":[97],"hybrid":[100,116],"combination":[101],"CPU":[103,127],"FPGA.":[105],"Results":[106],"showed":[107],"that":[108,135],"when":[109],"executing":[110],"in":[114],"configuration,":[117],"total":[119],"runtime":[120],"improvement":[121],"2.8x":[123],"over":[124],"pure":[126],"implementation":[128],"can":[129],"be":[130],"achieved.":[131],"concludes":[134],"node-wise":[136],"partitioning":[137],"practical":[144],"solution.":[145],"approach":[147],"offers":[148],"cost-effective":[150],"solution":[151],"users":[153],"who":[154],"seek":[155],"an":[156],"accessible":[157],"way":[158],"run":[160],"without":[163],"need":[165]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-10-10T00:00:00"}