{"id":"https://openalex.org/W6981761789","doi":null,"title":"Evaluation of Machine Learning Inference Workloads on Heterogeneous Edge Devices","display_name":"Evaluation of Machine Learning Inference Workloads on Heterogeneous Edge Devices","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W6981761789"},"language":"en","primary_location":{"id":"pmh:oai:aleph.bib-bvb.de:BVB01-032117770","doi":null,"is_oa":false,"landing_page_url":"https://mediatum.ub.tum.de/node?id=1540918","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Hochschulschrift"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://mediatum.ub.tum.de/node?id=1540918","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Rubin, Marco","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Rubin, Marco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.6934000253677368,"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":0.6934000253677368,"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":0.23229999840259552,"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":0.05900000035762787,"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/machine-learning-inference","display_name":"machine learning inference","score":0.9739999771118164},{"id":"https://openalex.org/keywords/edge-computing","display_name":"edge computing","score":0.949999988079071},{"id":"https://openalex.org/keywords/device-heterogeneity","display_name":"heterogeneous devices","score":0.6990000009536743},{"id":"https://openalex.org/keywords/nvidia-jetson-nano","display_name":"Jetson Nano","score":0.949999988079071},{"id":"https://openalex.org/keywords/openvino","display_name":"OpenVINO","score":0.9580000042915344},{"id":"https://openalex.org/keywords/inference-throughput","display_name":"inference throughput","score":0.5479999780654907},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8669999837875366},{"id":"https://openalex.org/keywords/model-precision","display_name":"model precision","score":0.5809999704360962},{"id":"https://openalex.org/keywords/macbook-pro","display_name":"MacBook Pro","score":0.7459999918937683}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7145000100135803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5857999920845032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5498999953269958},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5264999866485596},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4169999957084656},{"id":"https://openalex.org/C50292564","wikidata":"https://www.wikidata.org/wiki/Q2462783","display_name":"Computational learning theory","level":3,"score":0.3093999922275543},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28290000557899475},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:aleph.bib-bvb.de:BVB01-032117770","doi":null,"is_oa":false,"landing_page_url":"https://mediatum.ub.tum.de/node?id=1540918","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Hochschulschrift"},{"id":"pmh:oai:mediatum.ub.tum.de:node/1540918","doi":null,"is_oa":true,"landing_page_url":"http://mediatum.ub.tum.de/node?id=1540918","pdf_url":null,"source":{"id":"https://openalex.org/S4377196330","display_name":"mediaTUM  (Technical University of Munich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I62916508","host_organization_name":"Technical University of Munich","host_organization_lineage":["https://openalex.org/I62916508"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:mediatum.ub.tum.de:node/1540918","doi":null,"is_oa":true,"landing_page_url":"http://mediatum.ub.tum.de/node?id=1540918","pdf_url":null,"source":{"id":"https://openalex.org/S4377196330","display_name":"mediaTUM  (Technical University of Munich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I62916508","host_organization_name":"Technical University of Munich","host_organization_lineage":["https://openalex.org/I62916508"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4212896416","https://openalex.org/W4404524136","https://openalex.org/W2963947694","https://openalex.org/W3122596395","https://openalex.org/W4383048014","https://openalex.org/W4372263903","https://openalex.org/W4306694257","https://openalex.org/W3201951111","https://openalex.org/W3168541340","https://openalex.org/W3193291399"],"abstract_inverted_index":{"Machine":[0],"learning":[1,82],"has":[2],"traditionally":[3],"been":[4],"a":[5,78,115,125],"thing":[6],"of":[7,21,118,131,135,181],"powerful":[8],"computers":[9,42],"and":[10,18,48,61,70,202],"even":[11],"supercomputers.":[12],"Recent":[13],"increases":[14],"in":[15],"computational":[16],"power":[17],"the":[19,26,35,44,51,109,136,140,145,154,159,163,185,188,192,196,203],"development":[20],"specialized":[22,107],"architecture":[23],"led":[24],"to":[25,28,71,123,142,172],"possibility":[27],"perform":[29],"machine":[30,81],"learning,":[31],"especially":[32],"inference,":[33],"on":[34,108,128,153],"edge.":[36],"Those":[37],"edge":[38,173,186],"devices":[39,60,174],"include":[40],"small":[41],"like":[43,50],"Nvidia":[45],"Jetson":[46,189],"Nano":[47,190],"accelerators":[49],"Intel":[52],"Neural":[53,146,199,206],"Compute":[54,147,200,207],"Sticks.":[55],"In":[56],"this":[57,129],"thesis":[58],"these":[59],"their":[62],"respective":[63,110],"frameworks":[64],"are":[65,86],"compared":[66],"amongst":[67],"each":[68],"other":[69,155],"an":[72,90,178],"Apple":[73],"MacBook":[74,160],"Pro":[75],"which":[76],"represents":[77],"more":[79,169],"traditional":[80],"device.":[83],"The":[84,98,133],"comparisons":[85],"done":[87],"by":[88,195],"using":[89],"almost":[91],"identical":[92],"inference":[93],"script":[94],"across":[95],"all":[96],"platforms.":[97],"maximum":[99],"possible":[100],"throughput":[101],"is":[102],"also":[103],"tested":[104],"with":[105,114,177],"tools":[106],"framework.":[111],"Four":[112],"models":[113,137],"different":[116],"number":[117,180],"convolutional":[119,182],"layers":[120],"were":[121],"used":[122,176],"put":[124],"special":[126],"emphasis":[127],"kind":[130],"layer.":[132],"precision":[134],"dropped":[138],"after":[139],"conversion":[141],"OpenVINO":[143],"for":[144],"Sticks,":[148],"but":[149,167],"remained":[150],"equally":[151],"high":[152],"frameworks.":[156],"Regarding":[157],"performance,":[158],"was":[161,191],"still":[162],"fastest":[164],"device":[165],"overall,":[166],"lost":[168],"performance":[170],"proportionally":[171],"when":[175],"increasing":[179],"layers.":[183],"Amongst":[184],"devices,":[187],"fastest,":[193],"followed":[194],"2nd":[197],"gen":[198,205],"Stick":[201],"1st":[204],"Stick.":[208]},"counts_by_year":[],"updated_date":"2026-09-04T10:56:28.161419","created_date":"2025-10-10T00:00:00"}
