{"id":"https://openalex.org/W4312608791","doi":"https://doi.org/10.1109/igarss46834.2022.9883762","title":"Optimizing Distributed Deep Learning in Heterogeneous Computing Platforms for Remote Sensing Data Classification","display_name":"Optimizing Distributed Deep Learning in Heterogeneous Computing Platforms for Remote Sensing Data Classification","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4312608791","doi":"https://doi.org/10.1109/igarss46834.2022.9883762"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9883762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883762","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/20.500.14468/24422","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019044105","display_name":"Sergio Moreno\u2010\u00c1lvarez","orcid":"https://orcid.org/0000-0002-1858-9920"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Sergio Moreno-Alvarez","raw_affiliation_strings":["University of Extremadura,Department of Computer and Telematics Systems Engineering,Spain","Department of Computer and Telematics Systems Engineering, University of Extremadura, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Extremadura,Department of Computer and Telematics Systems Engineering,Spain","institution_ids":["https://openalex.org/I80606768"]},{"raw_affiliation_string":"Department of Computer and Telematics Systems Engineering, University of Extremadura, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046123228","display_name":"Mercedes E. Paoletti","orcid":"https://orcid.org/0000-0003-1030-3729"},"institutions":[{"id":"https://openalex.org/I121748325","display_name":"Universidad Complutense de Madrid","ror":"https://ror.org/02p0gd045","country_code":"ES","type":"education","lineage":["https://openalex.org/I121748325"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Mercedes E. Paoletti","raw_affiliation_strings":["Complutense University,Department of Computer Architecture,Madrid,Spain","Department of Computer Architecture, Complutense University, Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Complutense University,Department of Computer Architecture,Madrid,Spain","institution_ids":["https://openalex.org/I121748325"]},{"raw_affiliation_string":"Department of Computer Architecture, Complutense University, Madrid, Spain","institution_ids":["https://openalex.org/I121748325"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114038230","display_name":"Juan A. Rico","orcid":null},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan A. Rico","raw_affiliation_strings":["University of Extremadura,Department of Computer and Telematics Systems Engineering,Spain","Department of Computer and Telematics Systems Engineering, University of Extremadura, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Extremadura,Department of Computer and Telematics Systems Engineering,Spain","institution_ids":["https://openalex.org/I80606768"]},{"raw_affiliation_string":"Department of Computer and Telematics Systems Engineering, University of Extremadura, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058680339","display_name":"Gabriele Cavallaro","orcid":"https://orcid.org/0000-0002-3239-9904"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gabriele Cavallaro","raw_affiliation_strings":["Jülich Supercomputing Centre,Forschungszentrum Jülich,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jülich Supercomputing Centre,Forschungszentrum Jülich,Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039673511","display_name":"Juan M. Haut","orcid":"https://orcid.org/0000-0001-6701-961X"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan M. Haut","raw_affiliation_strings":["University of Extremadura,Hypercomp, Dept. of Technology of Computers & Communications,Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Extremadura,Hypercomp, Dept. of Technology of Computers & Communications,Spain","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":null,"first_page":"2726","last_page":"2729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9987000226974487,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8450606465339661},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.6318751573562622},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.6085063219070435},{"id":"https://openalex.org/keywords/supercomputer","display_name":"Supercomputer","score":0.6061023473739624},{"id":"https://openalex.org/keywords/data-parallelism","display_name":"Data parallelism","score":0.5796722769737244},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.572749137878418},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5590422749519348},{"id":"https://openalex.org/keywords/replica","display_name":"Replica","score":0.5392756462097168},{"id":"https://openalex.org/keywords/symmetric-multiprocessor-system","display_name":"Symmetric multiprocessor system","score":0.4961870312690735},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4837527275085449},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4798535704612732},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4242323935031891},{"id":"https://openalex.org/keywords/parallelism","display_name":"Parallelism (grammar)","score":0.3762248754501343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3715856969356537},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.25312215089797974}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8450606465339661},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.6318751573562622},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.6085063219070435},{"id":"https://openalex.org/C83283714","wikidata":"https://www.wikidata.org/wiki/Q121117","display_name":"Supercomputer","level":2,"score":0.6061023473739624},{"id":"https://openalex.org/C61483411","wikidata":"https://www.wikidata.org/wiki/Q3124522","display_name":"Data parallelism","level":3,"score":0.5796722769737244},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.572749137878418},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5590422749519348},{"id":"https://openalex.org/C2775937380","wikidata":"https://www.wikidata.org/wiki/Q1232589","display_name":"Replica","level":2,"score":0.5392756462097168},{"id":"https://openalex.org/C172430144","wikidata":"https://www.wikidata.org/wiki/Q17111997","display_name":"Symmetric multiprocessor system","level":2,"score":0.4961870312690735},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4837527275085449},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4798535704612732},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4242323935031891},{"id":"https://openalex.org/C2781172179","wikidata":"https://www.wikidata.org/wiki/Q853109","display_name":"Parallelism (grammar)","level":2,"score":0.3762248754501343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3715856969356537},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25312215089797974},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss46834.2022.9883762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883762","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:e-spacio.uned.es:20.500.14468/24422","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.14468/24422","pdf_url":null,"source":{"id":"https://openalex.org/S7407055166","display_name":"UNED repository","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference proceedings"}],"best_oa_location":{"id":"pmh:oai:e-spacio.uned.es:20.500.14468/24422","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.14468/24422","pdf_url":null,"source":{"id":"https://openalex.org/S7407055166","display_name":"UNED repository","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference proceedings"},"sustainable_development_goals":[{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1980038761","https://openalex.org/W2047268015","https://openalex.org/W2194775991","https://openalex.org/W2594265094","https://openalex.org/W2760340275","https://openalex.org/W2802076210","https://openalex.org/W2902190145","https://openalex.org/W2963964896","https://openalex.org/W2972087877","https://openalex.org/W3010045285","https://openalex.org/W4288079579","https://openalex.org/W4301239768","https://openalex.org/W6631190155","https://openalex.org/W6645519200","https://openalex.org/W6748645090","https://openalex.org/W6751595859","https://openalex.org/W6756446114"],"related_works":["https://openalex.org/W2950520577","https://openalex.org/W1501159154","https://openalex.org/W1554644772","https://openalex.org/W2003935582","https://openalex.org/W2494130044","https://openalex.org/W3170887803","https://openalex.org/W74409296","https://openalex.org/W3209384898","https://openalex.org/W4400951174","https://openalex.org/W1595834484"],"abstract_inverted_index":{"Applications":[0],"from":[1,38],"Remote":[2],"Sensing":[3],"(RS)":[4],"unveiled":[5],"unique":[6],"challenges":[7],"to":[8,13,33,112,123,132,138,179],"Deep":[9],"Learning":[10],"(DL)":[11],"due":[12],"the":[14,23,31,42,73,108,113,125,130,133,139,163,175,182],"high":[15,54],"volume":[16],"and":[17,88,160,172],"complexity":[18],"of":[19,50,75,142,181],"their":[20],"data.":[21,40],"On":[22,41],"one":[24,180],"hand,":[25,44],"deep":[26],"neural":[27],"network":[28],"architectures":[29],"have":[30,47,67],"capability":[32],"automatically":[34],"ex-tract":[35],"informative":[36],"features":[37],"RS":[39,158],"other":[43],"these":[45],"models":[46],"massive":[48],"amounts":[49],"tunable":[51],"parameters,":[52],"re-quiring":[53],"computational":[55],"capabilities.":[56],"Distributed":[57],"DL":[58,76,144,185],"with":[59,72,93,157],"data":[60,102,109,159],"parallelism":[61,103],"on":[62],"High-Performance":[63],"Computing":[64],"(HPC)":[65],"sys-tems":[66],"proved":[68],"necessary":[69],"in":[70,152,174],"dealing":[71],"demands":[74],"models.":[77],"Nevertheless,":[78],"a":[79,100,153,167],"single":[80],"HPC":[81,155],"system":[82,156],"can":[83],"be":[84],"al-ready":[85],"highly":[86],"heterogeneous":[87,154],"include":[89],"different":[90],"computing":[91,115],"resources":[92],"uneven":[94],"processing":[95,140],"power.":[96],"In":[97],"this":[98],"context,":[99],"standard":[101],"strategy":[104],"does":[105],"not":[106],"partition":[107],"efficiently":[110],"according":[111],"available":[114],"resources.":[116],"This":[117],"paper":[118],"proposes":[119],"an":[120],"alternative":[121],"approach":[122,165],"compute":[124],"gradient,":[126],"which":[127],"guarantees":[128],"that":[129,162],"contribution":[131],"gradi-ent":[134],"calculation":[135],"is":[136],"proportional":[137],"speed":[141,170],"each":[143],"model's":[145],"replica.":[146],"The":[147],"experimental":[148],"results":[149],"are":[150],"obtained":[151],"demon-strate":[161],"proposed":[164],"provides":[166],"significant":[168],"training":[169],"up":[171],"gain":[173],"global":[176],"accuracy":[177],"compared":[178],"state-of-the-art":[183],"distributed":[184],"framework.":[186]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}