{"id":"https://openalex.org/W3106955873","doi":"https://doi.org/10.1109/access.2020.3040849","title":"Speculative Backpropagation for CNN Parallel Training","display_name":"Speculative Backpropagation for CNN Parallel Training","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3106955873","doi":"https://doi.org/10.1109/access.2020.3040849","mag":"3106955873"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3040849","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3040849","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09272337.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09272337.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016660835","display_name":"Sangwoo Park","orcid":"https://orcid.org/0000-0002-5831-2176"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Sangwoo Park","raw_affiliation_strings":["Department of Computer Science and Engineering, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018071173","display_name":"Taeweon Suh","orcid":"https://orcid.org/0000-0002-6377-5482"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Taeweon Suh","raw_affiliation_strings":["Department of Computer Science and Engineering, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5016660835"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.2778,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.82970731,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"215365","last_page":"215374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/backpropagation","display_name":"Backpropagation","score":0.9368551969528198},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.888669490814209},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8630187511444092},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6352208852767944},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6280149221420288},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5608681440353394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5245984792709351},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5012743473052979},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4951743185520172},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3676620125770569}],"concepts":[{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.9368551969528198},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.888669490814209},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8630187511444092},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6352208852767944},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6280149221420288},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5608681440353394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5245984792709351},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5012743473052979},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4951743185520172},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3676620125770569},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3040849","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3040849","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09272337.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ee85e97e58e94035a7fad9ed10bb0123","is_oa":true,"landing_page_url":"https://doaj.org/article/ee85e97e58e94035a7fad9ed10bb0123","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 215365-215374 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3040849","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3040849","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09272337.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2325797177","display_name":null,"funder_award_id":"2019-0-01343","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G263811790","display_name":null,"funder_award_id":"2019-0-01343","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G6072120315","display_name":null,"funder_award_id":"funded","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G6186519187","display_name":null,"funder_award_id":"2019-0-00533","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G7054783114","display_name":null,"funder_award_id":"No.2019-0-01343","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3106955873.pdf","grobid_xml":"https://content.openalex.org/works/W3106955873.grobid-xml"},"referenced_works_count":70,"referenced_works":["https://openalex.org/W594283781","https://openalex.org/W1522301498","https://openalex.org/W1598866093","https://openalex.org/W1686810756","https://openalex.org/W1799366690","https://openalex.org/W2067523571","https://openalex.org/W2097117768","https://openalex.org/W2102017903","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2113547287","https://openalex.org/W2117130368","https://openalex.org/W2118858186","https://openalex.org/W2132424367","https://openalex.org/W2133156997","https://openalex.org/W2138243089","https://openalex.org/W2141125852","https://openalex.org/W2147768505","https://openalex.org/W2152839228","https://openalex.org/W2155806188","https://openalex.org/W2163605009","https://openalex.org/W2166706236","https://openalex.org/W2168231600","https://openalex.org/W2186615578","https://openalex.org/W2194775991","https://openalex.org/W2276486856","https://openalex.org/W2293771166","https://openalex.org/W2319920447","https://openalex.org/W2335835108","https://openalex.org/W2402144811","https://openalex.org/W2469490737","https://openalex.org/W2507556850","https://openalex.org/W2576986579","https://openalex.org/W2620481664","https://openalex.org/W2752159661","https://openalex.org/W2799069271","https://openalex.org/W2800893679","https://openalex.org/W2889111331","https://openalex.org/W2895432151","https://openalex.org/W2953384591","https://openalex.org/W2963140169","https://openalex.org/W2963334011","https://openalex.org/W2963373778","https://openalex.org/W2963881378","https://openalex.org/W2964115671","https://openalex.org/W2964121744","https://openalex.org/W3003315945","https://openalex.org/W3036533541","https://openalex.org/W3118608800","https://openalex.org/W3123753580","https://openalex.org/W4297797035","https://openalex.org/W6631190155","https://openalex.org/W6635810480","https://openalex.org/W6637373629","https://openalex.org/W6638444622","https://openalex.org/W6676756733","https://openalex.org/W6677919164","https://openalex.org/W6680402377","https://openalex.org/W6684191040","https://openalex.org/W6684249991","https://openalex.org/W6684859321","https://openalex.org/W6686509673","https://openalex.org/W6700264148","https://openalex.org/W6713134421","https://openalex.org/W6720242923","https://openalex.org/W6726238325","https://openalex.org/W6738975764","https://openalex.org/W6744265424","https://openalex.org/W6750269818","https://openalex.org/W6755325935"],"related_works":["https://openalex.org/W2899027234","https://openalex.org/W2115605526","https://openalex.org/W3093883775","https://openalex.org/W1539246760","https://openalex.org/W2786746258","https://openalex.org/W4225893763","https://openalex.org/W2788727425","https://openalex.org/W2405196115","https://openalex.org/W2104893957","https://openalex.org/W2971074373"],"abstract_inverted_index":{"The":[0,122],"parallel":[1,46,64,109,123],"learning":[2],"in":[3,32,78,113,131],"neural":[4,34],"networks":[5],"can":[6],"greatly":[7],"shorten":[8],"the":[9,28,33,54,58,63,67,73,79,83,99,107,126,134,137,142,151],"training":[10,36,47,65,124,127],"time.":[11],"Its":[12],"prior":[13],"efforts":[14],"were":[15],"mostly":[16],"limited":[17],"to":[18,21,88,97,141],"distributing":[19],"inputs":[20],"multiple":[22],"computing":[23],"engines.":[24],"It":[25,52],"is":[26,37],"because":[27],"gradient":[29,59],"descent":[30,60],"algorithm":[31],"network":[35],"inherently":[38],"sequential.":[39],"This":[40,92],"paper":[41],"proposes":[42],"a":[43],"novel":[44],"CNN":[45],"method":[48],"for":[49,82],"image":[50],"recognition.":[51],"overcomes":[53],"sequential":[55,143],"property":[56],"of":[57,136],"and":[61,75,101,116,118],"enables":[62],"with":[66,111],"speculative":[68],"backpropagation.":[69],"We":[70,105],"found":[71],"that":[72],"Softmax":[74],"ReLU":[76],"outcomes":[77],"forward":[80,100],"propagation":[81,103],"same":[84],"labels":[85],"are":[86],"likely":[87],"be":[89],"very":[90],"similar.":[91],"characteristic":[93],"makes":[94],"it":[95,148],"possible":[96],"perform":[98],"backward":[102],"simultaneously.":[104],"implemented":[106],"proposed":[108],"model":[110],"CNNs":[112],"both":[114],"software":[115],"hardware,":[117],"evaluated":[119],"its":[120],"performance.":[121],"reduces":[125],"time":[128],"by":[129],"34%":[130],"CIFAR-100":[132],"without":[133],"loss":[135],"prediction":[138],"accuracy":[139],"compared":[140],"training.":[144],"In":[145],"many":[146],"cases,":[147],"even":[149],"improves":[150],"accuracy.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":4}],"updated_date":"2026-03-14T08:43:22.919905","created_date":"2025-10-10T00:00:00"}