{"id":"https://openalex.org/W2808622995","doi":"https://doi.org/10.1109/tmscs.2018.2845886","title":"DLoBD: A Comprehensive Study of Deep Learning over Big Data Stacks on HPC Clusters","display_name":"DLoBD: A Comprehensive Study of Deep Learning over Big Data Stacks on HPC Clusters","publication_year":2018,"publication_date":"2018-06-11","ids":{"openalex":"https://openalex.org/W2808622995","doi":"https://doi.org/10.1109/tmscs.2018.2845886","mag":"2808622995"},"language":"en","primary_location":{"id":"doi:10.1109/tmscs.2018.2845886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmscs.2018.2845886","pdf_url":null,"source":{"id":"https://openalex.org/S4210201583","display_name":"IEEE Transactions on Multi-Scale Computing Systems","issn_l":"2332-7766","issn":["2332-7766","2372-207X"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multi-Scale Computing Systems","raw_type":"journal-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/A5067748041","display_name":"Xiaoyi Lu","orcid":"https://orcid.org/0000-0001-7581-8905"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoyi Lu","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA"],"raw_orcid":"https://orcid.org/0000-0001-7581-8905","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016218994","display_name":"Haiyang Shi","orcid":"https://orcid.org/0000-0002-6105-4737"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haiyang Shi","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101415525","display_name":"Rajarshi Biswas","orcid":"https://orcid.org/0000-0002-2793-7798"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rajarshi Biswas","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102836528","display_name":"M. Haseeb Javed","orcid":"https://orcid.org/0000-0002-2812-1045"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. Haseeb Javed","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA"],"raw_orcid":"https://orcid.org/0000-0002-2812-1045","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024879682","display_name":"Dhabaleswar K. Panda","orcid":"https://orcid.org/0000-0002-0356-1781"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dhabaleswar K. Panda","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":1.7202,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.85779871,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"4","issue":"4","first_page":"635","last_page":"648"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9973000288009644,"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":0.9973000288009644,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11181","display_name":"Advanced Data Storage Technologies","score":0.9921000003814697,"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/big-data","display_name":"Big data","score":0.6339214444160461},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46442046761512756},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.44397401809692383},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4398859739303589},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2972254753112793},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.16161590814590454}],"concepts":[{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6339214444160461},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46442046761512756},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.44397401809692383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4398859739303589},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2972254753112793},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.16161590814590454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmscs.2018.2845886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmscs.2018.2845886","pdf_url":null,"source":{"id":"https://openalex.org/S4210201583","display_name":"IEEE Transactions on Multi-Scale Computing Systems","issn_l":"2332-7766","issn":["2332-7766","2372-207X"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multi-Scale Computing Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W182691100","https://openalex.org/W1502383304","https://openalex.org/W1581677478","https://openalex.org/W1667652561","https://openalex.org/W1686810756","https://openalex.org/W1968781019","https://openalex.org/W1984020445","https://openalex.org/W1990082882","https://openalex.org/W2097117768","https://openalex.org/W2112796928","https://openalex.org/W2118023920","https://openalex.org/W2155893237","https://openalex.org/W2161050705","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2198403777","https://openalex.org/W2294581108","https://openalex.org/W2402144811","https://openalex.org/W2513383847","https://openalex.org/W2580688187","https://openalex.org/W2584830274","https://openalex.org/W2751051839","https://openalex.org/W2766487154","https://openalex.org/W2787998955","https://openalex.org/W2797740023","https://openalex.org/W2797862701","https://openalex.org/W2953384591","https://openalex.org/W2962758826","https://openalex.org/W2962844195","https://openalex.org/W2984509121","https://openalex.org/W4299797662","https://openalex.org/W4301239768","https://openalex.org/W4302296459","https://openalex.org/W6607408290","https://openalex.org/W6637151318","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6687494587","https://openalex.org/W6696776605","https://openalex.org/W6713134421","https://openalex.org/W6739693220","https://openalex.org/W6748645090","https://openalex.org/W6750139411","https://openalex.org/W6891802897"],"related_works":["https://openalex.org/W4322629366","https://openalex.org/W2808989540","https://openalex.org/W2397053934","https://openalex.org/W1039292361","https://openalex.org/W2551093110","https://openalex.org/W2148016376","https://openalex.org/W4237919137","https://openalex.org/W3184179822","https://openalex.org/W3095362084","https://openalex.org/W3003361536"],"abstract_inverted_index":{"DeepLearningoverBigData":[0],"(DLoBD)":[1],"is":[2,48],"an":[3,174],"emerging":[4],"paradigm":[5],"to":[6,92,116,120,186],"mine":[7],"value":[8],"from":[9],"the":[10,45,56,94,121,188],"massive":[11],"amount":[12],"of":[13,40,51,58,190],"gathered":[14],"data.":[15],"Many":[16],"Deep":[17],"Learning":[18],"frameworks,":[19],"like":[20],"Caffe,":[21],"TensorFlow,":[22],"etc.,":[23],"start":[24],"running":[25],"over":[26],"Big":[27],"Data":[28],"stacks,":[29],"such":[30],"as":[31],"Apache":[32],"Hadoop":[33],"and":[34,61,76,90,101,130,163,173],"Spark.":[35],"Even":[36],"though":[37],"a":[38,49,72],"lot":[39],"activities":[41],"are":[42,183],"happening":[43],"in":[44],"field,":[46],"there":[47,182],"lack":[50],"comprehensive":[52],"studies":[53],"on":[54,63,81,152,167,177],"analyzing":[55],"impact":[57],"RDMA-capable":[59],"networks":[60],"CPUs/GPUs":[62],"DLoBD":[64,84,111,192],"stacks.":[65,193],"To":[66],"fill":[67],"this":[68],"gap,":[69],"we":[70,147,179],"propose":[71],"systematical":[73],"characterization":[74],"methodology":[75],"conduct":[77],"extensive":[78],"performance":[79,160],"evaluations":[80],"four":[82],"representative":[83],"stacks":[85,112],"(i.e.,":[86],"CaffeOnSpark,":[87],"TensorFlowOnSpark,":[88,178],"MMLSpark/CNTKOnSpark,":[89],"BigDL)":[91],"expose":[93],"interesting":[95],"trends":[96],"regarding":[97],"performance,":[98],"scalability,":[99],"accuracy,":[100],"resource":[102],"utilization.":[103],"Our":[104],"observations":[105],"show":[106],"that":[107,149,181],"RDMA-based":[108],"design":[109],"for":[110,150],"can":[113,142,157],"achieve":[114,158],"up":[115],"2.7x":[117],"speedup":[118],"compared":[119],"IPoIB-based":[122],"scheme.":[123],"The":[124],"RDMA":[125],"scheme":[126],"also":[127],"scales":[128],"better":[129,159],"utilizes":[131],"resources":[132],"more":[133],"efficiently":[134],"than":[135,161],"IPoIB.":[136],"For":[137],"most":[138],"cases,":[139],"GPU-based":[140],"schemes":[141],"outperform":[143],"CPU-based":[144],"designs,":[145],"but":[146],"see":[148],"LeNet":[151],"MNIST,":[153],"CPU":[154],"+":[155,165],"MKL":[156],"GPU":[162,164],"cuDNN":[166],"16":[168],"nodes.":[169],"Through":[170],"our":[171],"evaluation":[172],"in-depth":[175],"analysis":[176],"find":[180],"large":[184],"rooms":[185],"improve":[187],"designs":[189],"current-generation":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2}],"updated_date":"2026-08-22T07:34:49.880490","created_date":"2025-10-10T00:00:00"}