{"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":true,"raw_author_name":"Xiaoyi Lu","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA"],"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"],"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"],"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"],"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"],"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":5,"corresponding_author_ids":["https://openalex.org/A5067748041"],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":1.4624,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.86775395,"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":{"grobid_xml":false,"pdf":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":{"<underline":[0,4,8,12,16],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[1,5,9,13,17],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">D</u>":[2,18],"eep":[3],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">L</u>":[6],"earning":[7],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">o</u>":[10],"ver":[11],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">B</u>":[14],"ig":[15],"ata":[19],"(DLoBD)":[20],"is":[21,67],"an":[22,193],"emerging":[23],"paradigm":[24],"to":[25,111,135,139,205],"mine":[26],"value":[27],"from":[28],"the":[29,64,75,113,140,207],"massive":[30],"amount":[31],"of":[32,59,70,77,209],"gathered":[33],"data.":[34],"Many":[35],"Deep":[36],"Learning":[37],"frameworks,":[38],"like":[39],"Caffe,":[40],"TensorFlow,":[41],"etc.,":[42],"start":[43],"running":[44],"over":[45],"Big":[46],"Data":[47],"stacks,":[48],"such":[49],"as":[50],"Apache":[51],"Hadoop":[52],"and":[53,80,95,109,120,149,182,192],"Spark.":[54],"Even":[55],"though":[56],"a":[57,68,91],"lot":[58],"activities":[60],"are":[61,202],"happening":[62],"in":[63],"field,":[65],"there":[66,201],"lack":[69],"comprehensive":[71],"studies":[72],"on":[73,82,100,171,186,196],"analyzing":[74],"impact":[76],"RDMA-capable":[78],"networks":[79],"CPUs/GPUs":[81],"DLoBD":[83,103,130,211],"stacks.":[84,212],"To":[85],"fill":[86],"this":[87],"gap,":[88],"we":[89,166,198],"propose":[90],"systematical":[92],"characterization":[93],"methodology":[94],"conduct":[96],"extensive":[97],"performance":[98,179],"evaluations":[99],"four":[101],"representative":[102],"stacks":[104,131],"(i.e.,":[105],"CaffeOnSpark,":[106],"TensorFlowOnSpark,":[107,197],"MMLSpark/CNTKOnSpark,":[108],"BigDL)":[110],"expose":[112],"interesting":[114],"trends":[115],"regarding":[116],"performance,":[117],"scalability,":[118],"accuracy,":[119],"resource":[121],"utilization.":[122],"Our":[123],"observations":[124],"show":[125],"that":[126,168,200],"RDMA-based":[127],"design":[128],"for":[129,169],"can":[132,161,176],"achieve":[133,177],"up":[134],"2.7x":[136],"speedup":[137],"compared":[138],"IPoIB-based":[141],"scheme.":[142],"The":[143],"RDMA":[144],"scheme":[145],"also":[146],"scales":[147],"better":[148,178],"utilizes":[150],"resources":[151],"more":[152],"efficiently":[153],"than":[154,180],"IPoIB.":[155],"For":[156],"most":[157],"cases,":[158],"GPU-based":[159],"schemes":[160],"outperform":[162],"CPU-based":[163],"designs,":[164],"but":[165],"see":[167],"LeNet":[170],"MNIST,":[172],"CPU":[173],"+":[174,184],"MKL":[175],"GPU":[181,183],"cuDNN":[185],"16":[187],"nodes.":[188],"Through":[189],"our":[190],"evaluation":[191],"in-depth":[194],"analysis":[195],"find":[199],"large":[203],"rooms":[204],"improve":[206],"designs":[208],"current-generation":[210]},"counts_by_year":[{"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":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
