{"id":"https://openalex.org/W2964330541","doi":"https://doi.org/10.1109/iiswc.2018.8573476","title":"Benchmarking and Analyzing Deep Neural Network Training","display_name":"Benchmarking and Analyzing Deep Neural Network Training","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2964330541","doi":"https://doi.org/10.1109/iiswc.2018.8573476","mag":"2964330541"},"language":"en","primary_location":{"id":"doi:10.1109/iiswc.2018.8573476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iiswc.2018.8573476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Symposium on Workload Characterization (IISWC)","raw_type":"proceedings-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/A5085361149","display_name":"Hongyu Zhu","orcid":"https://orcid.org/0009-0002-2803-6980"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Hongyu Zhu","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043530847","display_name":"Mohamed Akrout","orcid":"https://orcid.org/0000-0001-8031-1543"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohamed Akrout","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053912518","display_name":"Bojian Zheng","orcid":"https://orcid.org/0000-0002-1999-2359"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Bojian Zheng","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054068671","display_name":"Andrew Pelegris","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Andrew Pelegris","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022583753","display_name":"Anand Jayarajan","orcid":"https://orcid.org/0000-0002-2118-5935"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Anand Jayarajan","raw_affiliation_strings":["University of British Columbia, Vancouver, Canada"],"affiliations":[{"raw_affiliation_string":"University of British Columbia, Vancouver, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011102459","display_name":"Amar Phanishayee","orcid":"https://orcid.org/0009-0001-2777-1118"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amar Phanishayee","raw_affiliation_strings":["Microsoft Research, Redmond, United States"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, United States","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040893798","display_name":"Bianca Schroeder","orcid":"https://orcid.org/0000-0003-3289-1824"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Bianca Schroeder","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007585346","display_name":"Gennady Pekhimenko","orcid":"https://orcid.org/0000-0002-3839-0919"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Gennady Pekhimenko","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5085361149"],"corresponding_institution_ids":["https://openalex.org/I185261750"],"apc_list":null,"apc_paid":null,"fwci":15.3707,"has_fulltext":false,"cited_by_count":155,"citation_normalized_percentile":{"value":0.99118626,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"88","last_page":"100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.998199999332428,"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/computer-science","display_name":"Computer science","score":0.8540948033332825},{"id":"https://openalex.org/keywords/toolchain","display_name":"Toolchain","score":0.7518504858016968},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7158882021903992},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6614685654640198},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6445819735527039},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6225590705871582},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5387341380119324},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5194975137710571},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5109376311302185},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.46023014187812805},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4568212628364563},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.4543352723121643},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4520367383956909},{"id":"https://openalex.org/keywords/workspace","display_name":"Workspace","score":0.4474770426750183},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.21482053399085999},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.13420453667640686}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8540948033332825},{"id":"https://openalex.org/C2777062904","wikidata":"https://www.wikidata.org/wiki/Q545406","display_name":"Toolchain","level":3,"score":0.7518504858016968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7158882021903992},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6614685654640198},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6445819735527039},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6225590705871582},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5387341380119324},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5194975137710571},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5109376311302185},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.46023014187812805},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4568212628364563},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.4543352723121643},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4520367383956909},{"id":"https://openalex.org/C58581272","wikidata":"https://www.wikidata.org/wiki/Q12741163","display_name":"Workspace","level":3,"score":0.4474770426750183},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.21482053399085999},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.13420453667640686},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iiswc.2018.8573476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iiswc.2018.8573476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Symposium on Workload Characterization (IISWC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":131,"referenced_works":["https://openalex.org/W182691100","https://openalex.org/W639708223","https://openalex.org/W753012316","https://openalex.org/W1442374986","https://openalex.org/W1494198834","https://openalex.org/W1585377561","https://openalex.org/W1667652561","https://openalex.org/W1902237438","https://openalex.org/W2031489346","https://openalex.org/W2060393849","https://openalex.org/W2067523571","https://openalex.org/W2083842231","https://openalex.org/W2101105183","https://openalex.org/W2110798204","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2119144962","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2136922672","https://openalex.org/W2142801765","https://openalex.org/W2145339207","https://openalex.org/W2152175008","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2168231600","https://openalex.org/W2181607856","https://openalex.org/W2183341477","https://openalex.org/W2186615578","https://openalex.org/W2193413348","https://openalex.org/W2194775991","https://openalex.org/W2237922334","https://openalex.org/W2257408573","https://openalex.org/W2285660444","https://openalex.org/W2289252105","https://openalex.org/W2331737637","https://openalex.org/W2342840547","https://openalex.org/W2402144811","https://openalex.org/W2442974303","https://openalex.org/W2466675884","https://openalex.org/W2489529491","https://openalex.org/W2508602506","https://openalex.org/W2511743527","https://openalex.org/W2512971201","https://openalex.org/W2515080096","https://openalex.org/W2516141709","https://openalex.org/W2518281301","https://openalex.org/W2518511512","https://openalex.org/W2519224033","https://openalex.org/W2525778437","https://openalex.org/W2541839172","https://openalex.org/W2551814622","https://openalex.org/W2560912757","https://openalex.org/W2562773490","https://openalex.org/W2563587242","https://openalex.org/W2565851976","https://openalex.org/W2604783387","https://openalex.org/W2605277971","https://openalex.org/W2605347906","https://openalex.org/W2605350416","https://openalex.org/W2606722458","https://openalex.org/W2606833507","https://openalex.org/W2612076670","https://openalex.org/W2613989746","https://openalex.org/W2616028256","https://openalex.org/W2622263826","https://openalex.org/W2625457103","https://openalex.org/W2626991402","https://openalex.org/W2647836899","https://openalex.org/W2657126969","https://openalex.org/W2741430497","https://openalex.org/W2751366252","https://openalex.org/W2765927961","https://openalex.org/W2778814079","https://openalex.org/W2883283076","https://openalex.org/W2899771611","https://openalex.org/W2905927205","https://openalex.org/W2906043559","https://openalex.org/W2953384591","https://openalex.org/W2953830716","https://openalex.org/W2962747323","https://openalex.org/W2962879692","https://openalex.org/W2963403868","https://openalex.org/W2963674387","https://openalex.org/W2964043796","https://openalex.org/W2964174152","https://openalex.org/W2964299589","https://openalex.org/W2964308564","https://openalex.org/W3082674894","https://openalex.org/W3104393472","https://openalex.org/W3105753409","https://openalex.org/W4239722617","https://openalex.org/W4240168186","https://openalex.org/W4242577057","https://openalex.org/W4247198796","https://openalex.org/W4247624284","https://openalex.org/W4249932213","https://openalex.org/W4295521014","https://openalex.org/W4297666078","https://openalex.org/W4302296459","https://openalex.org/W4385245566","https://openalex.org/W6607408290","https://openalex.org/W6620707391","https://openalex.org/W6622239757","https://openalex.org/W6635292102","https://openalex.org/W6637151318","https://openalex.org/W6665801690","https://openalex.org/W6676481782","https://openalex.org/W6677580257","https://openalex.org/W6679434410","https://openalex.org/W6679436768","https://openalex.org/W6682825348","https://openalex.org/W6684191040","https://openalex.org/W6684859321","https://openalex.org/W6686509673","https://openalex.org/W6687566353","https://openalex.org/W6692846177","https://openalex.org/W6704559304","https://openalex.org/W6713134421","https://openalex.org/W6719559416","https://openalex.org/W6735913928","https://openalex.org/W6736126653","https://openalex.org/W6736413256","https://openalex.org/W6739622702","https://openalex.org/W6739901393","https://openalex.org/W6741978826","https://openalex.org/W6743955621","https://openalex.org/W6746857927","https://openalex.org/W6757517122","https://openalex.org/W6779669310","https://openalex.org/W6898505805"],"related_works":["https://openalex.org/W2013037783","https://openalex.org/W2909413202","https://openalex.org/W1999008563","https://openalex.org/W4385243142","https://openalex.org/W2561644314","https://openalex.org/W2794118724","https://openalex.org/W2912135124","https://openalex.org/W4206450104","https://openalex.org/W2883257033","https://openalex.org/W2122191294"],"abstract_inverted_index":{"The":[0],"recent":[1],"popularity":[2],"of":[3,84,114,150,157,172],"deep":[4,120],"neural":[5],"networks":[6,44],"(DNNs)":[7],"has":[8],"generated":[9],"considerable":[10],"research":[11,221],"interest":[12],"in":[13,54,177,201],"performing":[14,109],"DNN-related":[15],"computation":[16],"efficiently.":[17],"However,":[18],"the":[19,46,147,164],"primary":[20,47,52],"focus":[21],"is":[22,57,191],"usually":[23],"very":[24],"narrow":[25],"and":[26,40,88,107,132,160,207,214,222],"limited":[27],"to":[28,34,58,162],"(i)":[29,64],"inference":[30],"-":[31],"i.e.":[32],"how":[33,188],"efficiently":[35],"execute":[36],"already":[37],"trained":[38],"models":[39,87,116,144],"(ii)":[41,108],"image":[42,95],"classification":[43],"as":[45],"benchmark":[48,68],"for":[49,70,139,142,174],"evaluation.":[50],"Our":[51],"goal":[53],"this":[55,60],"work":[56],"break":[59],"myopic":[61],"view":[62],"by":[63,193],"proposing":[65],"a":[66,81,136,169],"new":[67,137,170],"suite":[69],"DNN":[71,86,202,219],"training,":[72],"called":[73],"TBD":[74],"<sup":[75],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[76],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[77],",":[78],"which":[79],"comprises":[80],"representative":[82],"set":[83,171],"eight":[85],"covers":[89],"six":[90],"major":[91,119,179],"machine":[92,97],"learning":[93,121],"applications:":[94],"classification,":[96],"translation,":[98],"speech":[99],"recognition,":[100],"object":[101],"detection,":[102],"adversarial":[103],"networks,":[104],"reinforcement":[105],"learning,":[106],"an":[110],"extensive":[111],"performance":[112,140,152,158],"analysis":[113,141,153],"these":[115,143],"on":[117,186,216],"three":[118,178],"frameworks":[122],"(TensorFlow,":[123],"MXNet,":[124],"CNTK)":[125],"across":[126],"different":[127,194],"hardware":[128],"configurations":[129],"(single-GPU,":[130],"multi-GPU,":[131],"multi-machine).":[133],"We":[134,166],"present":[135],"toolchain":[138],"that":[145],"combines":[146],"targeted":[148],"usage":[149],"existing":[151],"tools,":[154],"careful":[155],"selection":[156],"metrics,":[159],"methodologies":[161],"analyze":[163],"results.":[165],"also":[167],"build":[168],"tools":[173,182,206],"memory":[175,190],"profiling":[176],"frameworks.":[180],"These":[181],"can":[183],"shed":[184],"light":[185],"precisely":[187],"much":[189],"consumed":[192],"data":[195],"structures":[196],"(weights,":[197],"activations,":[198],"gradients,":[199],"workspace)":[200],"training.":[203],"Using":[204],"our":[205],"methodologies,":[208],"we":[209],"make":[210],"several":[211],"important":[212],"observations":[213],"recommendations":[215],"where":[217],"future":[218],"training":[220],"optimization":[223],"should":[224],"be":[225],"focused.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":32},{"year":2019,"cited_by_count":32},{"year":2018,"cited_by_count":7}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
