{"id":"https://openalex.org/W4383749677","doi":"https://doi.org/10.1109/ccgrid57682.2023.00033","title":"Chronica: A Data-Imbalance-Aware Scheduler for Distributed Deep Learning","display_name":"Chronica: A Data-Imbalance-Aware Scheduler for Distributed Deep Learning","publication_year":2023,"publication_date":"2023-05-01","ids":{"openalex":"https://openalex.org/W4383749677","doi":"https://doi.org/10.1109/ccgrid57682.2023.00033"},"language":"en","primary_location":{"id":"doi:10.1109/ccgrid57682.2023.00033","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ccgrid57682.2023.00033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid)","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/A5108872893","display_name":"Sanha Maeng","orcid":null},"institutions":[{"id":"https://openalex.org/I148751991","display_name":"Sogang University","ror":"https://ror.org/056tn4839","country_code":"KR","type":"education","lineage":["https://openalex.org/I148751991"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sanha Maeng","raw_affiliation_strings":["Sogang University,Seoul,Republic of Korea","Sogang University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sogang University,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I148751991"]},{"raw_affiliation_string":"Sogang University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I148751991"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023057376","display_name":"Gordon Euhyun Moon","orcid":"https://orcid.org/0000-0003-4992-6181"},"institutions":[{"id":"https://openalex.org/I148751991","display_name":"Sogang University","ror":"https://ror.org/056tn4839","country_code":"KR","type":"education","lineage":["https://openalex.org/I148751991"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gordon Euhyun Moon","raw_affiliation_strings":["Sogang University,Seoul,Republic of Korea","Sogang University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sogang University,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I148751991"]},{"raw_affiliation_string":"Sogang University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I148751991"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101413142","display_name":"Sungyong Park","orcid":"https://orcid.org/0000-0002-0309-1820"},"institutions":[{"id":"https://openalex.org/I148751991","display_name":"Sogang University","ror":"https://ror.org/056tn4839","country_code":"KR","type":"education","lineage":["https://openalex.org/I148751991"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sungyong Park","raw_affiliation_strings":["Sogang University,Seoul,Republic of Korea","Sogang University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sogang University,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I148751991"]},{"raw_affiliation_string":"Sogang University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I148751991"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06651552,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"262","last_page":"272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9976999759674072,"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":0.8384155035018921},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6186436414718628},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5904605388641357},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5280906558036804},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5093063116073608},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.49324101209640503},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.41688382625579834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40211260318756104},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3630602955818176},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.25325149297714233},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09619763493537903}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8384155035018921},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6186436414718628},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5904605388641357},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5280906558036804},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5093063116073608},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.49324101209640503},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.41688382625579834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40211260318756104},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3630602955818176},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.25325149297714233},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09619763493537903},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccgrid57682.2023.00033","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ccgrid57682.2023.00033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5400000214576721,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W174240283","https://openalex.org/W1522301498","https://openalex.org/W1595545560","https://openalex.org/W1686810756","https://openalex.org/W1994616650","https://openalex.org/W2016053056","https://openalex.org/W2101234009","https://openalex.org/W2194775991","https://openalex.org/W2336650964","https://openalex.org/W2337252826","https://openalex.org/W2470139095","https://openalex.org/W2523435939","https://openalex.org/W2524365899","https://openalex.org/W2592463526","https://openalex.org/W2782985982","https://openalex.org/W2801490189","https://openalex.org/W2803187616","https://openalex.org/W2936343019","https://openalex.org/W2964094654","https://openalex.org/W2964199361","https://openalex.org/W2972087877","https://openalex.org/W2994508843","https://openalex.org/W2996489182","https://openalex.org/W3036703963","https://openalex.org/W3112048118","https://openalex.org/W3125012172","https://openalex.org/W3132294480","https://openalex.org/W3188013984","https://openalex.org/W3204998121","https://openalex.org/W4224229551","https://openalex.org/W4292779060","https://openalex.org/W4297775537","https://openalex.org/W6600983433","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6675354045","https://openalex.org/W6685140790","https://openalex.org/W6703420464","https://openalex.org/W6713134421","https://openalex.org/W6728047685","https://openalex.org/W6737664043","https://openalex.org/W6751420435","https://openalex.org/W6762718338","https://openalex.org/W6771982476","https://openalex.org/W6778883912","https://openalex.org/W6790565284"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W2597809628","https://openalex.org/W3046370962"],"abstract_inverted_index":{"One":[0],"of":[1,23,43,86,93,112,138],"the":[2,21,31,36,41,44,65,70,84,87,91,98,113,135,139,161,170],"major":[3],"challenges":[4],"in":[5],"distributed":[6],"deep":[7,24,45,150],"learning":[8,25,46,151],"is":[9],"attenuating":[10],"straggler":[11,14,37,66,71,120],"problem.":[12,67],"The":[13],"increases":[15],"synchronization":[16,127],"latency":[17],"and":[18,39,55,72,90,118],"significantly":[19],"inhibits":[20],"convergence":[22,42,132],"model.":[26],"We":[27],"empirically":[28],"observe":[29],"that":[30,160],"imbal-anced":[32],"data":[33,60,73,88],"samples":[34,89],"worsen":[35],"problem":[38],"make":[40],"model":[47],"slower.":[48],"However,":[49],"existing":[50],"approaches":[51],"such":[52],"as":[53],"BOA":[54],"EP4DDL":[56],"have":[57],"not":[58],"addressed":[59],"imbalance":[61,74],"issues":[62],"while":[63],"solving":[64],"To":[68],"overcome":[69],"problems,":[75],"we":[76],"propose":[77],"Chronica,a":[78],"new":[79,125,162],"data-imbalance-aware":[80],"scheduler.":[81],"Based":[82],"on":[83,134,142,153],"size":[85],"configuration":[92],"each":[94,103,111,143],"worker,":[95],"Chronicaelaborately":[96],"predicts":[97],"training":[99,108,140],"time":[100,109],"required":[101],"for":[102],"worker.":[104,144],"Chronicathen":[105],"provides":[106],"equivalent":[107],"to":[110,129,165],"workers,":[114],"alleviating":[115],"both":[116],"step-":[117],"epoch-level":[119],"problems.":[121],"Furthermore,":[122],"Chronicasuggests":[123],"a":[124],"parameter":[126],"scheme":[128],"achieve":[130],"fast":[131],"based":[133],"weighted":[136],"average":[137],"workload":[141],"Our":[145],"extensive":[146],"evaluation":[147],"using":[148],"four":[149],"models":[152],"32":[154],"Amazon":[155],"EC2":[156],"GPU":[157],"instances":[158],"showed":[159],"Chronicaachieves":[163],"up":[164],"3.19":[166],"times":[167],"speedup":[168],"over":[169],"state-of-the-art":[171],"systems.":[172]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
