{"id":"https://openalex.org/W3193789877","doi":"https://doi.org/10.1145/3447548.3470816","title":"Simple and Automatic Distributed Machine Learning on Ray","display_name":"Simple and Automatic Distributed Machine Learning on Ray","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3193789877","doi":"https://doi.org/10.1145/3447548.3470816","mag":"3193789877"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3470816","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3470816","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","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/A5100396911","display_name":"Hao Zhang","orcid":"https://orcid.org/0000-0002-4527-9610"},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["UC Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009362721","display_name":"Zhuohan Li","orcid":"https://orcid.org/0000-0001-5372-9450"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]},{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhuohan Li","raw_affiliation_strings":["UC Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061339425","display_name":"Lianmin Zheng","orcid":"https://orcid.org/0000-0001-5812-731X"},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lianmin Zheng","raw_affiliation_strings":["UC Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041920173","display_name":"Ion Stoica","orcid":"https://orcid.org/0000-0002-5373-0088"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]},{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ion Stoica","raw_affiliation_strings":["UC Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100396911"],"corresponding_institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.11128729,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"4094","last_page":"4095"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.989300012588501,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.989300012588501,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9726999998092651,"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":0.843143105506897},{"id":"https://openalex.org/keywords/pace","display_name":"Pace","score":0.7094407677650452},{"id":"https://openalex.org/keywords/usability","display_name":"Usability","score":0.611661970615387},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4575274884700775},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4494839608669281},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4285825490951538},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.3709125518798828},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3590151369571686},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3201303780078888},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.29553481936454773}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.843143105506897},{"id":"https://openalex.org/C2777526511","wikidata":"https://www.wikidata.org/wiki/Q691543","display_name":"Pace","level":2,"score":0.7094407677650452},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.611661970615387},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4575274884700775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4494839608669281},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4285825490951538},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3709125518798828},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3590151369571686},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3201303780078888},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.29553481936454773},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447548.3470816","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3470816","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2339765813","https://openalex.org/W2626721309","https://openalex.org/W2734941459","https://openalex.org/W3080451848","https://openalex.org/W3100153641","https://openalex.org/W4212774754"],"related_works":["https://openalex.org/W2386723501","https://openalex.org/W2387879414","https://openalex.org/W2390304029","https://openalex.org/W2354923724","https://openalex.org/W2146830340","https://openalex.org/W2377101853","https://openalex.org/W2362180844","https://openalex.org/W2105573916","https://openalex.org/W2378405797","https://openalex.org/W4288601434"],"abstract_inverted_index":{"In":[0,131],"recent":[1],"years,":[2],"the":[3,8,63,78,167,186],"pace":[4],"of":[5,10,52,62,65,118,139,170],"innovations":[6],"in":[7,17,60,91,99,110,126],"fields":[9],"machine":[11],"learning":[12],"(ML)":[13],"has":[14],"accelerated,":[15],"researchers":[16],"SysML":[18],"have":[19,43],"created":[20],"algorithms":[21,119],"and":[22,67,96,106,114,120,129,153,158,172,178,182,188],"systems":[23,42,83,121],"that":[24],"parallelize":[25],"ML":[26,35,55,112,144,160],"training":[27,82,145],"over":[28],"multiple":[29],"devices":[30],"or":[31],"computational":[32],"nodes.":[33],"As":[34],"models":[36,86],"become":[37],"more":[38],"structurally":[39],"complex,":[40],"many":[41],"struggled":[44],"to":[45,70,77,84,93,156],"provide":[46],"all-round":[47],"performance":[48],"on":[49,122,148],"a":[50,136],"variety":[51],"models.":[53],"Particularly,":[54],"scale-up":[56],"is":[57,164],"usually":[58],"underestimated":[59],"terms":[61],"amount":[64],"knowledge":[66],"time":[68],"required":[69],"map":[71],"from":[72],"an":[73],"appropriate":[74],"distribution":[75],"strategy":[76],"model.":[79],"Applying":[80],"parallel":[81,111],"complex":[85],"adds":[87],"nontrivial":[88],"development":[89,117],"overheads":[90],"addition":[92],"model":[94],"prototyping,":[95],"often":[97],"results":[98],"lower-than-expected":[100],"performance.":[101,130],"This":[102,162],"tutorial":[103,134,163],"identifies":[104],"research":[105,171],"practical":[107],"pain":[108],"points":[109],"training,":[113],"discusses":[115],"latest":[116,180],"addressing":[123],"these":[124],"challenges":[125],"both":[127],"usability":[128],"particular,":[132],"this":[133],"presents":[135],"new":[137,151],"perspective":[138],"unifying":[140],"seemingly":[141],"different":[142],"distributed":[143],"strategies.":[146],"Based":[147],"it,":[149],"introduces":[150],"techniques":[152],"system":[154],"architectures":[155],"simplify":[157],"automate":[159],"parallelization.":[161],"built":[165],"upon":[166],"authors'":[168],"years'":[169],"industry":[173],"experience,":[174],"comprehensive":[175],"literature":[176],"survey,":[177],"several":[179],"tutorials":[181],"papers":[183],"published":[184],"by":[185],"authors":[187],"peer":[189],"researchers.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}