{"id":"https://openalex.org/W2753217274","doi":"https://doi.org/10.1147/jrd.2017.2709198","title":"Wildfire: Approximate synchronization of parameters in distributed deep learning","display_name":"Wildfire: Approximate synchronization of parameters in distributed deep learning","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2753217274","doi":"https://doi.org/10.1147/jrd.2017.2709198","mag":"2753217274"},"language":"en","primary_location":{"id":"doi:10.1147/jrd.2017.2709198","is_oa":false,"landing_page_url":"https://doi.org/10.1147/jrd.2017.2709198","pdf_url":null,"source":{"id":"https://openalex.org/S4210219925","display_name":"IBM Journal of Research and Development","issn_l":"0018-8646","issn":["0018-8646","2151-8556"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320652","host_organization_name":"IBM","host_organization_lineage":["https://openalex.org/P4310320652"],"host_organization_lineage_names":["IBM"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IBM Journal of Research and Development","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/A5022200143","display_name":"R. Nair","orcid":"https://orcid.org/0009-0006-4303-8270"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. Nair","raw_affiliation_strings":["IBM Research, Thomas J. Watson Research Center, Yorktown Heights, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research, Thomas J. Watson Research Center, Yorktown Heights, NY","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040211080","display_name":"Saurabh Gupta","orcid":"https://orcid.org/0000-0003-0095-4704"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S. Gupta","raw_affiliation_strings":["Google Mountain View, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Mountain View, CA","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7944,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.88911665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"61","issue":"4/5","first_page":"7:1","last_page":"7:9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9988999962806702,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9988999962806702,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9977999925613403,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.8570093512535095},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.737930178642273},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6713453531265259},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.6302403211593628},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6066124439239502},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5589867830276489},{"id":"https://openalex.org/keywords/ibm","display_name":"IBM","score":0.5335165858268738},{"id":"https://openalex.org/keywords/synchronization","display_name":"Synchronization (alternating current)","score":0.5201864242553711},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.5157740116119385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4834038317203522},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.46281754970550537},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3617636561393738},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3407953381538391},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.13806363940238953},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09559273719787598},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08163118362426758}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8570093512535095},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.737930178642273},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6713453531265259},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.6302403211593628},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6066124439239502},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5589867830276489},{"id":"https://openalex.org/C70388272","wikidata":"https://www.wikidata.org/wiki/Q5968558","display_name":"IBM","level":2,"score":0.5335165858268738},{"id":"https://openalex.org/C2778562939","wikidata":"https://www.wikidata.org/wiki/Q1298791","display_name":"Synchronization (alternating current)","level":3,"score":0.5201864242553711},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.5157740116119385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4834038317203522},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.46281754970550537},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3617636561393738},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3407953381538391},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.13806363940238953},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09559273719787598},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08163118362426758},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1147/jrd.2017.2709198","is_oa":false,"landing_page_url":"https://doi.org/10.1147/jrd.2017.2709198","pdf_url":null,"source":{"id":"https://openalex.org/S4210219925","display_name":"IBM Journal of Research and Development","issn_l":"0018-8646","issn":["0018-8646","2151-8556"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320652","host_organization_name":"IBM","host_organization_lineage":["https://openalex.org/P4310320652"],"host_organization_lineage_names":["IBM"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IBM Journal of Research and Development","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6800000071525574}],"awards":[{"id":"https://openalex.org/G1370957883","display_name":null,"funder_award_id":"FA8750-15-C-0125","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320307762","display_name":"International Business Machines Corporation","ror":"https://ror.org/05hh8d621"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W778657980","https://openalex.org/W1442374986","https://openalex.org/W1498436455","https://openalex.org/W1825216778","https://openalex.org/W1836465849","https://openalex.org/W1841592590","https://openalex.org/W1905882502","https://openalex.org/W1922655562","https://openalex.org/W2019145120","https://openalex.org/W2036816792","https://openalex.org/W2038562061","https://openalex.org/W2113651538","https://openalex.org/W2117539524","https://openalex.org/W2132560615","https://openalex.org/W2147800946","https://openalex.org/W2154834860","https://openalex.org/W2155893237","https://openalex.org/W2158899491","https://openalex.org/W2160815625","https://openalex.org/W2168231600","https://openalex.org/W2170135819","https://openalex.org/W2182646236","https://openalex.org/W2194775991","https://openalex.org/W2221532093","https://openalex.org/W2405578611","https://openalex.org/W2618530766","https://openalex.org/W2919115771","https://openalex.org/W2949117887","https://openalex.org/W2952033860","https://openalex.org/W2952230511","https://openalex.org/W2962911728","https://openalex.org/W2962950660","https://openalex.org/W2963374099","https://openalex.org/W2963804082","https://openalex.org/W2963903325","https://openalex.org/W3118608800","https://openalex.org/W6622473587","https://openalex.org/W6628377381","https://openalex.org/W6638667902","https://openalex.org/W6638783484","https://openalex.org/W6638803421","https://openalex.org/W6640090968","https://openalex.org/W6662929504","https://openalex.org/W6683738474","https://openalex.org/W6684859321","https://openalex.org/W6685932935","https://openalex.org/W6688899064","https://openalex.org/W6692488971","https://openalex.org/W6713835734","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W4382618745","https://openalex.org/W1973775000","https://openalex.org/W2748922771","https://openalex.org/W1987128138","https://openalex.org/W2743976221"],"abstract_inverted_index":{"In":[0,91],"distributed":[1],"deep":[2,147,185,192],"learning":[3,29,135,148,186,193],"approaches,":[4],"contributions":[5,33],"to":[6,23,56,136,152,171],"changes":[7],"in":[8,39,48,84,87,122,146],"the":[9,28,52,68,72,75,78,116,123,134,139,143,166,179,189],"parameter":[10,42,53,79,161],"values":[11],"from":[12,60,119],"multiple":[13],"learners":[14,62,76,121,128,151,169],"are":[15],"gathered":[16],"at":[17,34,130],"periodic":[18],"intervals":[19],"and":[20,66,77,163],"collectively":[21],"used":[22],"update":[24],"weights":[25,102],"associated":[26],"with":[27],"network.":[30],"Gathering":[31],"these":[32],"a":[35,46,96,160],"centralized":[36],"location,":[37],"as":[38],"common":[40,89,184],"synchronous":[41],"server":[43,54,80],"models,":[44],"causes":[45,81],"bottleneck":[47],"two":[49],"ways.":[50],"First,":[51],"needs":[55],"wait":[57,172],"until":[58],"gradients":[59,73],"all":[61],"have":[63],"been":[64],"received,":[65],"second,":[67],"traffic":[69],"pattern":[70],"of":[71,105,109,127,181],"between":[74],"an":[82],"imbalance":[83],"bandwidth":[85],"utilization":[86],"most":[88],"networks.":[90],"this":[92],"paper,":[93],"we":[94],"introduce":[95],"scheme":[97],"called":[98],"Wildfire,":[99],"which":[100,110],"communicates":[101],"among":[103,155],"subsets":[104,126],"parallel":[106],"learners,":[107],"each":[108],"updates":[111],"its":[112],"model":[113],"using":[114,188],"only":[115],"information":[117],"received":[118],"other":[120],"subset.":[124],"Different":[125],"communicate":[129,153],"different":[131],"times,":[132],"allowing":[133,150],"diffuse":[137],"through":[138,159],"system.":[140],"Wildfire":[141,182],"reduces":[142],"communication":[144],"overhead":[145],"by":[149,164],"directly":[154],"themselves":[156],"rather":[157],"than":[158],"server,":[162],"limiting":[165],"time":[167],"that":[168],"need":[170],"before":[173],"updating":[174],"their":[175],"models.":[176],"We":[177],"demonstrate":[178],"effectiveness":[180],"on":[183],"benchmarks,":[187],"IBM":[190],"Rudra":[191],"framework.":[194]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
