{"id":"https://openalex.org/W4290996544","doi":"https://doi.org/10.1109/icc45855.2022.9839126","title":"PipeCompress: Accelerating Pipelined Communication for Distributed Deep Learning","display_name":"PipeCompress: Accelerating Pipelined Communication for Distributed Deep Learning","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4290996544","doi":"https://doi.org/10.1109/icc45855.2022.9839126"},"language":"en","primary_location":{"id":"doi:10.1109/icc45855.2022.9839126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9839126","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","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/A5015855316","display_name":"Juncai Liu","orcid":"https://orcid.org/0000-0001-5783-731X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I2802444338","display_name":"King Center","ror":"https://ror.org/03nxex423","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2802444338"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Juncai Liu","raw_affiliation_strings":["Tsinghua University,Institute for Network Sciences and Cyberspace, BNRist,China","Institute for Network Sciences and Cyberspace, BNRist, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Institute for Network Sciences and Cyberspace, BNRist,China","institution_ids":["https://openalex.org/I2802444338"]},{"raw_affiliation_string":"Institute for Network Sciences and Cyberspace, BNRist, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075088248","display_name":"Jessie Hui Wang","orcid":"https://orcid.org/0000-0002-7825-4137"},"institutions":[{"id":"https://openalex.org/I2802444338","display_name":"King Center","ror":"https://ror.org/03nxex423","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2802444338"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jessie Hui Wang","raw_affiliation_strings":["Tsinghua University,Institute for Network Sciences and Cyberspace, BNRist,China","Institute for Network Sciences and Cyberspace, BNRist, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Institute for Network Sciences and Cyberspace, BNRist,China","institution_ids":["https://openalex.org/I2802444338"]},{"raw_affiliation_string":"Institute for Network Sciences and Cyberspace, BNRist, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041059888","display_name":"Chenghao Rong","orcid":"https://orcid.org/0000-0001-8685-6077"},"institutions":[{"id":"https://openalex.org/I2802444338","display_name":"King Center","ror":"https://ror.org/03nxex423","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2802444338"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Chenghao Rong","raw_affiliation_strings":["Tsinghua University,Institute for Network Sciences and Cyberspace, BNRist,China","Institute for Network Sciences and Cyberspace, BNRist, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Institute for Network Sciences and Cyberspace, BNRist,China","institution_ids":["https://openalex.org/I2802444338"]},{"raw_affiliation_string":"Institute for Network Sciences and Cyberspace, BNRist, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100660341","display_name":"Jilong Wang","orcid":"https://orcid.org/0000-0001-5899-603X"},"institutions":[{"id":"https://openalex.org/I2802444338","display_name":"King Center","ror":"https://ror.org/03nxex423","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2802444338"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jilong Wang","raw_affiliation_strings":["Tsinghua University,Institute for Network Sciences and Cyberspace, BNRist,China","Institute for Network Sciences and Cyberspace, BNRist, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Institute for Network Sciences and Cyberspace, BNRist,China","institution_ids":["https://openalex.org/I2802444338"]},{"raw_affiliation_string":"Institute for Network Sciences and Cyberspace, BNRist, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015855316"],"corresponding_institution_ids":["https://openalex.org/I2802444338","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06060174,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"207","last_page":"212"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9994000196456909,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9979000091552734,"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":0.8448383808135986},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6515670418739319},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6167929172515869},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5325692296028137},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5193361043930054},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4671197831630707},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4411260783672333},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4389660358428955},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4317203760147095},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.42263612151145935},{"id":"https://openalex.org/keywords/communications-system","display_name":"Communications system","score":0.4163312315940857},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3396252393722534},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.29776501655578613},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.18807625770568848},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.18116161227226257}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8448383808135986},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6515670418739319},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6167929172515869},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5325692296028137},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5193361043930054},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4671197831630707},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4411260783672333},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4389660358428955},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4317203760147095},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.42263612151145935},{"id":"https://openalex.org/C101765175","wikidata":"https://www.wikidata.org/wiki/Q577764","display_name":"Communications system","level":2,"score":0.4163312315940857},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3396252393722534},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29776501655578613},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.18807625770568848},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.18116161227226257},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc45855.2022.9839126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9839126","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2097117768","https://openalex.org/W2194775991","https://openalex.org/W2407022425","https://openalex.org/W2617766261","https://openalex.org/W2769644379","https://openalex.org/W2774000609","https://openalex.org/W2962758826","https://openalex.org/W2963403751","https://openalex.org/W2963766684","https://openalex.org/W2963786636","https://openalex.org/W2975712713","https://openalex.org/W2990061623","https://openalex.org/W3004495293","https://openalex.org/W3047357290","https://openalex.org/W3047537431","https://openalex.org/W4288357791","https://openalex.org/W6637373629","https://openalex.org/W6714239094","https://openalex.org/W6738460352","https://openalex.org/W6739693220","https://openalex.org/W6746200960","https://openalex.org/W6746839373","https://openalex.org/W6754341472","https://openalex.org/W6754416507","https://openalex.org/W6758283263","https://openalex.org/W6762211661","https://openalex.org/W6770379276"],"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":{"Distributed":[0],"learning":[1,11,25],"is":[2,15,45,56,72,156],"widely":[3],"used":[4],"to":[5,34,64,90,104,124,172],"accelerate":[6,192],"the":[7,21,39,53,60,101,118,126,132,139,157,162,193],"training":[8,123,194],"of":[9,23,120,128,164],"deep":[10],"models,":[12],"but":[13,38,69],"it":[14,75],"known":[16],"that":[17,138,160,181],"communication":[18,36,54,114,147],"efficiency":[19,127],"limits":[20],"scalability":[22],"distributed":[24,122,177],"systems.":[26],"Current":[27],"gradient":[28],"compression":[29,44,49,92,106,165,170,174,186],"techniques":[30,50],"provide":[31],"promising":[32],"methods":[33],"reduce":[35,188],"time,":[37,187,190],"extra":[40,145],"time":[41,55,148,175],"incurred":[42],"by":[43],"not":[46,142],"negligible.":[47],"After":[48],"are":[51],"applied,":[52],"significantly":[57,184],"reduced":[58],"because":[59],"data":[61],"size":[62],"needed":[63],"communicate":[65],"becomes":[66,76],"much":[67,144],"smaller,":[68],"compressing":[70],"gradients":[71],"time-consuming":[73],"and":[74,85,93,99,166,169,191],"a":[77,88,111],"new":[78],"bottleneck.":[79],"In":[80],"this":[81,155],"paper,":[82],"we":[83,153],"design":[84],"implement":[86],"PipeCompress,":[87],"system":[89],"decouple":[91],"backpropagation":[94,168],"operations":[95,171],"into":[96],"two":[97,102,133],"processes":[98,103],"pipeline":[100],"hide":[105,173,185],"time.":[107],"We":[108],"also":[109],"propose":[110],"specialized":[112],"inter-process":[113,146],"mechanism":[115],"based":[116],"on":[117,196],"characteristics":[119],"DNN":[121,198],"improve":[125],"passing":[129],"messages":[130],"between":[131],"processes,":[134],"which":[135],"makes":[136],"sure":[137],"decoupling":[140],"does":[141],"bring":[143],"cost.":[149],"As":[150],"far":[151],"as":[152],"know,":[154],"first":[158],"work":[159],"notices":[161],"overhead":[163],"pipelines":[167],"in":[176],"learning.":[178],"Experiments":[179],"show":[180],"PipeCompress":[182],"can":[183],"iteration":[189],"process":[195],"various":[197],"models.":[199]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
