{"id":"https://openalex.org/W4386710073","doi":"https://doi.org/10.1145/3605573.3605610","title":"PSRA-HGADMM: A Communication Efficient Distributed ADMM Algorithm","display_name":"PSRA-HGADMM: A Communication Efficient Distributed ADMM Algorithm","publication_year":2023,"publication_date":"2023-08-07","ids":{"openalex":"https://openalex.org/W4386710073","doi":"https://doi.org/10.1145/3605573.3605610"},"language":"en","primary_location":{"id":"doi:10.1145/3605573.3605610","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3605573.3605610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd International Conference on Parallel Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102008953","display_name":"Yongwen Qiu","orcid":"https://orcid.org/0000-0002-8709-1034"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongwen Qiu","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, China"],"raw_orcid":"https://orcid.org/0000-0002-8709-1034","affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105771087","display_name":"Y. J. Lei","orcid":"https://orcid.org/0009-0008-8010-5545"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongmei Lei","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, China"],"raw_orcid":"https://orcid.org/0009-0008-8010-5545","affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022048706","display_name":"Guozheng Wang","orcid":"https://orcid.org/0000-0002-5260-3458"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guozheng Wang","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, China"],"raw_orcid":"https://orcid.org/0000-0002-5260-3458","affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, China","institution_ids":["https://openalex.org/I141962983"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I141962983"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"82","last_page":"91"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9993000030517578,"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/T12676","display_name":"Machine Learning and ELM","score":0.9993000030517578,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.9955999851226807,"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/scalability","display_name":"Scalability","score":0.8554258346557617},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8276315331459045},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6651119589805603},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5805692076683044},{"id":"https://openalex.org/keywords/distributed-algorithm","display_name":"Distributed algorithm","score":0.5452755689620972},{"id":"https://openalex.org/keywords/algorithm-design","display_name":"Algorithm design","score":0.4119069576263428},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3539784550666809}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8554258346557617},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8276315331459045},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6651119589805603},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5805692076683044},{"id":"https://openalex.org/C130120984","wikidata":"https://www.wikidata.org/wiki/Q2835898","display_name":"Distributed algorithm","level":2,"score":0.5452755689620972},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.4119069576263428},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3539784550666809},{"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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3605573.3605610","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3605573.3605610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd International Conference on Parallel Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2045271686","https://openalex.org/W2097117768","https://openalex.org/W2129191766","https://openalex.org/W2132737349","https://openalex.org/W2164278908","https://openalex.org/W2193413348","https://openalex.org/W2550821151","https://openalex.org/W2559655401","https://openalex.org/W2612139288","https://openalex.org/W2734941459","https://openalex.org/W2911382970","https://openalex.org/W2972934812","https://openalex.org/W2975481252","https://openalex.org/W2982191236","https://openalex.org/W3000095577","https://openalex.org/W3120950563","https://openalex.org/W3175007265"],"related_works":["https://openalex.org/W1982914007","https://openalex.org/W2159583675","https://openalex.org/W1824242903","https://openalex.org/W1493858311","https://openalex.org/W2155470929","https://openalex.org/W2394465510","https://openalex.org/W2111125783","https://openalex.org/W1544070555","https://openalex.org/W4255666353","https://openalex.org/W17303578"],"abstract_inverted_index":{"Among":[0],"distributed":[1,87,139],"machine":[2],"learning":[3],"algorithms,":[4],"the":[5,27,39,61,65,70,76,82,86,99,115,130,135,138,159],"global":[6,71],"consensus":[7,72],"alternating":[8],"direction":[9],"method":[10],"of":[11,64,85,101,117,119,137,163],"multipliers":[12],"(ADMM)":[13],"has":[14,145],"attracted":[15],"much":[16],"attention":[17],"because":[18],"it":[19],"can":[20],"effectively":[21],"solve":[22,38,114],"large-scale":[23],"optimization":[24],"problems.":[25],"However,":[26],"high":[28],"communication":[29,53,83,94,161],"cost":[30,162],"slows":[31],"its":[32],"convergence":[33,147],"and":[34,68,128,149,154],"limits":[35],"scalability.":[36],"To":[37],"problem,":[40],"we":[41,59,89],"propose":[42,90],"a":[43,50,91,106],"hierarchical":[44,125],"grouping":[45,131],"ADMM":[46,66,73],"algorithm":[47,67,74],"(PSRA-HGADMM)":[48],"with":[49,157],"novel":[51,92],"Ring-Allreduce":[52,93],"model":[54,95],"in":[55,75],"this":[56],"paper.":[57],"Firstly,":[58],"optimize":[60],"parameter":[62,102,126],"exchange":[63],"implement":[69],"decentralized":[77],"architecture.":[78,104],"Secondly,":[79],"to":[80,113,133],"improve":[81,134],"efficiency":[84],"system,":[88],"(PSR-Allreduce)":[96],"based":[97],"on":[98],"idea":[100],"server":[103],"Finally,":[105],"Worker-Leader-Group":[107],"generator":[108],"(WLG)":[109],"framework":[110,123],"is":[111,165],"designed":[112],"problem":[116],"inconsistency":[118],"cluster":[120],"nodes.":[121],"This":[122],"combines":[124],"aggregation":[127],"adopts":[129],"strategy":[132],"scalability":[136,151],"system.":[140],"Experiments":[141],"show":[142],"that":[143],"PSRA-HGADMM":[144,164],"better":[146,150],"performance":[148],"than":[152],"ADMMLib":[153],"AD-ADMM.":[155],"Compared":[156],"ADMMLib,":[158],"overall":[160],"reduced":[166],"by":[167],"32%.":[168]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}