{"id":"https://openalex.org/W7154397643","doi":"https://doi.org/10.48550/arxiv.2604.10859","title":"Understanding Communication Backends in Cross-Silo Federated Learning","display_name":"Understanding Communication Backends in Cross-Silo Federated Learning","publication_year":2026,"publication_date":"2026-04-12","ids":{"openalex":"https://openalex.org/W7154397643","doi":"https://doi.org/10.48550/arxiv.2604.10859"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2604.10859","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.10859","pdf_url":"https://arxiv.org/pdf/2604.10859","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2604.10859","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073329688","display_name":"Amir Ziashahabi","orcid":"https://orcid.org/0009-0000-1154-0078","observed_orcids":["https://orcid.org/0009-0000-1154-0078"]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziashahabi, Amir","raw_affiliation_strings":["Department of Electrical and Computer Engineering , University of Southern California , Los Angeles , CA , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering , University of Southern California , Los Angeles , CA , USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108988726","display_name":"Chaoyang He","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Chaoyang","raw_affiliation_strings":["TensorOpera, Inc. , Palo Alto , CA , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TensorOpera, Inc. , Palo Alto , CA , USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112726818","display_name":"Salman Avestimehr","orcid":"https://orcid.org/0000-0003-3102-0867","observed_orcids":["https://orcid.org/0000-0003-3102-0867"]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Avestimehr, Salman","raw_affiliation_strings":["Department of Electrical and Computer Engineering , University of Southern California , Los Angeles , CA , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering , University of Southern California , Los Angeles , CA , USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.98580002784729,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.98580002784729,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.0019000000320374966,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/cross-silo-federated-learning","display_name":"cross-silo federated learning","score":0.9900000095367432},{"id":"https://openalex.org/keywords/grpc","display_name":"gRPC","score":0.859000027179718},{"id":"https://openalex.org/keywords/mpi","display_name":"MPI","score":0.9940000176429749},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.609000027179718}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8720999956130981},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.5857999920845032},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5680000185966492},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5135999917984009},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.48989999294281006},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4812999963760376},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4803999960422516},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.46129998564720154},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.382999986410141},{"id":"https://openalex.org/C158156997","wikidata":"https://www.wikidata.org/wiki/Q1416645","display_name":"Models of communication","level":2,"score":0.37279999256134033},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.361299991607666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35850000381469727},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3352999985218048},{"id":"https://openalex.org/C12269588","wikidata":"https://www.wikidata.org/wiki/Q132364","display_name":"Communications protocol","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.3249000012874603},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.2624000012874603},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25999999046325684},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.25949999690055847},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2604.10859","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.10859","pdf_url":"https://arxiv.org/pdf/2604.10859","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2604.10859","doi":"https://doi.org/10.48550/arxiv.2604.10859","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10859","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2604.10859","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.10859","pdf_url":"https://arxiv.org/pdf/2604.10859","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.428600013256073,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7154397643.pdf","grobid_xml":"https://content.openalex.org/works/W7154397643.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4392490331","https://openalex.org/W4406031014","https://openalex.org/W4318619411","https://openalex.org/W3094306715","https://openalex.org/W3103635059","https://openalex.org/W7079595153","https://openalex.org/W4388116613","https://openalex.org/W4324268150","https://openalex.org/W4404420871","https://openalex.org/W4283697267"],"abstract_inverted_index":{"Federated":[0],"learning":[1,174],"(FL)":[2],"has":[3],"emerged":[4],"as":[5,66],"a":[6,111,146],"practical":[7,160],"means":[8],"for":[9,20,62,79,123,145,162],"privacy-preserving":[10],"distributed":[11],"machine":[12],"learning.":[13],"FL's":[14],"versatile":[15],"design":[16],"makes":[17],"it":[18],"suitable":[19,166],"various":[21,97],"training":[22],"settings,":[23],"from":[24],"IoT":[25],"edge":[26],"devices":[27],"in":[28,34,50,83],"cross-device":[29],"FL":[30,55,84],"to":[31,115,132,170],"powerful":[32],"servers":[33],"cross-silo":[35,90],"FL.":[36],"A":[37],"key":[38],"consequence":[39],"of":[40,47,54,74,96,119,149],"this":[41],"versatility":[42],"is":[43],"the":[44,51,59,117,171],"high":[45],"level":[46],"diversity":[48],"found":[49],"networking":[52],"configuration":[53,73],"applications.":[56],"Coupled":[57],"with":[58],"rising":[60],"demand":[61],"large-scale":[63],"models":[64,126],"such":[65],"large":[67,125],"language":[68],"models,":[69],"well-informed":[70],"selection":[71],"and":[72,103,142,164,176],"communication":[75,98,167],"backends":[76,168],"become":[77],"crucial":[78],"ensuring":[80],"optimal":[81],"performance":[82,144],"systems.":[85],"This":[86],"work":[87],"focuses":[88],"on":[89],"federated":[91,173],"learning,":[92],"presenting":[93],"in-depth":[94],"benchmarks":[95,139],"backends,":[99],"including":[100],"MPI,":[101],"gRPC,":[102],"PyTorch":[104],"RPC.":[105],"In":[106],"addition,":[107],"we":[108],"introduce":[109],"gRPC+S3,":[110],"hybrid":[112],"backend":[113],"designed":[114],"overcome":[116],"limitations":[118],"existing":[120],"approaches,":[121],"particularly":[122],"transmitting":[124],"across":[127],"geo-distributed":[128],"deployments,":[129],"achieving":[130],"up":[131],"$3.8\\times$":[133],"end-to-end":[134,143],"speedup":[135],"over":[136],"gRPC.":[137],"Our":[138,157],"examine":[140],"point-to-point":[141],"broad":[147],"range":[148],"model":[150],"sizes":[151],"running":[152],"under":[153],"realistic":[154],"network":[155,177],"conditions.":[156],"findings":[158],"provide":[159],"insights":[161],"selecting":[163],"configuring":[165],"tailored":[169],"specific":[172],"tasks":[175],"configurations.":[178]},"counts_by_year":[],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2026-04-15T00:00:00"}