{"id":"https://openalex.org/W7160961462","doi":"https://doi.org/10.48550/arxiv.2605.08524","title":"Unleashing Scalable Context Parallelism for Foundation Models Pre-Training via FCP","display_name":"Unleashing Scalable Context Parallelism for Foundation Models Pre-Training via FCP","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160961462","doi":"https://doi.org/10.48550/arxiv.2605.08524"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.08524","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08524","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,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.08524","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135987408","display_name":"Yilong Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yilong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059601307","display_name":"Xiaonan Nie","orcid":"https://orcid.org/0000-0001-6766-757X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie, Xiaonan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109738655","display_name":"Kan Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Kan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135992498","display_name":"Shuang Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Shuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135936041","display_name":"Zhichao Lai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lai, Zhichao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135913896","display_name":"Hongxiang Hao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao, Hongxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135924018","display_name":"Yang Zhou","orcid":"https://orcid.org/0009-0003-9022-8681"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135970484","display_name":"Baris Kasikci","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kasikci, Baris","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135993773","display_name":"Ion Stoica","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stoica, Ion","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.5034000277519226,"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":0.5034000277519226,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.1818999946117401,"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"}},{"id":"https://openalex.org/T10904","display_name":"Embedded Systems Design Techniques","score":0.02539999969303608,"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/scalability","display_name":"Scalability","score":0.8007000088691711},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.7347000241279602},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.6373999714851379},{"id":"https://openalex.org/keywords/parallelism","display_name":"Parallelism (grammar)","score":0.6366999745368958},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5823000073432922},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.524399995803833},{"id":"https://openalex.org/keywords/inefficiency","display_name":"Inefficiency","score":0.45210000872612}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8129000067710876},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8007000088691711},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7347000241279602},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.6373999714851379},{"id":"https://openalex.org/C2781172179","wikidata":"https://www.wikidata.org/wiki/Q853109","display_name":"Parallelism (grammar)","level":2,"score":0.6366999745368958},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5823000073432922},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5680999755859375},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.524399995803833},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5105999708175659},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.45210000872612},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3490000069141388},{"id":"https://openalex.org/C191172861","wikidata":"https://www.wikidata.org/wiki/Q7899321","display_name":"Upstream (networking)","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.33719998598098755},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.33320000767707825},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.28929999470710754},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2849000096321106},{"id":"https://openalex.org/C106515295","wikidata":"https://www.wikidata.org/wiki/Q26806595","display_name":"Parallel processing","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C61483411","wikidata":"https://www.wikidata.org/wiki/Q3124522","display_name":"Data parallelism","level":3,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.08524","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08524","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,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.08524","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08524","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,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.42320945858955383,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Context":[0],"parallelism":[1,71],"(CP)":[2],"has":[3],"been":[4],"widely":[5],"adopted":[6],"to":[7,21,43,133],"support":[8],"the":[9,23,141],"growing":[10],"context":[11,70],"length":[12,28],"in":[13,26,33,140],"foundation":[14],"model":[15],"pretraining.":[16],"However,":[17],"existing":[18],"designs":[19],"fail":[20],"handle":[22],"large":[24],"variation":[25],"sequence":[27,100],"from":[29,107],"training":[30],"datasets,":[31],"resulting":[32],"suboptimal":[34],"performance.":[35],"These":[36],"methods":[37],"often":[38],"over-shard":[39],"short":[40,53,109],"sequences,":[41,112],"leading":[42],"compute":[44,117],"inefficiency":[45],"and":[46,52,75,110,119],"excessive":[47],"communication,":[48,95],"or":[49],"process":[50],"long":[51,111],"sequences":[54,77],"separately":[55],"without":[56],"proper":[57],"bin-packing,":[58],"causing":[59],"workload":[60,121],"imbalance.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65],"propose":[66],"FCP,":[67],"a":[68],"flexible":[69,97],"paradigm":[72],"that":[73,126],"shards":[74],"schedules":[76],"at":[78],"block-level":[79],"granularity.":[80],"Instead":[81],"of":[82,99],"relying":[83],"on":[84,131],"rigid":[85],"communication":[86],"topologies":[87],"such":[88],"as":[89],"ring,":[90],"FCP":[91,113,127],"enables":[92],"arbitrary":[93],"peer-to-peer":[94],"allowing":[96],"placement":[98],"blocks":[101,106],"across":[102],"workers.":[103],"By":[104],"bin-packing":[105],"both":[108,115],"achieves":[114],"high":[116],"efficiency":[118],"balanced":[120],"distribution.":[122],"Extensive":[123],"evaluations":[124],"show":[125],"attains":[128],"near-linear":[129],"scalability":[130],"up":[132],"256":[134],"NVIDIA":[135],"GPUs,":[136],"with":[137],"1.13x-2.21x":[138],"improvement":[139],"attention":[142],"MFU.":[143]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-13T00:00:00"}