{"id":"https://openalex.org/W7165139949","doi":"https://doi.org/10.48550/arxiv.2606.19163","title":"Pulse: Training Acceleration for Large Diffusion Models with Automatic Pipeline Parallelism","display_name":"Pulse: Training Acceleration for Large Diffusion Models with Automatic Pipeline Parallelism","publication_year":2026,"publication_date":"2026-06-17","ids":{"openalex":"https://openalex.org/W7165139949","doi":"https://doi.org/10.48550/arxiv.2606.19163"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.19163","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.19163","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2606.19163","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100374253","display_name":"Bo Sun","orcid":"https://orcid.org/0000-0001-7001-8781"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Boran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138906434","display_name":"Guoyong Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Guoyong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138889755","display_name":"Lin Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Lin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138920926","display_name":"Chen Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030246817","display_name":"Yuechen Tao","orcid":"https://orcid.org/0000-0002-0650-3608"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Yuechen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138889671","display_name":"Zhishu Che","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Che, Zhishu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107877612","display_name":"J. Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Jieling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086644343","display_name":"S. Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang, Shan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049448415","display_name":"Huaxi Gu","orcid":"https://orcid.org/0000-0002-6409-2229"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Huaxi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138954182","display_name":"Fangming Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Fangming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138868185","display_name":"Bo Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Bo","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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.46880000829696655,"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"}},"topics":[{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.46880000829696655,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.05490000173449516,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.04399999976158142,"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/pipeline","display_name":"Pipeline (software)","score":0.8282999992370605},{"id":"https://openalex.org/keywords/parallelism","display_name":"Parallelism (grammar)","score":0.585099995136261},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.570900022983551},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.5454999804496765},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4997999966144562},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.42669999599456787},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.40959998965263367},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.39489999413490295},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.392300009727478}],"concepts":[{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.8282999992370605},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8148000240325928},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.6068999767303467},{"id":"https://openalex.org/C2781172179","wikidata":"https://www.wikidata.org/wiki/Q853109","display_name":"Parallelism (grammar)","level":2,"score":0.585099995136261},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.570900022983551},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5454999804496765},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4997999966144562},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.42669999599456787},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.40959998965263367},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.392300009727478},{"id":"https://openalex.org/C61483411","wikidata":"https://www.wikidata.org/wiki/Q3124522","display_name":"Data parallelism","level":3,"score":0.3702999949455261},{"id":"https://openalex.org/C176809094","wikidata":"https://www.wikidata.org/wiki/Q15401496","display_name":"Traverse","level":2,"score":0.3476000130176544},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3359000086784363},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C106515295","wikidata":"https://www.wikidata.org/wiki/Q26806595","display_name":"Parallel processing","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C141297171","wikidata":"https://www.wikidata.org/wiki/Q1143237","display_name":"Octree","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3107999861240387},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.30410000681877136},{"id":"https://openalex.org/C190475519","wikidata":"https://www.wikidata.org/wiki/Q544384","display_name":"Massively parallel","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C41681595","wikidata":"https://www.wikidata.org/wiki/Q7917855","display_name":"Vectorization (mathematics)","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.2687000036239624},{"id":"https://openalex.org/C2781215313","wikidata":"https://www.wikidata.org/wiki/Q3493345","display_name":"SPARK (programming language)","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C2776190703","wikidata":"https://www.wikidata.org/wiki/Q488148","display_name":"Slicing","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.19163","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.19163","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2606.19163","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.19163","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.4284673035144806}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Diffusion":[0],"models":[1],"are":[2],"now":[3],"a":[4,62,85,124,154],"dominant":[5,63],"approach":[6],"for":[7,107,147],"high-fidelity":[8],"image":[9],"and":[10,35,50,65,102,152,162,167,185],"video":[11],"generation,":[12],"yet":[13],"scaling":[14],"their":[15,51],"training":[16,79,187],"across":[17],"GPU":[18],"clusters":[19],"remains":[20],"challenging.":[21],"Unlike":[22],"transformer-only":[23],"architectures,":[24],"diffusion":[25],"backbones":[26],"commonly":[27],"adopt":[28],"UNet-style":[29],"encoder-decoder":[30,96],"structures":[31],"with":[32,200],"heterogeneous":[33,130],"layers":[34,97],"long-range":[36],"skip":[37,48,83,104],"connections.":[38],"Under":[39],"conventional":[40],"pipeline":[41,56,68,119],"parallelism,":[42],"these":[43],"non-local":[44],"dependencies":[45],"force":[46],"large":[47],"activations":[49,105],"gradients":[52],"to":[53,194],"traverse":[54],"multiple":[55],"boundaries,":[57],"making":[58],"peer-to-peer":[59],"(P2P)":[60],"communication":[61,92,178],"bottleneck":[64],"substantially":[66],"reducing":[67],"efficiency.":[69],"In":[70],"this":[71,114],"paper,":[72],"we":[73],"present":[74],"PULSE,":[75],"an":[76,138],"automatic":[77],"pipeline-parallel":[78],"strategy":[80],"that":[81,128,142,158,174],"makes":[82],"locality":[84],"first-class":[86],"optimization":[87],"objective.":[88],"PULSE":[89,121],"eliminates":[90],"skip-induced":[91],"by":[93,182,192],"collocating":[94],"skip-connected":[95],"on":[98,196],"the":[99,148,175,186],"same":[100],"device":[101],"caching":[103],"locally":[106],"later":[108],"use":[109],"in":[110],"backpropagation.":[111],"To":[112],"realize":[113],"placement":[115],"while":[116],"maintaining":[117],"high":[118],"utilization,":[120],"co-designs:":[122],"(1)":[123],"skip-aware":[125],"dynamic-programming":[126],"partitioner":[127],"balances":[129],"stage":[131],"workloads":[132],"under":[133,165],"symmetric":[134],"collocation":[135],"constraints,":[136],"(2)":[137],"ILP-based":[139],"schedule":[140],"synthesizer":[141],"generates":[143],"bubble-efficient":[144],"wave":[145],"schedules":[146],"resulting":[149],"stage-to-device":[150],"mapping,":[151],"(3)":[153],"hybrid":[155],"parallelism":[156,202],"tuner":[157],"selects":[159],"pipeline/data-parallel":[160],"degrees":[161],"microbatch":[163],"sizes":[164],"memory":[166],"network":[168],"constraints.":[169],"Our":[170],"extensive":[171],"experiments":[172],"show":[173],"volume":[176],"of":[177],"can":[179,189],"be":[180,190],"reduced":[181],"89":[183],"percent,":[184],"throughput":[188],"increased":[191],"up":[193],"2.3x":[195],"communication-bound":[197],"hardware,":[198],"compared":[199],"state-of-the-art":[201],"strategies.":[203]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-19T00:00:00"}