{"id":"https://openalex.org/W7164040158","doi":"https://doi.org/10.48550/arxiv.2606.07777","title":"Large-Scale Regularized Matching on GPU Clusters","display_name":"Large-Scale Regularized Matching on GPU Clusters","publication_year":2026,"publication_date":"2026-06-05","ids":{"openalex":"https://openalex.org/W7164040158","doi":"https://doi.org/10.48550/arxiv.2606.07777"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.07777","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07777","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":"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.07777","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037919308","display_name":"Aida Rahmattalabi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rahmattalabi, Aida","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138233875","display_name":"Gregory Dexter","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dexter, Gregory","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128237882","display_name":"Sanjana Garg","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Garg, Sanjana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128251947","display_name":"Qinquan Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Qinquan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002072162","display_name":"Shenyinying Tu","orcid":"https://orcid.org/0000-0001-8549-9899"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tu, Shenyinying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138254577","display_name":"Yuan Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138264120","display_name":"Zhipeng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zhipeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138212872","display_name":"Rahul Mazumder","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mazumder, Rahul","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/T12292","display_name":"Graph Theory and Algorithms","score":0.616100013256073,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.616100013256073,"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":0.11479999870061874,"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/T12326","display_name":"Network Packet Processing and Optimization","score":0.09539999812841415,"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/speedup","display_name":"Speedup","score":0.7480999827384949},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.7386000156402588},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.46000000834465027},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.45579999685287476},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4474000036716461},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.44679999351501465},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.44200000166893005},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.4239000082015991},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4007999897003174},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.39579999446868896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8197000026702881},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.7480999827384949},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.7386000156402588},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.707099974155426},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.46000000834465027},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.45579999685287476},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4474000036716461},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.44679999351501465},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.44200000166893005},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.4239000082015991},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4007999897003174},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.39579999446868896},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.3885999917984009},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.38109999895095825},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3589000105857849},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3124000132083893},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2906000018119812},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C50630238","wikidata":"https://www.wikidata.org/wiki/Q971505","display_name":"General-purpose computing on graphics processing units","level":3,"score":0.2874999940395355},{"id":"https://openalex.org/C201374245","wikidata":"https://www.wikidata.org/wiki/Q104534","display_name":"Digital subscriber line","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C61445026","wikidata":"https://www.wikidata.org/wiki/Q217608","display_name":"Fixed point","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C88626702","wikidata":"https://www.wikidata.org/wiki/Q1128903","display_name":"Continuation","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C137119250","wikidata":"https://www.wikidata.org/wiki/Q1413101","display_name":"Multigrid method","level":3,"score":0.27129998803138733},{"id":"https://openalex.org/C6802819","wikidata":"https://www.wikidata.org/wiki/Q1072174","display_name":"Linear system","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.26570001244544983},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C1306188","wikidata":"https://www.wikidata.org/wiki/Q4060687","display_name":"Nested loop join","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C173404611","wikidata":"https://www.wikidata.org/wiki/Q528588","display_name":"Constraint programming","level":3,"score":0.259799987077713},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C34165917","wikidata":"https://www.wikidata.org/wiki/Q188267","display_name":"Programming paradigm","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.07777","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07777","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.07777","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07777","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":"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"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6422945261001587}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Production":[0],"decision":[1],"systems":[2],"such":[3,57,88],"as":[4,58,89],"ad":[5],"allocation":[6],"or":[7,218],"content":[8],"matching":[9],"involve":[10],"millions":[11],"of":[12,16,54,153,244],"users":[13,140],"and":[14,60,75,93,132,192,239],"thousands":[15],"items,":[17],"reducing":[18],"to":[19,97,105,135,150,172],"large-scale":[20],"linear":[21],"programs":[22],"with":[23,118,128,160,207],"sparse":[24],"block-diagonal":[25],"structure":[26],"across":[27,70],"users.":[28],"These":[29],"LPs":[30,171],"are":[31],"solved":[32],"repeatedly":[33],"on":[34,236],"recurring":[35],"cadences":[36],"over":[37,185,230],"slowly":[38,92],"evolving":[39],"inputs.":[40],"Three":[41],"system":[42,225],"gaps":[43],"stand":[44],"out.":[45],"Scale:":[46],"production":[47],"instances":[48],"routinely":[49],"exceed":[50],"the":[51,186,215,242],"memory":[52],"capacity":[53],"GPU":[55,161,180,246],"solvers":[56,80,87],"cuPDLP":[59],"D-PDLP":[61],"under":[62],"fixed":[63,98,164],"hardware":[64],"budgets.":[65],"Temporal":[66],"instability:":[67],"solution":[68,193],"variability":[69],"runs":[71],"induces":[72],"downstream":[73],"churn":[74],"complicates":[76],"SLAs,":[77],"yet":[78],"existing":[79,179,245],"provide":[81],"no":[82],"explicit":[83],"control.":[84],"Extensibility:":[85],"CPU-based":[86],"DuaLip-Scala":[90],"converge":[91],"couple":[94],"problem":[95],"formulation":[96],"schemas,":[99],"making":[100],"new":[101,211],"constraint":[102],"families":[103],"difficult":[104],"express.":[106],"We":[107,167],"present":[108],"a":[109,151,175],"distributed":[110,219],"multi-GPU":[111,233],"LP":[112],"solver":[113],"built":[114],"natively":[115],"in":[116],"PyTorch":[117],"systems-algorithm":[119],"co-design":[120],"for":[121],"this":[122],"structure.":[123],"It":[124],"adopts":[125],"column-sharded":[126],"parallelism":[127],"fused":[129],"Triton":[130],"kernels":[131],"batched":[133],"operations":[134],"reduce":[136],"per-iteration":[137],"overhead.":[138],"As":[139],"grow,":[141],"only":[142],"local":[143],"computation":[144],"increases,":[145],"while":[146],"communication":[147],"is":[148],"limited":[149],"reduction":[152],"item-level":[154],"dual":[155],"variables,":[156],"yielding":[157],"near-linear":[158,232],"scaling":[159,234],"count":[162],"at":[163],"item":[165],"size.":[166],"also":[168],"adopt":[169],"ridge-regularized":[170],"improve":[173],"stability,":[174],"control":[176],"absent":[177],"from":[178],"solvers.":[181,247],"A":[182],"continuation":[183],"schedule":[184],"regularization":[187],"parameter":[188],"balances":[189],"convergence":[190],"speed":[191],"fidelity.":[194],"Finally,":[195],"we":[196],"introduce":[197],"an":[198],"operator-centric":[199],"programming":[200],"model":[201],"that":[202],"replaces":[203],"DuaLip-Scala's":[204],"schema-bound":[205],"interface":[206],"composable":[208],"primitives,":[209],"enabling":[210],"formulations":[212],"without":[213],"modifying":[214],"solve":[216],"loop":[217],"infrastructure.":[220],"On":[221],"synthetic":[222],"workloads,":[223],"our":[224],"achieves":[226],"order-of-magnitude":[227],"wall-clock":[228],"speedup":[229],"DuaLip-Scala,":[231],"(3.86x":[235],"4":[237],"GPUs),":[238],"scales":[240],"beyond":[241],"reach":[243]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-10T00:00:00"}