{"id":"https://openalex.org/W7160244815","doi":"https://doi.org/10.48550/arxiv.2605.00837","title":"Fast Log-Domain Sinkhorn Optimal Transport with Warp-Level GPU Reductions","display_name":"Fast Log-Domain Sinkhorn Optimal Transport with Warp-Level GPU Reductions","publication_year":2026,"publication_date":"2026-04-04","ids":{"openalex":"https://openalex.org/W7160244815","doi":"https://doi.org/10.48550/arxiv.2605.00837"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.00837","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00837","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.2605.00837","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135372528","display_name":"Hao Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xiao, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5135372528"],"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.1899999976158142,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.1899999976158142,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.15700000524520874,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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":0.13079999387264252,"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":0.8600000143051147},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.8062999844551086},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.7868000268936157},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5751000046730042},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.569100022315979},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.5213000178337097},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4968000054359436},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.48669999837875366}],"concepts":[{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.8600000143051147},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.8062999844551086},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7972000241279602},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.7868000268936157},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.6195999979972839},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5751000046730042},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.569100022315979},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.5213000178337097},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4968000054359436},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.48669999837875366},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4537000060081482},{"id":"https://openalex.org/C150552126","wikidata":"https://www.wikidata.org/wiki/Q339387","display_name":"SIMD","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.41850000619888306},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3928000032901764},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.37450000643730164},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.33959999680519104},{"id":"https://openalex.org/C50630238","wikidata":"https://www.wikidata.org/wiki/Q971505","display_name":"General-purpose computing on graphics processing units","level":3,"score":0.31690001487731934},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29989999532699585},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.2775000035762787},{"id":"https://openalex.org/C83283714","wikidata":"https://www.wikidata.org/wiki/Q121117","display_name":"Supercomputer","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C176321772","wikidata":"https://www.wikidata.org/wiki/Q1430640","display_name":"Numerical stability","level":3,"score":0.265500009059906},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C48753275","wikidata":"https://www.wikidata.org/wiki/Q11216","display_name":"Numerical analysis","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C2989134064","wikidata":"https://www.wikidata.org/wiki/Q288510","display_name":"Execution time","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.00837","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00837","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.2605.00837","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00837","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Entropic":[0],"regularized":[1],"optimal":[2,157],"transport":[3,158],"(OT)":[4],"via":[5],"the":[6,46,72,106],"Sinkhorn":[7,48],"algorithm":[8,49],"has":[9],"become":[10],"a":[11,40,150],"fundamental":[12],"tool":[13],"in":[14,71],"machine":[15],"learning,":[16],"yet":[17],"existing":[18],"implementations":[19],"either":[20],"suffer":[21],"from":[22,33],"numerical":[23,65,147],"instability":[24],"for":[25,77,155],"small":[26,81],"regularization":[27,78],"parameters":[28,79],"or":[29],"incur":[30],"significant":[31],"overhead":[32],"deep":[34],"learning":[35],"frameworks.":[36],"We":[37,125],"present":[38],"FastSinkhorn,":[39],"lightweight,":[41],"native":[42,142],"CUDA":[43,143],"implementation":[44,101],"of":[45,122],"log-domain":[47],"that":[50,141],"combines":[51],"warp-level":[52],"shuffle":[53],"reductions":[54],"with":[55,94,145],"shared-memory":[56],"tiling":[57],"to":[58],"achieve":[59],"high":[60],"GPU":[61,123],"utilization":[62],"without":[63],"sacrificing":[64],"stability.":[66],"Our":[67],"solver":[68,128],"operates":[69],"entirely":[70],"log-domain,":[73],"enabling":[74],"robust":[75],"computation":[76],"as":[80,82],"epsilon":[83],"=":[84,96,98],"10^{-4}":[85],"where":[86],"standard-domain":[87],"methods":[88],"fail.":[89],"On":[90],"dense":[91],"OT":[92],"problems":[93],"n":[95],"m":[97],"8192,":[99],"our":[100,127],"achieves":[102],"12x":[103],"speedup":[104,112],"over":[105,113],"widely-used":[107],"POT":[108],"library":[109],"and":[110,137,152],"5.9x":[111],"GPU-accelerated":[114],"PyTorch":[115],"baselines,":[116],"while":[117],"consuming":[118],"only":[119],"256":[120],"MB":[121],"memory.":[124],"validate":[126],"on":[129],"image":[130],"color":[131],"transfer,":[132],"3D":[133],"point":[134],"cloud":[135],"matching,":[136],"convergence":[138],"analysis,":[139],"demonstrating":[140],"kernels":[144],"careful":[146],"treatment":[148],"provide":[149],"practical":[151],"efficient":[153],"foundation":[154],"large-scale":[156],"computation.":[159]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-06T00:00:00"}
