{"id":"https://openalex.org/W7167594155","doi":"https://doi.org/10.48550/arxiv.2607.02945","title":"Optimus: A Generic Operator-Level PyTorch Model Transformation Framework","display_name":"Optimus: A Generic Operator-Level PyTorch Model Transformation Framework","publication_year":2026,"publication_date":"2026-07-03","ids":{"openalex":"https://openalex.org/W7167594155","doi":"https://doi.org/10.48550/arxiv.2607.02945"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.02945","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.02945","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":"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.2607.02945","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031558801","display_name":"Menglu Yu","orcid":"https://orcid.org/0000-0002-3653-3453"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Menglu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111626467","display_name":"J Q Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Jiaqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034586871","display_name":"Yuzhen Huang","orcid":"https://orcid.org/0000-0002-9536-7918"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Yuzhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107311577","display_name":"Y Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Yanbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140164541","display_name":"Jia Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026769012","display_name":"Sen Yang","orcid":"https://orcid.org/0000-0003-1064-0055"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Shuai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089997788","display_name":"Jason Ansel","orcid":"https://orcid.org/0009-0007-5207-2179"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ansel, Jason","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140194772","display_name":"Elias Ellison","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ellison, Elias","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140213012","display_name":"Edward Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Edward","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140182445","display_name":"Brian Hirsh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hirsh, Brian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140191092","display_name":"Jia Chen Ren","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Jia Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011399916","display_name":"Will Feng","orcid":"https://orcid.org/0009-0009-6406-4699"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Will","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063210087","display_name":"O\u011fuz \u00dclgen","orcid":"https://orcid.org/0000-0003-4923-7191"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ulgen, Oguz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053213848","display_name":"X Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069028055","display_name":"Daohang Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Daohang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058039924","display_name":"Huaqing Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Huaqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114402062","display_name":"Quanyu Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Quanyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088272481","display_name":"Mingming Ding","orcid":"https://orcid.org/0000-0001-5972-2540"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Mingming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125656933","display_name":"Junqing Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Junqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140157090","display_name":"Ruilin Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Ruilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140215727","display_name":"Yuhang Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yuhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140164004","display_name":"Chi-Keung Luk","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luk, Chi-Keung","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/T12535","display_name":"Machine Learning and Data Classification","score":0.22220000624656677,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.22220000624656677,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.17069999873638153,"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/T11450","display_name":"Model-Driven Software Engineering Techniques","score":0.07699999958276749,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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":0.6175000071525574},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.566100001335144},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5133000016212463},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.48019999265670776},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.4690000116825104},{"id":"https://openalex.org/keywords/model-transformation","display_name":"Model transformation","score":0.4108000099658966},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4106999933719635},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4065999984741211}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8083000183105469},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6175000071525574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6067000031471252},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.566100001335144},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5133000016212463},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.48019999265670776},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.4690000116825104},{"id":"https://openalex.org/C2779791154","wikidata":"https://www.wikidata.org/wiki/Q258040","display_name":"Model transformation","level":3,"score":0.4108000099658966},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4106999933719635},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.38749998807907104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38339999318122864},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3269999921321869},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.31049999594688416},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C189474733","wikidata":"https://www.wikidata.org/wiki/Q917912","display_name":"Model building","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C68859911","wikidata":"https://www.wikidata.org/wiki/Q1503724","display_name":"Pattern matching","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.28679999709129333},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C152752567","wikidata":"https://www.wikidata.org/wiki/Q116877","display_name":"Code refactoring","level":3,"score":0.2639999985694885}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.02945","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.02945","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":"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.2607.02945","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.02945","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":"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":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6699801087379456}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"large-scale":[1],"industrial":[2],"applications,":[3],"deep":[4],"learning":[5,30,94],"models":[6,19,163],"that":[7,139],"power":[8],"recommendation":[9,162],"and":[10,14,23,113,122,128,152],"ranking":[11],"have":[12,40],"complex":[13],"diverse":[15,72],"model":[16,73,84,117,177],"architectures.":[17,74],"These":[18,55],"are":[20,68],"continuously":[21],"developed":[22],"refined":[24],"by":[25],"large":[26],"teams":[27],"of":[28,62,100],"machine":[29,93],"engineers,":[31],"rendering":[32],"manual":[33],"optimization":[34,38],"infeasible.":[35],"Consequently,":[36],"graph-based":[37],"techniques":[39],"become":[41],"an":[42,105],"industry":[43],"standard":[44],"for":[45,110,159],"boosting":[46],"performance,":[47],"with":[48,171],"PyTorch":[49,90,172],"FX":[50],"transformations":[51,56],"leading":[52],"the":[53,89,133,140],"charge.":[54],"typically":[57],"rely":[58],"on":[59],"a":[60,82,97,125,175],"set":[61,99],"human-engineered":[63],"module-level":[64],"rewrite":[65],"rules":[66],"which":[67],"not":[69],"scalable":[70],"to":[71,145,165],"To":[75],"address":[76],"this":[77],"limitation,":[78],"we":[79],"introduce":[80],"Optimus,":[81],"general-purpose":[83],"transformation":[85,178],"framework":[86,130,141],"built":[87],"in":[88],"2.x":[91,173],"(PT2)":[92],"compiler.":[95],"With":[96],"concise":[98],"predefined":[101],"patterns,":[102],"Optimus":[103,167],"applies":[104],"efficient":[106],"greedy":[107],"search":[108],"algorithm":[109],"pattern":[111],"matching":[112],"replacement,":[114],"while":[115],"preserving":[116],"semantic.":[118],"It":[119],"is":[120,168],"designed":[121],"implemented":[123],"as":[124,174],"highly":[126],"customizable":[127,176],"extensible":[129],"integrated":[131],"into":[132],"PT2":[134],"stack.":[135],"Our":[136],"evaluation":[137],"shows":[138],"can":[142],"achieve":[143],"up":[144],"63%":[146],"speedup,":[147],"6%":[148],"peak":[149],"memory":[150],"reduction,":[151],"over":[153],"400":[154],"second":[155],"compile":[156],"time":[157],"decrease":[158],"our":[160],"industry-scale":[161],"compared":[164],"baselines.":[166],"open-sourced":[169],"together":[170],"layer.":[179]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-08T00:00:00"}