{"id":"https://openalex.org/W7140221820","doi":"https://doi.org/10.48550/arxiv.2603.20421","title":"Hawkeye: Reproducing GPU-Level Non-Determinism","display_name":"Hawkeye: Reproducing GPU-Level Non-Determinism","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W7140221820","doi":"https://doi.org/10.48550/arxiv.2603.20421"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.20421","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20421","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.20421","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Badash, Erez","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Badash, Erez","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Boneh, Dan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boneh, Dan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Komargodski, Ilan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Komargodski, Ilan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Srivastava, Megha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Srivastava, Megha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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":0.17180000245571136,"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":0.17180000245571136,"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/T11697","display_name":"Numerical Methods and Algorithms","score":0.09589999914169312,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11948","display_name":"Machine Learning in Materials Science","score":0.08659999817609787,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/rounding","display_name":"Rounding","score":0.6861000061035156},{"id":"https://openalex.org/keywords/matrix-multiplication","display_name":"Matrix multiplication","score":0.6212000250816345},{"id":"https://openalex.org/keywords/verifiable-secret-sharing","display_name":"Verifiable secret sharing","score":0.5532000064849854},{"id":"https://openalex.org/keywords/multiplication","display_name":"Multiplication (music)","score":0.5461000204086304},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4221000075340271},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.41190001368522644},{"id":"https://openalex.org/keywords/sync","display_name":"sync","score":0.3736000061035156},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.36010000109672546}],"concepts":[{"id":"https://openalex.org/C136625980","wikidata":"https://www.wikidata.org/wiki/Q663208","display_name":"Rounding","level":2,"score":0.6861000061035156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.684499979019165},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.6212000250816345},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.5532000064849854},{"id":"https://openalex.org/C2780595030","wikidata":"https://www.wikidata.org/wiki/Q3860309","display_name":"Multiplication (music)","level":2,"score":0.5461000204086304},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.4244000017642975},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4221000075340271},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.41190001368522644},{"id":"https://openalex.org/C3913047","wikidata":"https://www.wikidata.org/wiki/Q1956265","display_name":"sync","level":3,"score":0.3736000061035156},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3716999888420105},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C60798267","wikidata":"https://www.wikidata.org/wiki/Q1226939","display_name":"Division (mathematics)","level":2,"score":0.3537999987602234},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C1793878","wikidata":"https://www.wikidata.org/wiki/Q1153762","display_name":"Out-of-order execution","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C84211073","wikidata":"https://www.wikidata.org/wiki/Q117879","display_name":"Floating point","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.28769999742507935},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2840000092983246},{"id":"https://openalex.org/C159718280","wikidata":"https://www.wikidata.org/wiki/Q5526353","display_name":"Gas meter prover","level":3,"score":0.27320000529289246},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2581999897956848}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.20421","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20421","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.20421","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20421","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,109],"present":[1],"Hawkeye,":[2],"a":[3,19,27,83,143],"system":[4],"for":[5,148],"analyzing":[6],"and":[7,73,97,111,123,125,150,158],"reproducing":[8],"GPU-level":[9],"arithmetic":[10],"operations.":[11],"Using":[12],"our":[13,113],"framework,":[14],"anyone":[15],"can":[16],"re-execute":[17],"on":[18,38,105,115,142],"CPU":[20],"the":[21,65,146],"exact":[22],"matrix":[23,103,140],"multiplication":[24,104,141],"operations":[25],"underlying":[26],"machine":[28,56],"learning":[29],"model":[30,67,156],"training":[31,157],"or":[32,69],"inference":[33],"workflow":[34],"that":[35,90],"was":[36],"executed":[37],"an":[39],"NVIDIA":[40,117],"GPU,":[41],"without":[42],"any":[43],"precision":[44,126],"loss.":[45],"This":[46],"is":[47,82],"in":[48],"stark":[49],"contrast":[50],"to":[51,54,64],"prior":[52],"approaches":[53],"verifiable":[55],"learning,":[57],"which":[58],"either":[59],"introduce":[60],"significant":[61],"computation":[62],"overhead":[63],"original":[66],"owner,":[68],"suffer":[70],"from":[71],"non-robustness":[72],"quality":[74],"degradation.":[75],"The":[76],"main":[77],"technical":[78],"contribution":[79],"of":[80,86,99,139,154],"Hawkeye":[81,135],"systematic":[84],"sequence":[85],"carefully":[87],"crafted":[88],"tests":[89],"study":[91],"rounding":[92],"direction,":[93],"subnormal":[94],"number":[95],"handling,":[96],"order":[98],"(non-associative)":[100],"accumulation":[101],"during":[102],"NVIDIA's":[106],"Tensor":[107],"Cores.":[108],"test":[110,133],"evaluate":[112],"framework":[114],"multiple":[116],"GPU":[118],"architectures":[119],"(":[120],"Ampere,":[121],"Hopper,":[122],"Lovelace)":[124],"types":[127],"(FP16,":[128],"BFP16,":[129],"FP8).":[130],"In":[131],"all":[132],"cases,":[134],"enables":[136],"perfect":[137],"reproduction":[138],"CPU,":[144],"paving":[145],"way":[147],"efficient":[149],"trustworthy":[151],"third-party":[152],"auditing":[153],"ML":[155],"inference.":[159]},"counts_by_year":[],"updated_date":"2026-04-25T08:17:42.794288","created_date":"2026-03-25T00:00:00"}