{"id":"https://openalex.org/W7161977493","doi":"https://doi.org/10.48550/arxiv.2605.20799","title":"Instant GPU Efficiency Visibility at Fleet Scale","display_name":"Instant GPU Efficiency Visibility at Fleet Scale","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7161977493","doi":"https://doi.org/10.48550/arxiv.2605.20799"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.20799","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20799","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.2605.20799","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136664439","display_name":"Connor Pedersen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pedersen, Connor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006598908","display_name":"Dong H. Ahn","orcid":"https://orcid.org/0000-0001-6722-0532"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahn, Dong H.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136726009","display_name":"Michel Migdal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Migdal, Michel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121348894","display_name":"Collin Neale","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neale, Collin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136695919","display_name":"Nik Konyuchenko","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Konyuchenko, Nik","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":0.9610999822616577,"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":0.9610999822616577,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.004100000020116568,"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/T10363","display_name":"Low-power high-performance VLSI design","score":0.003599999938160181,"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/visibility","display_name":"Visibility","score":0.6165000200271606},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5485000014305115},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5128999948501587},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.47209998965263367},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.4505000114440918},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.4058000147342682}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6766999959945679},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.6165000200271606},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5485000014305115},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5128999948501587},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.47209998965263367},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.4505000114440918},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.40630000829696655},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.4058000147342682},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3580999970436096},{"id":"https://openalex.org/C2779432360","wikidata":"https://www.wikidata.org/wiki/Q16963779","display_name":"Instant","level":2,"score":0.3569999933242798},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3531000018119812},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27799999713897705},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.2727999985218048},{"id":"https://openalex.org/C118530786","wikidata":"https://www.wikidata.org/wiki/Q1134732","display_name":"Instrumentation (computer programming)","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2597000002861023},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.25209999084472656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.20799","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20799","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.2605.20799","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20799","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,44],"present":[1],"Overall":[2],"FLOP":[3],"Utilization":[4],"(OFU),":[5],"a":[6,123,143],"hardware-level,":[7],"precision-agnostic":[8],"GPU":[9,39,118],"efficiency":[10,125,153],"metric":[11],"for":[12,150],"AI":[13],"workloads":[14],"on":[15,73],"HPC":[16],"systems,":[17],"derived":[18],"from":[19],"two":[20,111],"on-chip":[21],"performance":[22],"counters:":[23],"Tensor":[24,61],"Pipe":[25],"Activity":[26],"and":[27,36,41,65,75,81,109,127,137],"SM":[28],"clock":[29,58,63],"frequency.":[30],"OFU":[31,50,86,100,120,141],"requires":[32],"no":[33],"application":[34],"instrumentation":[35],"works":[37],"across":[38,77,116],"generations":[40],"numeric":[42],"precisions.":[43],"characterize":[45],"five":[46],"properties":[47],"of":[48],"the":[49],"approximation":[51],"--":[52,68],"tile":[53],"quantization,":[54],"floating-point":[55],"precision":[56],"scaling,":[57],"sampling":[59],"noise,":[60],"Core":[62],"domains,":[64],"non-tensor":[66],"undercounting":[67],"through":[69],"controlled":[70],"GEMM":[71],"experiments":[72],"H100":[74],"GB200":[76],"FP16,":[78],"TF32,":[79],"FP8,":[80],"NVFP4.":[82],"After":[83],"tile-quantization":[84],"correction,":[85],"predicts":[87],"application-level":[88,107,148],"MFU":[89,108,149],"to":[90,147],"within":[91],"<=2":[92],"percentage":[93],"points.":[94],"Against":[95],"608":[96],"production":[97],"training":[98],"jobs,":[99],"achieves":[101],"r":[102],"=":[103],"0.78":[104],"correlation":[105],"with":[106],"surfaces":[110],"framework-level":[112],"FLOPs":[113],"miscalculations.":[114],"Deployed":[115],"large-scale":[117],"fleets,":[119],"has":[121],"detected":[122],"2.5x":[124],"regression":[126],"tracked":[128],"precision-dependent":[129],"utilization":[130],"changes":[131],"in":[132],"mixed-precision":[133],"pretraining.":[134],"Our":[135],"evaluation":[136],"operational":[138],"experience":[139],"suggest":[140],"is":[142],"practical,":[144],"deployment-ready":[145],"complement":[146],"continuous":[151],"fleet-wide":[152],"monitoring.":[154]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-22T00:00:00"}