{"id":"https://openalex.org/W7104742932","doi":"https://doi.org/10.1145/3757348.3757364","title":"Framework for tracking metadata, lineage and model provenance in hybrid simulation-AI HPC exascale workflows","display_name":"Framework for tracking metadata, lineage and model provenance in hybrid simulation-AI HPC exascale workflows","publication_year":2025,"publication_date":"2025-05-04","ids":{"openalex":"https://openalex.org/W7104742932","doi":"https://doi.org/10.1145/3757348.3757364"},"language":null,"primary_location":{"id":"doi:10.1145/3757348.3757364","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3757348.3757364","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Cray User Group","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3757348.3757364","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Martin Foltin","orcid":"https://orcid.org/0000-0002-3386-0272"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Martin Foltin","raw_affiliation_strings":["AI Research Lab, HPE Labs, HPE, Fort Collins, Colorado, USA"],"affiliations":[{"raw_affiliation_string":"AI Research Lab, HPE Labs, HPE, Fort Collins, Colorado, USA","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Andrew Shao","orcid":"https://orcid.org/0000-0003-3658-512X"},"institutions":[{"id":"https://openalex.org/I4210163432","display_name":"Hewlett Packard Enterprise (Ireland)","ror":"https://ror.org/05cc0x492","country_code":"IE","type":"company","lineage":["https://openalex.org/I4210163432"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Andrew Shao","raw_affiliation_strings":["AI Research Lab, HPE Labs, HPE, Victoria, British Columbia, Canada"],"affiliations":[{"raw_affiliation_string":"AI Research Lab, HPE Labs, HPE, Victoria, British Columbia, Canada","institution_ids":["https://openalex.org/I4210163432"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Rishabh Sharma","orcid":"https://orcid.org/0000-0002-8515-082X"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rishabh Sharma","raw_affiliation_strings":["AI Research Lab, HPE Labs, HPE, Milpitas, California, USA"],"affiliations":[{"raw_affiliation_string":"AI Research Lab, HPE Labs, HPE, Milpitas, California, USA","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shreyas Kulkarni","orcid":"https://orcid.org/0009-0007-6657-6044"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shreyas Kulkarni","raw_affiliation_strings":["AI Research Lab, HPE Labs, HPE, Fort Collins, Colorado, USA"],"affiliations":[{"raw_affiliation_string":"AI Research Lab, HPE Labs, HPE, Fort Collins, Colorado, USA","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Annmary Justine Koomthanam","orcid":"https://orcid.org/0009-0002-8282-6190"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Annmary Justine Koomthanam","raw_affiliation_strings":["AI Research Lab, HPE Labs, HPE, Fort Collins, CO, USA"],"affiliations":[{"raw_affiliation_string":"AI Research Lab, HPE Labs, HPE, Fort Collins, CO, USA","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Aalap Tripathy","orcid":"https://orcid.org/0000-0002-9046-6298"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aalap Tripathy","raw_affiliation_strings":["AI Research Lab, HPE Labs, HPE, Spring, Texas, USA"],"affiliations":[{"raw_affiliation_string":"AI Research Lab, HPE Labs, HPE, Spring, Texas, USA","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Cong Xu","orcid":"https://orcid.org/0009-0005-8409-5282"},"institutions":[{"id":"https://openalex.org/I4210097286","display_name":"Hwa Chong Institution","ror":"https://ror.org/00rrrfr24","country_code":"SG","type":"education","lineage":["https://openalex.org/I4210097286"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Cong Xu","raw_affiliation_strings":["AI Research Lab, HPE Labs, HPE, Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"AI Research Lab, HPE Labs, HPE, Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I4210097286"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenqian Dong","orcid":"https://orcid.org/0000-0002-8376-6647"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenqian Dong","raw_affiliation_strings":["EECS Department, Oregon State University, Corvallis, Oregon, USA"],"affiliations":[{"raw_affiliation_string":"EECS Department, Oregon State University, Corvallis, Oregon, USA","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Suparna Bhattacharya","orcid":"https://orcid.org/0000-0001-9541-4027"},"institutions":[{"id":"https://openalex.org/I4210117576","display_name":"Hewlett-Packard (India)","ror":"https://ror.org/02ffkja82","country_code":"IN","type":"company","lineage":["https://openalex.org/I1324840837","https://openalex.org/I4210117576"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Suparna Bhattacharya","raw_affiliation_strings":["AI Research Lab, HPE Labs, HPE, Bangalore, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"AI Research Lab, HPE Labs, HPE, Bangalore, Karnataka, India","institution_ids":["https://openalex.org/I4210117576"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Brian Sammuli","orcid":"https://orcid.org/0000-0002-3000-9327"},"institutions":[{"id":"https://openalex.org/I63533367","display_name":"General Atomics (United States)","ror":"https://ror.org/03ngjpk76","country_code":"US","type":"company","lineage":["https://openalex.org/I63533367"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Sammuli","raw_affiliation_strings":["Advanced Computing Center, General Atomics, San Diego, California, USA"],"affiliations":[{"raw_affiliation_string":"Advanced Computing Center, General Atomics, San Diego, California, USA","institution_ids":["https://openalex.org/I63533367"]}]},{"author_position":"last","author":{"id":null,"display_name":"Paolo Faraboschi","orcid":"https://orcid.org/0000-0003-4778-5696"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paolo Faraboschi","raw_affiliation_strings":["AI Research Lab, HPE Labs, HPE, Milpitas, California, USA"],"affiliations":[{"raw_affiliation_string":"AI Research Lab, HPE Labs, HPE, Milpitas, California, USA","institution_ids":["https://openalex.org/I4210122178"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":11,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210122178"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7607829,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"147","last_page":"155"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.8659999966621399,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.8659999966621399,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.05490000173449516,"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"}},{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.0066999997943639755,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.8337000012397766},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.63919997215271},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4894999861717224},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4693000018596649},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.460099995136261},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.45829999446868896},{"id":"https://openalex.org/keywords/container","display_name":"Container (type theory)","score":0.33410000801086426},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.31540000438690186}],"concepts":[{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.8337000012397766},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7861999869346619},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.63919997215271},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4894999861717224},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4693000018596649},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.45829999446868896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40139999985694885},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.396699994802475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3903000056743622},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3662000000476837},{"id":"https://openalex.org/C2781018962","wikidata":"https://www.wikidata.org/wiki/Q5164884","display_name":"Container (type theory)","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.31540000438690186},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.2985000014305115},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.26750001311302185},{"id":"https://openalex.org/C83283714","wikidata":"https://www.wikidata.org/wiki/Q121117","display_name":"Supercomputer","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.25839999318122864}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3757348.3757364","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3757348.3757364","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Cray User Group","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3757348.3757364","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3757348.3757364","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Cray User Group","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1981792447","https://openalex.org/W2194775991","https://openalex.org/W2909912937","https://openalex.org/W2966184765","https://openalex.org/W2971199049","https://openalex.org/W3179389344","https://openalex.org/W3216968833","https://openalex.org/W4211060442","https://openalex.org/W4280589740","https://openalex.org/W4392222151"],"related_works":[],"abstract_inverted_index":{"The":[0],"integration":[1],"of":[2,59,85,118,138,184],"AI":[3,39,88,133,143,146,201],"in":[4,37,62,99,203,207],"HPC":[5,13],"workflows":[6,34,64,102,202],"can":[7],"have":[8],"a":[9,82,153,204],"profound":[10],"impact":[11],"on":[12,30,152],"scale":[14],"and":[15,53,56,80,106,145,173,192],"usability,":[16],"for":[17,92,170],"example,":[18],"by":[19,44,164],"accelerating":[20],"simulations":[21,28],"with":[22,159,189],"surrogate":[23],"models":[24,40,89,179],"or":[25],"intelligently":[26],"steering":[27],"based":[29],"previous":[31,78],"results.":[32,185],"New":[33],"are":[35,41,187],"explored":[36],"which":[38],"iteratively":[42],"improved":[43],"continual":[45],"learning":[46,172],"to":[47,67,77,129,180,196],"better":[48,83],"reflect":[49],"input":[50],"data":[51,71,169],"distributions":[52],"avoid":[54],"outliers":[55],"drifts.":[57],"Tracking":[58],"model":[60,73],"provenance":[61,107],"these":[63],"is":[65,96],"important":[66],"understand":[68],"how":[69],"new":[70],"affect":[72],"performance,":[74],"allow":[75],"unwinding":[76],"iterations,":[79],"provide":[81],"understanding":[84],"conditions":[86],"where":[87],"perform":[90],"well":[91],"future":[93],"reuse.":[94],"This":[95],"more":[97],"challenging":[98],"hybrid":[100,130],"HPC-AI":[101],"because":[103],"the":[104,182],"lineage":[105],"must":[108],"be":[109],"tracked":[110],"across":[111,141],"multiple":[112],"software":[113],"components":[114],"at":[115],"different":[116,178],"levels":[117],"scale.":[119],"In":[120],"this":[121],"work,":[122],"we":[123],"extend":[124],"HPE":[125,149],"Common":[126],"Metadata":[127],"Framework":[128],"simulation":[131,199],"\u2013":[132,200],"workflows.":[134],"We":[135,166,186],"demonstrate":[136],"benefits":[137],"CMF":[139],"tracking":[140],"simulation,":[142],"training,":[144],"inference":[147],"along":[148],"SmartSim":[150],"system":[151],"simple":[154],"computational":[155],"fluid":[156],"dynamics":[157],"problem":[158],"Eddy":[160],"Kinetic":[161],"Energy":[162],"parameterized":[163],"AI.":[165],"track":[167],"out-of-distribution":[168],"continuous":[171],"employ":[174],"adaptive":[175],"switching":[176],"between":[177],"improve":[181],"quality":[183],"working":[188],"fusion":[190],"energy":[191],"materials":[193],"science":[194],"communities":[195],"enhance":[197],"coupled":[198],"similar":[205],"fashion":[206],"those":[208],"domains.":[209]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-11T00:00:00"}
