{"id":"https://openalex.org/W4385429973","doi":"https://doi.org/10.1145/3588993.3597262","title":"HPC Application Performance Prediction with Machine Learning on New Architectures","display_name":"HPC Application Performance Prediction with Machine Learning on New Architectures","publication_year":2023,"publication_date":"2023-07-28","ids":{"openalex":"https://openalex.org/W4385429973","doi":"https://doi.org/10.1145/3588993.3597262"},"language":"en","primary_location":{"id":"doi:10.1145/3588993.3597262","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3588993.3597262","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3588993.3597262","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn Strategy","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3588993.3597262","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009000154","display_name":"Dewi Yokelson","orcid":"https://orcid.org/0000-0003-1453-5906"},"institutions":[{"id":"https://openalex.org/I181233156","display_name":"University of Oregon","ror":"https://ror.org/0293rh119","country_code":"US","type":"education","lineage":["https://openalex.org/I181233156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dewi Yokelson","raw_affiliation_strings":["University of Oregon, Eugene, OR, USA"],"raw_orcid":"https://orcid.org/0000-0003-1453-5906","affiliations":[{"raw_affiliation_string":"University of Oregon, Eugene, OR, USA","institution_ids":["https://openalex.org/I181233156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036404793","display_name":"Marc Charest","orcid":"https://orcid.org/0000-0002-2818-1232"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marc Robert Joseph Charest","raw_affiliation_strings":["Microsoft, Seattle, WA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2818-1232","affiliations":[{"raw_affiliation_string":"Microsoft, Seattle, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060737716","display_name":"Ying Wai Li","orcid":"https://orcid.org/0000-0003-0124-8262"},"institutions":[{"id":"https://openalex.org/I1343871089","display_name":"Los Alamos National Laboratory","ror":"https://ror.org/01e41cf67","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I1343871089","https://openalex.org/I198811213","https://openalex.org/I4210120050"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ying Wai Li","raw_affiliation_strings":["Los Alamos National Laboratory, Los Alamos, NM, USA"],"raw_orcid":"https://orcid.org/0000-0003-0124-8262","affiliations":[{"raw_affiliation_string":"Los Alamos National Laboratory, Los Alamos, NM, USA","institution_ids":["https://openalex.org/I1343871089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0862,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.87764173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12127","display_name":"Software System Performance and Reliability","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11986","display_name":"Scientific Computing and Data Management","score":0.9864000082015991,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.815585732460022},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7305383086204529},{"id":"https://openalex.org/keywords/performance-prediction","display_name":"Performance prediction","score":0.7101432681083679},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6415673494338989},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6403270959854126},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4712921679019928},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.47101032733917236},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44096994400024414},{"id":"https://openalex.org/keywords/execution-time","display_name":"Execution time","score":0.4396439790725708},{"id":"https://openalex.org/keywords/performance-improvement","display_name":"Performance improvement","score":0.43529850244522095},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4247778058052063},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3625904619693756},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.2511037588119507},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.12582308053970337},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07729625701904297}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.815585732460022},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7305383086204529},{"id":"https://openalex.org/C2777115002","wikidata":"https://www.wikidata.org/wiki/Q7168246","display_name":"Performance prediction","level":2,"score":0.7101432681083679},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6415673494338989},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6403270959854126},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4712921679019928},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.47101032733917236},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44096994400024414},{"id":"https://openalex.org/C2989134064","wikidata":"https://www.wikidata.org/wiki/Q288510","display_name":"Execution time","level":2,"score":0.4396439790725708},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.43529850244522095},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4247778058052063},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3625904619693756},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.2511037588119507},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.12582308053970337},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07729625701904297},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3588993.3597262","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3588993.3597262","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3588993.3597262","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn Strategy","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3588993.3597262","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3588993.3597262","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3588993.3597262","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn Strategy","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6563880843","display_name":null,"funder_award_id":"No.  89233218CNA000001","funder_id":"https://openalex.org/F4320332369","funder_display_name":"National Nuclear Security Administration"},{"id":"https://openalex.org/G6995210142","display_name":null,"funder_award_id":"89233218CNA000001","funder_id":"https://openalex.org/F4320332369","funder_display_name":"National Nuclear Security Administration"},{"id":"https://openalex.org/G7500863821","display_name":null,"funder_award_id":"89233218CNA000001","funder_id":"https://openalex.org/F4320338304","funder_display_name":"Los Alamos National Laboratory"},{"id":"https://openalex.org/G8659807574","display_name":null,"funder_award_id":"89233218CNA000001","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320332369","display_name":"National Nuclear Security Administration","ror":"https://ror.org/03sk1we31"},{"id":"https://openalex.org/F4320338304","display_name":"Los Alamos National Laboratory","ror":"https://ror.org/01e41cf67"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385429973.pdf","grobid_xml":"https://content.openalex.org/works/W4385429973.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W2070493638","https://openalex.org/W2071678527","https://openalex.org/W2806583692","https://openalex.org/W2900365206","https://openalex.org/W2919115771","https://openalex.org/W2951642938","https://openalex.org/W2970442534","https://openalex.org/W2997591727","https://openalex.org/W2999925821","https://openalex.org/W3027308092","https://openalex.org/W3042713993","https://openalex.org/W3100344569","https://openalex.org/W3104906823","https://openalex.org/W4224226906","https://openalex.org/W4246704440","https://openalex.org/W4255455317"],"related_works":["https://openalex.org/W2083862258","https://openalex.org/W2397087612","https://openalex.org/W153340049","https://openalex.org/W2110529327","https://openalex.org/W4210891154","https://openalex.org/W61261787","https://openalex.org/W2803417426","https://openalex.org/W2371116970","https://openalex.org/W2802138742","https://openalex.org/W3207786695"],"abstract_inverted_index":{"We":[0],"explore":[1],"a":[2,78,141],"modeling":[3],"approach":[4,63,122],"for":[5,26,55,68,87,110,186],"scientific":[6],"application":[7,187],"performance":[8,30,57,69,102,113,191],"on":[9,159],"high-performance":[10],"computer":[11,162],"architectures":[12],"using":[13],"machine":[14,61,91],"learning":[15,62,92],"techniques.":[16],"Multiple":[17],"linear":[18],"regression":[19],"models":[20,31,93,132],"and":[21,140,176],"neural":[22,142],"networks":[23],"were":[24,50,94],"evaluated":[25],"effectiveness":[27],"in":[28,116,124],"constructing":[29],"to":[32,76,97,138,154,168],"predict":[33,98,155],"the":[34,56,65,84,108,111,117,156],"execution":[35,88,157],"time":[36,89,158],"of":[37,80,101,149],"an":[38,134,146,160],"application.":[39],"Performance":[40],"metrics":[41,81],"collected":[42],"during":[43,127],"run":[44],"time,":[45],"together":[46],"with":[47],"hardware":[48,175],"specifications,":[49],"used":[51],"as":[52,107],"input":[53],"features":[54],"models.":[58],"Our":[59],"two-step":[60,121],"improved":[64],"R^2":[66,135,147],"score":[67,136,148],"prediction:":[70],"we":[71],"first":[72],"performed":[73],"feature":[74],"selection":[75],"select":[77],"subset":[79,100],"that":[82,171,180],"are":[83,166],"most":[85],"relevant":[86],"prediction;":[90],"then":[95,105],"trained":[96],"this":[99],"metrics,":[103],"which":[104],"served":[106],"inputs":[109],"final":[112],"model":[114,144],"construction":[115],"second":[118],"step.":[119],"This":[120],"resulted":[123],"promising":[125],"results":[126,165],"our":[128,181],"case":[129],"study.":[130],"Regression":[131],"achieved":[133,145],"up":[137],"93%":[139],"network":[143],"over":[150],"94%":[151],"when":[152],"applied":[153],"unseen":[161],"architecture.":[163],"These":[164],"comparable":[167],"existing":[169],"methods":[170],"require":[172],"more":[173,184],"upfront":[174],"systems":[177],"knowledge,":[178],"implying":[179],"method":[182],"is":[183],"approachable":[185],"developers":[188],"without":[189],"extensive":[190],"knowledge.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
