{"id":"https://openalex.org/W2899430097","doi":"https://doi.org/10.1109/cluster.2018.00070","title":"Modeling Expected Application Runtime for Characterizing and Assessing Job Performance","display_name":"Modeling Expected Application Runtime for Characterizing and Assessing Job Performance","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2899430097","doi":"https://doi.org/10.1109/cluster.2018.00070","mag":"2899430097"},"language":"en","primary_location":{"id":"doi:10.1109/cluster.2018.00070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cluster.2018.00070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Cluster Computing (CLUSTER)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030343676","display_name":"Omar Aaziz","orcid":"https://orcid.org/0009-0000-9651-0299"},"institutions":[{"id":"https://openalex.org/I4210104735","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210104735"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Omar Aaziz","raw_affiliation_strings":["Sandia National Laboratories, Albuquerque, NM"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sandia National Laboratories, Albuquerque, NM","institution_ids":["https://openalex.org/I4210104735"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014312938","display_name":"Jonathan Cook","orcid":"https://orcid.org/0000-0003-4907-5719"},"institutions":[{"id":"https://openalex.org/I10052268","display_name":"New Mexico State University","ror":"https://ror.org/00hpz7z43","country_code":"US","type":"education","lineage":["https://openalex.org/I10052268"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan Cook","raw_affiliation_strings":["New Mexico State University, Las Cruces, NM"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Mexico State University, Las Cruces, NM","institution_ids":["https://openalex.org/I10052268"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063403585","display_name":"Mohammed Tanash","orcid":"https://orcid.org/0000-0002-2877-5735"},"institutions":[{"id":"https://openalex.org/I10052268","display_name":"New Mexico State University","ror":"https://ror.org/00hpz7z43","country_code":"US","type":"education","lineage":["https://openalex.org/I10052268"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammed Tanash","raw_affiliation_strings":["New Mexico State University, Las Cruces, NM"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Mexico State University, Las Cruces, NM","institution_ids":["https://openalex.org/I10052268"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3953,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67358189,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"31","issue":null,"first_page":"543","last_page":"551"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9995999932289124,"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":0.9995999932289124,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9994999766349792,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.9994000196456909,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7960339784622192},{"id":"https://openalex.org/keywords/job-scheduler","display_name":"Job scheduler","score":0.562172532081604},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5335180163383484},{"id":"https://openalex.org/keywords/job-performance","display_name":"Job performance","score":0.5074393153190613},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.47485804557800293},{"id":"https://openalex.org/keywords/proxy","display_name":"Proxy (statistics)","score":0.45901361107826233},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4459892213344574},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.41053056716918945},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.23027577996253967},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.16238290071487427},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12209346890449524},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07608622312545776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7960339784622192},{"id":"https://openalex.org/C111873713","wikidata":"https://www.wikidata.org/wiki/Q1641413","display_name":"Job scheduler","level":3,"score":0.562172532081604},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5335180163383484},{"id":"https://openalex.org/C174954385","wikidata":"https://www.wikidata.org/wiki/Q6206740","display_name":"Job performance","level":3,"score":0.5074393153190613},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.47485804557800293},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.45901361107826233},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4459892213344574},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.41053056716918945},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.23027577996253967},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.16238290071487427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12209346890449524},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07608622312545776},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C2718322","wikidata":"https://www.wikidata.org/wiki/Q629463","display_name":"Job satisfaction","level":2,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cluster.2018.00070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cluster.2018.00070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Cluster Computing (CLUSTER)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W56226570","https://openalex.org/W83535271","https://openalex.org/W94052953","https://openalex.org/W583100948","https://openalex.org/W1540325530","https://openalex.org/W2010540152","https://openalex.org/W2011516616","https://openalex.org/W2020538806","https://openalex.org/W2038924755","https://openalex.org/W2095127626","https://openalex.org/W2101587002","https://openalex.org/W2101778912","https://openalex.org/W2108177987","https://openalex.org/W2110399624","https://openalex.org/W2136434791","https://openalex.org/W2152419477","https://openalex.org/W2337228275","https://openalex.org/W2562696307","https://openalex.org/W2564237233","https://openalex.org/W3004935110","https://openalex.org/W4235580647","https://openalex.org/W4246569695","https://openalex.org/W4252521241","https://openalex.org/W4252637763","https://openalex.org/W4255616683","https://openalex.org/W6602337924","https://openalex.org/W6617190919","https://openalex.org/W6703177460","https://openalex.org/W6730927469"],"related_works":["https://openalex.org/W2028495302","https://openalex.org/W4249498729","https://openalex.org/W2002261065","https://openalex.org/W1513656766","https://openalex.org/W1967083444","https://openalex.org/W2160863446","https://openalex.org/W2106866459","https://openalex.org/W2361609491","https://openalex.org/W4239167708","https://openalex.org/W3121666323"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,13,39,50,68],"methodology":[6],"for":[7,31,33],"modeling":[8],"the":[9,23,43,55,83],"expected":[10],"runtime":[11,46,85],"of":[12,52,54,111],"job":[14,24,45,59,76,84],"based":[15],"on":[16],"historical":[17,92],"application":[18,93],"data":[19,21],"and":[20,36,63,74,101],"from":[22,91],"itself.":[25],"This":[26],"estimation":[27],"model":[28,73],"is":[29],"useful":[30],"both":[32],"HPC":[34],"users":[35],"administrators":[37],"as":[38],"metric":[40],"to":[41,72],"compare":[42],"actual":[44,112],"to,":[47],"thus":[48],"establishing":[49],"measure":[51],"performance":[53,65],"job.":[56],"We":[57,95],"used":[58],"data,":[60,62],"system":[61],"hardware":[64],"counters":[66],"in":[67,78,87],"near-zero":[69],"overhead":[70],"manner":[71],"assess":[75],"performance,":[77],"particular":[79],"whether":[80],"or":[81],"not":[82],"was":[86],"line":[88],"with":[89],"expectations":[90],"performance.":[94,113],"show":[96],"over":[97],"three":[98,102],"proxy":[99],"applications":[100,104],"real":[103],"that":[105],"our":[106],"estimations":[107],"are":[108],"within":[109],"5%":[110]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}