{"id":"https://openalex.org/W2911520031","doi":"https://doi.org/10.1109/bigdata.2018.8622330","title":"Application of Comprehensive Data Analysis for Interactive, Hierarchical Views of HPC Workloads","display_name":"Application of Comprehensive Data Analysis for Interactive, Hierarchical Views of HPC Workloads","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2911520031","doi":"https://doi.org/10.1109/bigdata.2018.8622330","mag":"2911520031"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8622330","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622330","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 Big Data (Big Data)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5086757331","display_name":"Matthew B. Dwyer","orcid":"https://orcid.org/0000-0002-1937-1544"},"institutions":[{"id":"https://openalex.org/I1320675724","display_name":"Parsons (United States)","ror":"https://ror.org/001sezm06","country_code":"US","type":"company","lineage":["https://openalex.org/I1320675724"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Dwyer","raw_affiliation_strings":["Parsons Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Parsons Corporation","institution_ids":["https://openalex.org/I1320675724"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041402377","display_name":"John T. Hwang","orcid":"https://orcid.org/0000-0001-7280-0240"},"institutions":[{"id":"https://openalex.org/I1320675724","display_name":"Parsons (United States)","ror":"https://ror.org/001sezm06","country_code":"US","type":"company","lineage":["https://openalex.org/I1320675724"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Hwang","raw_affiliation_strings":["Parsons Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Parsons Corporation","institution_ids":["https://openalex.org/I1320675724"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104492823","display_name":"Alexander Shires","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Shires","raw_affiliation_strings":["University of Maryland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013165905","display_name":"Jacob Cohen","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacob Cohen","raw_affiliation_strings":["University of Maryland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6785,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67003766,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3585","last_page":"3589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9994999766349792,"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":0.9994999766349792,"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/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.9986000061035156,"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":0.9983999729156494,"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":0.8403630256652832},{"id":"https://openalex.org/keywords/downtime","display_name":"Downtime","score":0.582035481929779},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5779325366020203},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5471765398979187},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4938686490058899},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.45152655243873596},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.44253674149513245},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.4189787209033966},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.19043391942977905},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.18055227398872375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8403630256652832},{"id":"https://openalex.org/C180591934","wikidata":"https://www.wikidata.org/wiki/Q1253369","display_name":"Downtime","level":2,"score":0.582035481929779},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5779325366020203},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5471765398979187},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4938686490058899},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.45152655243873596},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.44253674149513245},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.4189787209033966},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.19043391942977905},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.18055227398872375},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2018.8622330","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622330","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 Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306078","display_name":"U.S. Department of Defense","ror":"https://ror.org/0447fe631"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1977614058","https://openalex.org/W2151316504","https://openalex.org/W2290151715","https://openalex.org/W2398646962","https://openalex.org/W2483795459","https://openalex.org/W2725626595","https://openalex.org/W2766228805","https://openalex.org/W2779653234","https://openalex.org/W2883906378","https://openalex.org/W2963330992","https://openalex.org/W2963946443","https://openalex.org/W6696597308","https://openalex.org/W6753443340"],"related_works":["https://openalex.org/W2046276983","https://openalex.org/W2954002293","https://openalex.org/W2892741875","https://openalex.org/W2164372000","https://openalex.org/W2078264086","https://openalex.org/W2109143577","https://openalex.org/W1985537075","https://openalex.org/W2161582432","https://openalex.org/W1972812226","https://openalex.org/W187383352"],"abstract_inverted_index":{"Alongside":[0],"advancements":[1],"in":[2,14,38,42,104,116,194],"computer":[3],"related":[4],"technologies,":[5],"High":[6],"Performance":[7],"Computing":[8],"(HPC)":[9],"systems":[10],"continue":[11,30],"to":[12,31,54,63,80,112,137,178,204],"grow":[13],"both":[15],"complexity":[16,39],"and":[17,23,48,73,89,118,141,157,190],"scale.":[18],"As":[19],"the":[20,68,123,146,172,191,195,200],"compute":[21],"capabilities":[22],"space":[24],"efficiency":[25,66],"of":[26,70,83,87,125,148,209],"these":[27,56],"powerful":[28],"machines":[29],"improve,":[32],"there":[33,59],"is":[34,96,106,202],"a":[35,161],"correlated":[36],"increase":[37],"which":[40],"results":[41],"increased":[43],"acquisition":[44],"costs,":[45],"node":[46,114],"failures,":[47],"operational":[49,128],"costs.":[50,129],"In":[51,130],"an":[52,135],"effort":[53],"address":[55],"growing":[57],"concerns,":[58],"have":[60],"been":[61],"attempts":[62],"improve":[64],"cost":[65],"through":[67,99],"use":[69,77],"data":[71,74,78,144,181,184,196],"analysis":[72,79,159,173,197],"monitoring.":[75],"Facilities":[76],"understand":[81],"causes":[82,86],"degraded":[84],"performance,":[85],"failure,":[88],"requirements":[90],"for":[91,168],"future":[92],"acquisitions.":[93],"This":[94],"information":[95],"often":[97],"obtained":[98],"ad-hoc":[100,155],"programs.":[101],"Data":[102],"monitoring,":[103,153],"turn,":[105],"used":[107],"by":[108],"HPC":[109],"facility":[110],"managers":[111],"detect":[113],"failures":[115,126],"real-time":[117],"decrease":[119],"downtime,":[120],"thereby":[121],"minimizing":[122],"impact":[124],"on":[127],"this":[131,143,187],"paper":[132],"we":[133],"present":[134],"application":[136],"ingest,":[138],"store,":[139],"analyze":[140],"display":[142],"at":[145],"scale":[147],"HPC.":[149],"Our":[150],"approach":[151],"brings":[152],"alerting,":[154],"analysis,":[156],"exploratory":[158],"into":[160],"single":[162],"integrated":[163],"solution.":[164],"Beyond":[165],"providing":[166],"support":[167],"existing":[169],"diagnostic":[170,180,210],"data,":[171],"pipeline":[174],"makes":[175],"it":[176],"simple":[177],"link":[179],"between":[182],"multiple":[183],"sources.":[185],"With":[186],"linking":[188],"capability":[189],"features":[192],"available":[193],"software":[198],"stack,":[199],"user":[201],"able":[203],"create":[205],"interactive,":[206],"hierarchical":[207],"views":[208],"data.":[211]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}