{"id":"https://openalex.org/W4248775335","doi":"https://doi.org/10.1109/iccad.2017.8203843","title":"P<sup>4</sup>: Phase-based power/performance prediction of heterogeneous systems via neural networks","display_name":"P<sup>4</sup>: Phase-based power/performance prediction of heterogeneous systems via neural networks","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W4248775335","doi":"https://doi.org/10.1109/iccad.2017.8203843"},"language":"en","primary_location":{"id":"doi:10.1109/iccad.2017.8203843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2017.8203843","pdf_url":null,"source":{"id":"https://openalex.org/S4363608376","display_name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","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/A5067380102","display_name":"Yeseong Kim","orcid":"https://orcid.org/0000-0001-5947-9632"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yeseong Kim","raw_affiliation_strings":["University of California San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020615383","display_name":"Pietro Mercati","orcid":"https://orcid.org/0000-0003-2842-7201"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pietro Mercati","raw_affiliation_strings":["University of California San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062538954","display_name":"Ankit More","orcid":"https://orcid.org/0009-0004-2813-3988"},"institutions":[{"id":"https://openalex.org/I4210158342","display_name":"Intel (United Kingdom)","ror":"https://ror.org/058cxws58","country_code":"GB","type":"company","lineage":["https://openalex.org/I1343180700","https://openalex.org/I4210158342"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ankit More","raw_affiliation_strings":["Intel Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intel Corporation","institution_ids":["https://openalex.org/I4210158342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015095396","display_name":"Emily Shriver","orcid":"https://orcid.org/0009-0003-2135-6428"},"institutions":[{"id":"https://openalex.org/I4210158342","display_name":"Intel (United Kingdom)","ror":"https://ror.org/058cxws58","country_code":"GB","type":"company","lineage":["https://openalex.org/I1343180700","https://openalex.org/I4210158342"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Emily Shriver","raw_affiliation_strings":["Intel Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intel Corporation","institution_ids":["https://openalex.org/I4210158342"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112841571","display_name":"Tajana Rosing","orcid":null},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tajana Rosing","raw_affiliation_strings":["University of California San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California San Diego","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7084,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.9137931,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"683","last_page":"690"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":1.0,"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":1.0,"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":0.9991000294685364,"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.9991000294685364,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7640690803527832},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7200436592102051},{"id":"https://openalex.org/keywords/x86","display_name":"x86","score":0.6675926446914673},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5896716117858887},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.48411500453948975},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46062391996383667},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4122653007507324},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3557233214378357},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.346628338098526},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3383482098579407},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.22581082582473755},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.15390434861183167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7640690803527832},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7200436592102051},{"id":"https://openalex.org/C170723468","wikidata":"https://www.wikidata.org/wiki/Q182933","display_name":"x86","level":3,"score":0.6675926446914673},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5896716117858887},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.48411500453948975},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46062391996383667},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4122653007507324},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3557233214378357},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.346628338098526},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3383482098579407},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.22581082582473755},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.15390434861183167},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccad.2017.8203843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2017.8203843","pdf_url":null,"source":{"id":"https://openalex.org/S4363608376","display_name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.9100000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W55699008","https://openalex.org/W98223237","https://openalex.org/W1468576370","https://openalex.org/W1926090661","https://openalex.org/W1963867219","https://openalex.org/W2028800864","https://openalex.org/W2035419218","https://openalex.org/W2051530471","https://openalex.org/W2054989513","https://openalex.org/W2073459066","https://openalex.org/W2082545328","https://openalex.org/W2097749765","https://openalex.org/W2130327500","https://openalex.org/W2169875292","https://openalex.org/W2401063723","https://openalex.org/W3010939381","https://openalex.org/W4234144196","https://openalex.org/W4245659854","https://openalex.org/W4254609974","https://openalex.org/W6604000583","https://openalex.org/W6656463566","https://openalex.org/W6668990524"],"related_works":["https://openalex.org/W3215381467","https://openalex.org/W2915956107","https://openalex.org/W4301207796","https://openalex.org/W4846490","https://openalex.org/W2099986681","https://openalex.org/W4240878335","https://openalex.org/W2216575582","https://openalex.org/W2048582679","https://openalex.org/W2782226720","https://openalex.org/W3155846967"],"abstract_inverted_index":{"The":[0],"emergence":[1],"of":[2,4,12,36,133],"Internet":[3],"Things":[5],"increases":[6],"the":[7,10,50,146,198,229,247],"complexity":[8],"and":[9,28,39,98,107,120,135,144,170,231,237],"heterogeneity":[11],"computing":[13,113,127,181],"platforms.":[14],"Migrating":[15],"workload":[16],"between":[17],"various":[18],"platforms":[19,128],"is":[20],"one":[21],"way":[22],"to":[23,141,167,191,210],"improve":[24],"both":[25],"energy":[26],"efficiency":[27],"performance.":[29],"Effective":[30],"migration":[31],"decisions":[32],"require":[33],"accurate":[34,78],"estimates":[35,44,61],"its":[37],"costs":[38],"benefits.":[40],"To":[41],"date,":[42],"these":[43,157],"were":[45,175],"done":[46],"by":[47,58,125],"either":[48],"instrumenting":[49],"source":[51],"code/binaries,":[52],"thus":[53],"causing":[54],"high":[55],"overhead,":[56],"or":[57],"using":[59],"power":[60,106,171,230],"from":[62,207,246],"hardware":[63],"performance":[64,108,161,169,232],"counters,":[65],"which":[66,102],"work":[67],"well":[68],"for":[69,79,111,150,242],"individual":[70],"machines,":[71],"but":[72],"until":[73],"now":[74],"have":[75],"not":[76],"been":[77],"predicting":[80],"across":[81],"different":[82,180,185,244],"architectures.":[83],"In":[84],"this":[85],"paper,":[86],"we":[87],"propose":[88],"P":[89,115,223],"<sup":[90,116,224],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[91,117,225],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">4</sup>":[92,118,226],",":[93],"a":[94,131,178,184],"new":[95],"Phase-based":[96],"Power":[97],"Performance":[99],"Prediction":[100],"framework":[101,200],"identifies":[103],"cross-platform":[104,148],"application":[105,123],"at":[109,165],"runtime":[110,166],"heterogeneous":[112,204],"systems.":[114],"analyzes":[119],"detects":[121],"machine-independent":[122],"phases":[124],"characterizing":[126],"offline":[129],"with":[130,160,214,234],"set":[132],"benchmarks,":[134],"then":[136,155],"builds":[137],"neural":[138],"network-based":[139],"models":[140,158],"automatically":[142],"identify":[143],"generalize":[145],"complex":[147],"relationships":[149],"each":[151],"benchmark":[152],"phase.":[153],"It":[154],"leverages":[156],"along":[159],"counter":[162],"measurements":[163],"collected":[164],"estimate":[168],"consumption":[172],"if":[173],"it":[174,193],"running":[176],"on":[177,194,201],"completely":[179,243],"platform,":[182],"including":[183],"CPU":[186],"architecture,":[187,213],"without":[188],"ever":[189],"having":[190],"run":[192],"there.":[195],"We":[196],"evaluate":[197],"proposed":[199],"four":[202],"commercial":[203],"platforms,":[205],"ranging":[206],"X86":[208],"servers":[209],"mobile":[211],"ARM-based":[212],"129":[215],"industry-standard":[216],"benchmarks.":[217],"Our":[218],"experimental":[219],"results":[220],"show":[221],"that":[222],"can":[227],"predict":[228],"changes":[233],"only":[235],"6.8%":[236],"5.6%":[238],"error,":[239],"respectively,":[240],"even":[241],"architectures":[245],"ones":[248],"applications":[249],"ran":[250],"on.":[251]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}