{"id":"https://openalex.org/W2132219981","doi":"https://doi.org/10.1145/1168857.1168881","title":"Accurate and efficient regression modeling for microarchitectural performance and power prediction","display_name":"Accurate and efficient regression modeling for microarchitectural performance and power prediction","publication_year":2006,"publication_date":"2006-10-20","ids":{"openalex":"https://openalex.org/W2132219981","doi":"https://doi.org/10.1145/1168857.1168881","mag":"2132219981"},"language":"en","primary_location":{"id":"doi:10.1145/1168857.1168881","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1168857.1168881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th international conference on Architectural support for programming languages and operating systems","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/A5003811456","display_name":"Benjamin C. Lee","orcid":"https://orcid.org/0000-0003-4472-6375"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Benjamin C. Lee","raw_affiliation_strings":["Harvard University"],"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026496503","display_name":"David Brooks","orcid":"https://orcid.org/0000-0002-0662-7889"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David M. Brooks","raw_affiliation_strings":["Harvard University"],"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5003811456"],"corresponding_institution_ids":["https://openalex.org/I2801851002"],"apc_list":null,"apc_paid":null,"fwci":25.9808,"has_fulltext":false,"cited_by_count":409,"citation_normalized_percentile":{"value":0.99855357,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"185","last_page":"194"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10363","display_name":"Low-power high-performance VLSI design","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/microarchitecture","display_name":"Microarchitecture","score":0.6876043677330017},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6673519611358643},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6639041304588318},{"id":"https://openalex.org/keywords/design-space-exploration","display_name":"Design space exploration","score":0.6254457235336304},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5378095507621765},{"id":"https://openalex.org/keywords/statistical-power","display_name":"Statistical power","score":0.523535966873169},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.5000813007354736},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.47232407331466675},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.46691110730171204},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.46211934089660645},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.43470266461372375},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37928545475006104},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3645203709602356},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3584774136543274},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3231264352798462},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2290087640285492},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.14877831935882568},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13994571566581726},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10704824328422546},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.09002459049224854}],"concepts":[{"id":"https://openalex.org/C107598950","wikidata":"https://www.wikidata.org/wiki/Q259864","display_name":"Microarchitecture","level":2,"score":0.6876043677330017},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6673519611358643},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6639041304588318},{"id":"https://openalex.org/C2776221188","wikidata":"https://www.wikidata.org/wiki/Q21072556","display_name":"Design space exploration","level":2,"score":0.6254457235336304},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5378095507621765},{"id":"https://openalex.org/C96608239","wikidata":"https://www.wikidata.org/wiki/Q1199823","display_name":"Statistical power","level":2,"score":0.523535966873169},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.5000813007354736},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.47232407331466675},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.46691110730171204},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.46211934089660645},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.43470266461372375},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37928545475006104},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3645203709602356},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3584774136543274},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3231264352798462},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2290087640285492},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.14877831935882568},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13994571566581726},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10704824328422546},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.09002459049224854},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1168857.1168881","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1168857.1168881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th international conference on Architectural support for programming languages and operating systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1488327529","https://openalex.org/W1981408476","https://openalex.org/W2000062521","https://openalex.org/W2070015279","https://openalex.org/W2073617099","https://openalex.org/W2096858484","https://openalex.org/W2106270437","https://openalex.org/W2109632314","https://openalex.org/W2115709314","https://openalex.org/W2120368896","https://openalex.org/W2134032953","https://openalex.org/W2139574045","https://openalex.org/W2153456949","https://openalex.org/W2154327203","https://openalex.org/W2157070686","https://openalex.org/W2158924248","https://openalex.org/W2165126693","https://openalex.org/W2287436271"],"related_works":["https://openalex.org/W4386869637","https://openalex.org/W4392309884","https://openalex.org/W4387251174","https://openalex.org/W2169880332","https://openalex.org/W4242293745","https://openalex.org/W3009555776","https://openalex.org/W2099305970","https://openalex.org/W2052801483","https://openalex.org/W2087838646","https://openalex.org/W2915863966"],"abstract_inverted_index":{"We":[0,118],"propose":[1],"regression":[2,59,124,205],"modeling":[3,52],"as":[4,93,95],"an":[5],"efficient":[6,69,196],"approach":[7],"for":[8,14,61,98,103,121,167,199],"accurately":[9],"predicting":[10],"performance":[11,62,99,135],"and":[12,44,53,57,63,100,137,195],"power":[13,140,157],"various":[15],"applications":[16],"executing":[17],"on":[18],"any":[19],"microprocessor":[20],"configuration":[21],"in":[22,33,78,134,156,193],"a":[23,83,122,177],"large":[24],"microarchitectural":[25,34,150,200],"design":[26,86,151,178,201],"space.":[27],"This":[28],"paper":[29],"addresses":[30],"fundamental":[31],"challenges":[32],"simulation":[35,74],"cost":[36],"by":[37],"reducing":[38],"the":[39,73,111,144,149,162],"number":[40,163],"of":[41,75,82,113,164,180],"required":[42],"simulations":[43],"using":[45],"simulated":[46,166],"results":[47,189],"more":[48],"effectively":[49],"via":[50,204],"statistical":[51,70,197],"inference.Specifically,":[54],"we":[55,170],"derive":[56],"validate":[58],"models":[60,66,107,130,141],"power.":[64,104],"Such":[65],"enable":[67],"computationally":[68],"inference,":[71],"requiring":[72],"only":[76,143],"1":[77],"5":[79],"million":[80],"points":[81,184],"joint":[84],"microarchitecture-application":[85],"space":[87,152,179,202],"while":[88],"achieving":[89],"median":[90],"error":[91],"rates":[92],"low":[94],"4.1":[96],"percent":[97,102],"4.3":[101],"Although":[105],"both":[106],"achieve":[108],"similar":[109],"accuracy,":[110],"sources":[112],"accuracy":[114,133,155],"are":[115,185],"strikingly":[116],"different.":[117],"present":[119],"optimizations":[120],"baseline":[123],"model":[125,168],"to":[126,131,153,161],"obtain":[127],"(1)":[128],"application-specific":[129],"maximize":[132,154],"prediction":[136],"(2)":[138],"regional":[139],"leveraging":[142],"most":[145],"relevant":[146],"samples":[147,165,175],"from":[148,176],"prediction.":[158],"Assessing":[159],"sensitivity":[160],"formulation,":[169],"find":[171],"fewer":[172],"than":[173],"4,000":[174],"approximately":[181],"22":[182],"billion":[183],"sufficient.":[186],"Collectively,":[187],"our":[188],"suggest":[190],"significant":[191],"potential":[192],"accurate":[194],"inference":[198],"exploration":[203],"models.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":22},{"year":2017,"cited_by_count":27},{"year":2016,"cited_by_count":21},{"year":2015,"cited_by_count":38},{"year":2014,"cited_by_count":26},{"year":2013,"cited_by_count":30},{"year":2012,"cited_by_count":33}],"updated_date":"2026-03-08T08:50:53.379069","created_date":"2025-10-10T00:00:00"}