{"id":"https://openalex.org/W2962760064","doi":"https://doi.org/10.1145/3337821.3337834","title":"ECoST","display_name":"ECoST","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2962760064","doi":"https://doi.org/10.1145/3337821.3337834","mag":"2962760064"},"language":"en","primary_location":{"id":"doi:10.1145/3337821.3337834","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3337821.3337834","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International Conference on Parallel Processing","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/A5010278061","display_name":"Maria Malik","orcid":"https://orcid.org/0000-0001-8425-2501"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Maria Malik","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007139473","display_name":"Hassan Ghasemzadeh","orcid":"https://orcid.org/0000-0002-1844-1416"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hassan Ghasemzadeh","raw_affiliation_strings":["Department of Computer Science, Washington State University, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Washington State University, USA","institution_ids":["https://openalex.org/I72951846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084010501","display_name":"Tinoosh Mohsenin","orcid":"https://orcid.org/0000-0001-5551-2124"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tinoosh Mohsenin","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085883266","display_name":"Rosario Cammarota","orcid":"https://orcid.org/0000-0002-2965-8987"},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rosario Cammarota","raw_affiliation_strings":["Intel, USA"],"affiliations":[{"raw_affiliation_string":"Intel, USA","institution_ids":["https://openalex.org/I1343180700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048756500","display_name":"Liang Zhao","orcid":"https://orcid.org/0000-0002-2648-9989"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Zhao","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060036961","display_name":"Avesta Sasan","orcid":"https://orcid.org/0000-0002-4052-8075"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Avesta Sasan","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047382437","display_name":"Houman Homayoun","orcid":"https://orcid.org/0000-0001-8904-4699"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Houman Homayoun","raw_affiliation_strings":["University of California Davis, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051940611","display_name":"Setareh Rafatirad","orcid":"https://orcid.org/0000-0002-0626-9778"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Setareh Rafatirad","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5010278061"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":2.0349,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.898201,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9998999834060669,"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/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/T12127","display_name":"Software System Performance and Reliability","score":0.9976000189781189,"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":0.8332772254943848},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7748290300369263},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6855143308639526},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.6731851696968079},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6481199264526367},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5904625654220581},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5747705698013306},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.49277427792549133},{"id":"https://openalex.org/keywords/massively-parallel","display_name":"Massively parallel","score":0.4700820744037628},{"id":"https://openalex.org/keywords/data-intensive-computing","display_name":"Data-intensive computing","score":0.45881351828575134},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.4139467477798462},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.26292169094085693},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.19002416729927063},{"id":"https://openalex.org/keywords/grid-computing","display_name":"Grid computing","score":0.14984866976737976}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8332772254943848},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7748290300369263},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6855143308639526},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.6731851696968079},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6481199264526367},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5904625654220581},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5747705698013306},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.49277427792549133},{"id":"https://openalex.org/C190475519","wikidata":"https://www.wikidata.org/wiki/Q544384","display_name":"Massively parallel","level":2,"score":0.4700820744037628},{"id":"https://openalex.org/C76831024","wikidata":"https://www.wikidata.org/wiki/Q5227096","display_name":"Data-intensive computing","level":4,"score":0.45881351828575134},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.4139467477798462},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.26292169094085693},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.19002416729927063},{"id":"https://openalex.org/C70429105","wikidata":"https://www.wikidata.org/wiki/Q249999","display_name":"Grid computing","level":3,"score":0.14984866976737976},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3337821.3337834","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3337821.3337834","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International Conference on Parallel Processing","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":0.8500000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1485435899","https://openalex.org/W1586654869","https://openalex.org/W1855098165","https://openalex.org/W1986800449","https://openalex.org/W1992752524","https://openalex.org/W2038361169","https://openalex.org/W2078994750","https://openalex.org/W2086291744","https://openalex.org/W2102709380","https://openalex.org/W2116785402","https://openalex.org/W2118651798","https://openalex.org/W2121884932","https://openalex.org/W2141181087","https://openalex.org/W2141249441","https://openalex.org/W2142719274","https://openalex.org/W2146434221","https://openalex.org/W2150139096","https://openalex.org/W2155072926","https://openalex.org/W2160121678","https://openalex.org/W2169380619","https://openalex.org/W2170382128","https://openalex.org/W2172339043","https://openalex.org/W2198342846","https://openalex.org/W2401224581","https://openalex.org/W2416173365","https://openalex.org/W2542189141","https://openalex.org/W2547552176","https://openalex.org/W2613215347","https://openalex.org/W2642383336","https://openalex.org/W2768424695","https://openalex.org/W2772687287","https://openalex.org/W2789494740","https://openalex.org/W2795242415","https://openalex.org/W2883173712","https://openalex.org/W2884029204","https://openalex.org/W2890774642","https://openalex.org/W2893549539","https://openalex.org/W2911037141","https://openalex.org/W2997451313","https://openalex.org/W4205941017","https://openalex.org/W4233484638","https://openalex.org/W4236491543","https://openalex.org/W4253824360","https://openalex.org/W6681038754"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W4233347783","https://openalex.org/W2910064364","https://openalex.org/W2794953737","https://openalex.org/W2615669199"],"abstract_inverted_index":{"Datacenters":[0],"provide":[1],"high":[2],"performance":[3,64,220,227],"and":[4,8,38,44,65,85,98,108,156,162,185,219,230],"flexibility":[5],"for":[6,11,21,189,217],"users":[7],"cost":[9],"efficiency":[10,265],"operators.":[12],"Hyperscale":[13],"datacenters":[14],"are":[15,88,113,214],"harnessing":[16],"massively":[17],"scalable":[18],"computer":[19],"resources":[20],"large-scale":[22],"data":[23,36,43,121,190,229,262],"analysis.":[24],"However,":[25],"cloud/datacenter":[26],"infrastructure":[27],"does":[28],"not":[29],"scale":[30],"as":[31,33,237,239,248,250],"fast":[32],"the":[34,55,82,95,102,135,158,169,175,182,256,271],"input":[35],"volume":[37],"computational":[39,178],"requirements":[40],"of":[41,101,110,177,195,258,270,290],"big":[42,120],"analytics":[45],"technologies.":[46],"Thus,":[47],"more":[48],"applications":[49,93,112,122,151,278],"need":[50,144],"to":[51,91,133,145,167,247,254],"share":[52],"CPU":[53],"at":[54,81,94,152,279],"node":[56,96,154,281],"level":[57,97,155,164],"that":[58,149],"could":[59],"have":[60],"large":[61],"impact":[62],"on":[63,200,208,293],"operational":[66],"cost.":[67],"To":[68],"address":[69],"this":[70,73],"challenge,":[71],"in":[72],"paper":[74],"we":[75],"show":[76,263],"that,":[77],"concurrently":[78,123],"fine-tune":[79],"parameters":[80,166,216],"application,":[83],"microarchitecture,":[84],"system":[86],"levels":[87],"creating":[89],"opportunities":[90],"co-locate":[92],"improve":[99],"energy-efficiency":[100,257],"server":[103],"while":[104],"maintaining":[105],"performance.":[106],"Co-locating":[107],"self-tuning":[109],"unknown":[111],"challenging":[114],"problems,":[115],"especially":[116],"when":[117,275],"co-locating":[118,276],"multiple":[119,277],"with":[124],"many":[125],"tuning":[126,221],"knobs,":[127],"potentially":[128],"requiring":[129],"exhaustive":[130],"brute-force":[131],"search":[132],"find":[134],"right":[136],"settings.":[137],"This":[138],"research":[139],"challenge":[140],"upsurges":[141],"an":[142,294],"imminent":[143],"develop":[146],"a":[147,153,240,280],"technique":[148,188],"co-locates":[150],"predict":[157,255],"optimal":[159],"system,":[160],"architecture":[161],"application":[163],"configure":[165],"achieve":[168],"maximum":[170],"energy":[171,264],"efficiency.":[172],"It":[173],"promotes":[174],"scale-down":[176],"nodes":[179],"by":[180],"presenting":[181],"Energy-Efficient":[183],"Co-Locating":[184],"Self-Tuning":[186],"(ECoST)":[187],"intensive":[191],"applications.":[192,260],"ECoST":[193,203,223,283],"proof":[194],"concept":[196],"was":[197],"successfully":[198],"tested":[199],"MapReduce":[201],"platform.":[202],"can":[204],"also":[205,285],"be":[206],"deployed":[207],"other":[209],"data-intensive":[210],"frameworks":[211],"where":[212],"there":[213],"several":[215],"power":[218],"optimizations.":[222],"collects":[224],"run-time":[225],"hardware":[226],"counter":[228],"implements":[231],"various":[232],"machine":[233],"learning":[234],"models":[235],"from":[236],"simple":[238],"lookup":[241],"table":[242],"or":[243],"decision":[244],"tree":[245],"based":[246,253],"complex":[249],"neural":[251],"network":[252],"co-located":[259],"Experimental":[261],"is":[266,284],"achieved":[267],"within":[268,288],"4%":[269],"upper":[272,291],"bound":[273,292],"results":[274],"level.":[282],"scalable,":[286],"being":[287],"8%":[289],"8-node":[295],"server.":[296]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-07-30T00:00:00"}