{"id":"https://openalex.org/W2056058392","doi":"https://doi.org/10.1109/cloud.2014.41","title":"Optimizing Power and Performance Trade-offs of MapReduce Job Processing with Heterogeneous Multi-core Processors","display_name":"Optimizing Power and Performance Trade-offs of MapReduce Job Processing with Heterogeneous Multi-core Processors","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2056058392","doi":"https://doi.org/10.1109/cloud.2014.41","mag":"2056058392"},"language":"en","primary_location":{"id":"doi:10.1109/cloud.2014.41","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cloud.2014.41","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 7th International Conference on Cloud Computing","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/A5100381152","display_name":"Feng Yan","orcid":"https://orcid.org/0000-0001-9840-7754"},"institutions":[{"id":"https://openalex.org/I1324840837","display_name":"Hewlett-Packard (United States)","ror":"https://ror.org/059rn9488","country_code":"US","type":"company","lineage":["https://openalex.org/I1324840837"]},{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Feng Yan","raw_affiliation_strings":["College of William and Mary","Hewlett-Packard Labs"],"affiliations":[{"raw_affiliation_string":"College of William and Mary","institution_ids":["https://openalex.org/I16285277"]},{"raw_affiliation_string":"Hewlett-Packard Labs","institution_ids":["https://openalex.org/I1324840837"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016669578","display_name":"Ludmila Cherkasova","orcid":"https://orcid.org/0000-0002-9333-4901"},"institutions":[{"id":"https://openalex.org/I1324840837","display_name":"Hewlett-Packard (United States)","ror":"https://ror.org/059rn9488","country_code":"US","type":"company","lineage":["https://openalex.org/I1324840837"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ludmila Cherkasova","raw_affiliation_strings":["Hewlett-Packard Labs"],"affiliations":[{"raw_affiliation_string":"Hewlett-Packard Labs","institution_ids":["https://openalex.org/I1324840837"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011774662","display_name":"Zhuoyao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhuoyao Zhang","raw_affiliation_strings":["University of Pennsylvania"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I36788626"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017102040","display_name":"Evgenia Smirni","orcid":"https://orcid.org/0000-0001-8754-581X"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Evgenia Smirni","raw_affiliation_strings":["College of William and Mary"],"affiliations":[{"raw_affiliation_string":"College of William and Mary","institution_ids":["https://openalex.org/I16285277"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100381152"],"corresponding_institution_ids":["https://openalex.org/I1324840837","https://openalex.org/I16285277"],"apc_list":null,"apc_paid":null,"fwci":8.678,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.97338806,"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":"240","last_page":"247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":1.0,"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":1.0,"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":0.9979000091552734,"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.995199978351593,"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":0.8238674998283386},{"id":"https://openalex.org/keywords/multi-core-processor","display_name":"Multi-core processor","score":0.6560275554656982},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.625422477722168},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.6091936230659485},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5994716286659241},{"id":"https://openalex.org/keywords/job-scheduler","display_name":"Job scheduler","score":0.5733742117881775},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.5627416372299194},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.49727585911750793},{"id":"https://openalex.org/keywords/symmetric-multiprocessor-system","display_name":"Symmetric multiprocessor system","score":0.4664090871810913},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.43184927105903625},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4074234366416931},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.27117836475372314},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.14686545729637146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8238674998283386},{"id":"https://openalex.org/C78766204","wikidata":"https://www.wikidata.org/wiki/Q555032","display_name":"Multi-core processor","level":2,"score":0.6560275554656982},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.625422477722168},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.6091936230659485},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5994716286659241},{"id":"https://openalex.org/C111873713","wikidata":"https://www.wikidata.org/wiki/Q1641413","display_name":"Job scheduler","level":3,"score":0.5733742117881775},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.5627416372299194},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.49727585911750793},{"id":"https://openalex.org/C172430144","wikidata":"https://www.wikidata.org/wiki/Q17111997","display_name":"Symmetric multiprocessor system","level":2,"score":0.4664090871810913},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.43184927105903625},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4074234366416931},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.27117836475372314},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.14686545729637146},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"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/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cloud.2014.41","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cloud.2014.41","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 7th International Conference on Cloud Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1441180820","https://openalex.org/W1598064945","https://openalex.org/W1861377444","https://openalex.org/W1996438407","https://openalex.org/W2002472616","https://openalex.org/W2012181719","https://openalex.org/W2021446094","https://openalex.org/W2045635963","https://openalex.org/W2076164405","https://openalex.org/W2090441779","https://openalex.org/W2090732649","https://openalex.org/W2096125134","https://openalex.org/W2109569477","https://openalex.org/W2140486418","https://openalex.org/W2169875292","https://openalex.org/W2173213060","https://openalex.org/W2230666400","https://openalex.org/W2995564009","https://openalex.org/W6628401824","https://openalex.org/W6639193275","https://openalex.org/W6649353803","https://openalex.org/W6655732470","https://openalex.org/W6673329414","https://openalex.org/W6689360179"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W1996306926","https://openalex.org/W4253152747","https://openalex.org/W2473588286","https://openalex.org/W2048968534","https://openalex.org/W4308691326"],"abstract_inverted_index":{"Modern":[0],"processors":[1,97,155],"are":[2,84,92],"often":[3],"constrained":[4],"by":[5,55],"a":[6,34,45,59,65,135],"given":[7],"power":[8],"budget":[9],"that":[10,51,83,91,130],"forces":[11],"designers":[12],"to":[13,18,32,171,184],"consider":[14],"different":[15,77,106,127],"trade-offs,":[16],"e.g.,":[17],"choose":[19],"between":[20],"either":[21],"many":[22],"slow,":[23],"power-efficient":[24],"cores,":[25,30],"or":[26,31],"fewer":[27],"faster,":[28],"power-hungry":[29],"select":[33],"combination":[35],"of":[36,67,152,164],"them.":[37],"In":[38],"this":[39],"work,":[40],"we":[41,148],"design":[42],"and":[43,87,144],"evaluate":[44],"new":[46],"Hadoop":[47,115,136],"scheduler,":[48],"called":[49],"DyScale,":[50],"exploits":[52],"capabilities":[53],"offered":[54],"heterogeneous":[56,153],"cores":[57,120,123],"within":[58],"single":[60],"multi-core":[61,96,154],"processor":[62],"for":[63,109,161,187],"achieving":[64],"variety":[66],"performance":[68,78,128,159],"objectives.":[69],"A":[70],"typical":[71],"MapReduce":[72,168],"workload":[73],"contains":[74],"jobs":[75,82,90,169],"with":[76,138],"goals:":[79],"large,":[80,188],"batch":[81,189],"throughput":[85,182],"oriented,":[86],"smaller":[88],"interactive":[89,167],"response-time":[93],"sensitive.":[94],"Heterogeneous":[95],"enable":[98],"creating":[99],"virtual":[100,114],"resource":[101],"pools":[102],"based":[103,117],"on":[104,118],"the":[105,165,176],"core":[107],"types":[108],"multi-class":[110],"priority":[111],"scheduling.":[112],"These":[113],"clusters,":[116],"\"slow\"":[119],"versus":[121],"\"fast\"":[122],"can":[124],"effectively":[125],"support":[126],"objectives":[129],"cannot":[131],"be":[132],"achieved":[133],"in":[134,150],"cluster":[137],"homogeneous":[139],"processors.":[140],"Using":[141],"detailed":[142],"measurements":[143],"extensive":[145],"simulation":[146],"study":[147],"argue":[149],"favor":[151],"as":[156],"they":[157],"provide":[158],"means":[160],"\"faster\"":[162],"processing":[163],"small,":[166],"(up":[170,183],"40%":[172,185],"faster),":[173],"while":[174],"at":[175],"same":[177],"time":[178],"offer":[179],"an":[180],"improved":[181],"higher)":[186],"job":[190],"processing.":[191]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}