{"id":"https://openalex.org/W4251267405","doi":"https://doi.org/10.1109/islped.2013.6629278","title":"Breaking the boundary for whole-system performance optimization of big data","display_name":"Breaking the boundary for whole-system performance optimization of big data","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W4251267405","doi":"https://doi.org/10.1109/islped.2013.6629278"},"language":"en","primary_location":{"id":"doi:10.1109/islped.2013.6629278","is_oa":false,"landing_page_url":"https://doi.org/10.1109/islped.2013.6629278","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Symposium on Low Power Electronics and Design (ISLPED)","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/A5100380302","display_name":"Yan Li","orcid":"https://orcid.org/0000-0002-1126-9772"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Li","raw_affiliation_strings":["IBM Research, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100366692","display_name":"Kun Wang","orcid":"https://orcid.org/0000-0002-9099-2781"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Wang","raw_affiliation_strings":["IBM Research, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101834321","display_name":"Qi Guo","orcid":"https://orcid.org/0000-0002-8329-7668"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Guo","raw_affiliation_strings":["IBM Research, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353780","display_name":"Xin Li","orcid":"https://orcid.org/0000-0002-0041-3134"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["IBM Research, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100458555","display_name":"Xiaochen Zhang","orcid":"https://orcid.org/0000-0002-7154-5337"},"institutions":[{"id":"https://openalex.org/I174216632","display_name":"City University of New York","ror":"https://ror.org/00453a208","country_code":"US","type":"education","lineage":["https://openalex.org/I174216632"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaochen Zhang","raw_affiliation_strings":["City University of New York, USA"],"affiliations":[{"raw_affiliation_string":"City University of New York, USA","institution_ids":["https://openalex.org/I174216632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052260605","display_name":"Guancheng Chen","orcid":"https://orcid.org/0000-0002-4941-1543"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guancheng Chen","raw_affiliation_strings":["IBM Research, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100678890","display_name":"Tao Liu","orcid":"https://orcid.org/0000-0002-3709-7892"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Liu","raw_affiliation_strings":["IBM Research, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100402571","display_name":"Jian Li","orcid":"https://orcid.org/0000-0003-0894-0892"},"institutions":[{"id":"https://openalex.org/I4210156936","display_name":"IBM Research - Austin","ror":"https://ror.org/05gjbbg60","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210156936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Li","raw_affiliation_strings":["IBM Research-Austin, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research-Austin, USA","institution_ids":["https://openalex.org/I4210156936"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100380302"],"corresponding_institution_ids":["https://openalex.org/I4210126794"],"apc_list":null,"apc_paid":null,"fwci":2.4268,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.92209457,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9973000288009644,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9955000281333923,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8866366147994995},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7320401668548584},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.5968822836875916},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5516982674598694},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5331577062606812},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4539856016635895},{"id":"https://openalex.org/keywords/performance-tuning","display_name":"Performance tuning","score":0.44138002395629883},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.43609336018562317},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.4271343946456909},{"id":"https://openalex.org/keywords/performance-prediction","display_name":"Performance prediction","score":0.41939690709114075},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.41751405596733093},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3362082540988922},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.2594771087169647},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13873779773712158},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.11616447567939758}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8866366147994995},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7320401668548584},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.5968822836875916},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5516982674598694},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5331577062606812},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4539856016635895},{"id":"https://openalex.org/C2777138346","wikidata":"https://www.wikidata.org/wiki/Q1714153","display_name":"Performance tuning","level":2,"score":0.44138002395629883},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.43609336018562317},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.4271343946456909},{"id":"https://openalex.org/C2777115002","wikidata":"https://www.wikidata.org/wiki/Q7168246","display_name":"Performance prediction","level":2,"score":0.41939690709114075},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.41751405596733093},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3362082540988922},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.2594771087169647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13873779773712158},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.11616447567939758},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/islped.2013.6629278","is_oa":false,"landing_page_url":"https://doi.org/10.1109/islped.2013.6629278","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Symposium on Low Power Electronics and Design (ISLPED)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1834532152","https://openalex.org/W2020694540","https://openalex.org/W2048554864","https://openalex.org/W2059878010","https://openalex.org/W2060650311","https://openalex.org/W2102130607","https://openalex.org/W2122744911","https://openalex.org/W2126743076","https://openalex.org/W2154614053","https://openalex.org/W2168207031","https://openalex.org/W2173213060","https://openalex.org/W2323110450","https://openalex.org/W2552081135","https://openalex.org/W6639007902","https://openalex.org/W6662682235"],"related_works":["https://openalex.org/W2574266028","https://openalex.org/W1483675448","https://openalex.org/W2756782242","https://openalex.org/W4235049746","https://openalex.org/W2068649455","https://openalex.org/W2174199525","https://openalex.org/W2081167087","https://openalex.org/W2080961578","https://openalex.org/W2077946670","https://openalex.org/W2321868906"],"abstract_inverted_index":{"MapReduce":[0,15,132,157,221],"plays":[1],"an":[2],"critical":[3],"role":[4],"in":[5,8],"finding":[6],"insights":[7,103],"Big":[9],"Data.":[10],"The":[11,128,141],"performance":[12,53,83,91,96,108,159,208],"optimization":[13,56],"of":[14,25,50,79,114,117,130,153],"programs":[16],"is":[17,112,134],"challenging":[18],"because":[19],"it":[20],"requires":[21],"a":[22,66,72,90,115,131,144,167,172],"comprehensive":[23],"understanding":[24],"the":[26,51,77,107,137,181,189,204],"whole":[27],"system":[28],"including":[29],"both":[30],"hardware":[31],"layers":[32,81],"(processors,":[33],"storages,":[34],"networks":[35],"and":[36,38,46,55,61,223],"etc),":[37],"software":[39],"stacks":[40],"(operating":[41],"systems,":[42],"JVM,":[43,220],"runtime,":[44],"applications":[45],"etc).":[47],"However,":[48],"most":[49],"existing":[52],"tuning":[54],"are":[57,213],"based":[58],"on":[59,68,166,207],"empirical":[60],"heuristic":[62],"attempts.":[63],"It":[64],"remains":[65],"blank":[67],"how":[69,177],"to":[70,104,136,155,175,196,203],"build":[71],"systematical":[73],"framework":[74,93,111,142,179],"which":[75,101,147],"breaks":[76],"boundary":[78],"multiple":[80],"for":[82,219],"optimization.":[84,160],"In":[85,201],"this":[86,178,184],"paper,":[87],"we":[88,186],"propose":[89],"evaluation":[92],"by":[94],"correlating":[95],"metrics":[97],"from":[98,193],"different":[99,151],"layers,":[100],"provides":[102,143],"efficiently":[105],"pinpoint":[106],"issue.":[109],"This":[110],"composed":[113],"series":[116],"predefined":[118],"patterns.":[119],"Each":[120],"pattern":[121],"indicates":[122],"one":[123],"or":[124],"more":[125],"potential":[126],"issues.":[127],"behavior":[129],"program":[133,158],"mapped":[135],"corresponding":[138],"resource":[139],"utilization.":[140],"holistic":[145],"approach":[146],"allows":[148],"users":[149],"at":[150],"levels":[152],"experience":[154],"conduct":[156],"We":[161],"use":[162],"Terasort":[163,190],"benchmark":[164],"running":[165],"10-node":[168],"Power7R2":[169],"cluster":[170],"as":[171,215],"real":[173],"case":[174],"show":[176],"improves":[180],"performance.":[182],"By":[183],"framework,":[185],"finally":[187],"get":[188],"result":[191],"improved":[192],"47":[194],"mins":[195],"less":[197],"than":[198],"8":[199],"mins.":[200],"addition":[202],"best":[205],"practice":[206],"tuning,":[209],"several":[210],"key":[211],"findings":[212],"summarized":[214],"valuable":[216],"workload":[217],"analysis":[218],"runtime":[222],"application":[224],"design.":[225]},"counts_by_year":[{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
