{"id":"https://openalex.org/W4230608487","doi":"https://doi.org/10.1109/date.2010.5457139","title":"Process variation and temperature-aware reliability management","display_name":"Process variation and temperature-aware reliability management","publication_year":2010,"publication_date":"2010-03-01","ids":{"openalex":"https://openalex.org/W4230608487","doi":"https://doi.org/10.1109/date.2010.5457139"},"language":"en","primary_location":{"id":"doi:10.1109/date.2010.5457139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/date.2010.5457139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010)","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/A5054211420","display_name":"Cheng Zhuo","orcid":"https://orcid.org/0000-0002-2610-7522"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Cheng Zhuo","raw_affiliation_strings":["EECS Department, University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000767141","display_name":"Dennis Sylvester","orcid":"https://orcid.org/0000-0003-2598-0458"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dennis Sylvester","raw_affiliation_strings":["EECS Department, University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026311377","display_name":"David Blaauw","orcid":"https://orcid.org/0000-0001-6744-7075"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Blaauw","raw_affiliation_strings":["EECS Department, University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054211420"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":2.0205,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.8819709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"580","last_page":"585"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11005","display_name":"Radiation Effects in Electronics","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11005","display_name":"Radiation Effects in Electronics","score":0.9998000264167786,"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/T10472","display_name":"Semiconductor materials and devices","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/T10363","display_name":"Low-power high-performance VLSI design","score":0.9986000061035156,"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/reliability","display_name":"Reliability (semiconductor)","score":0.7947217226028442},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7754107117652893},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.7323666214942932},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6001458168029785},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5690810680389404},{"id":"https://openalex.org/keywords/process-variation","display_name":"Process variation","score":0.5571221113204956},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5260719656944275},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5055196285247803},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.49508801102638245},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.48111075162887573},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.13075894117355347},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10200342535972595},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.09178701043128967}],"concepts":[{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.7947217226028442},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7754107117652893},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.7323666214942932},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6001458168029785},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5690810680389404},{"id":"https://openalex.org/C93389723","wikidata":"https://www.wikidata.org/wiki/Q7247313","display_name":"Process variation","level":3,"score":0.5571221113204956},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5260719656944275},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5055196285247803},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.49508801102638245},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.48111075162887573},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.13075894117355347},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10200342535972595},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.09178701043128967},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/date.2010.5457139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/date.2010.5457139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010)","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":19,"referenced_works":["https://openalex.org/W1882151751","https://openalex.org/W1890614305","https://openalex.org/W1923733561","https://openalex.org/W2032069904","https://openalex.org/W2066815871","https://openalex.org/W2114840932","https://openalex.org/W2121319784","https://openalex.org/W2125169487","https://openalex.org/W2126564504","https://openalex.org/W2154857344","https://openalex.org/W2160207526","https://openalex.org/W3139960886","https://openalex.org/W3140903683","https://openalex.org/W3147797681","https://openalex.org/W3150603910","https://openalex.org/W4231523873","https://openalex.org/W6639550676","https://openalex.org/W6678664461","https://openalex.org/W6792941224"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W4391547476","https://openalex.org/W2597809628"],"abstract_inverted_index":{"In":[0,68,96],"aggressively":[1],"scaled":[2],"technologies,":[3],"reliability":[4,16,34,105,120,140],"concerns":[5],"such":[6],"as":[7,22],"oxide":[8],"breakdown":[9],"have":[10,61],"become":[11],"a":[12,23,62,101,131,146],"key":[13],"issue.":[14],"Dynamic":[15],"management":[17,106],"(DRM)":[18],"has":[19],"been":[20],"proposed":[21],"mechanism":[24],"to":[25,81,90,130,136,160,167],"dynamically":[26],"explore":[27],"the":[28,43,72,76,82,115,124,138,182],"trade-off":[29],"between":[30],"system":[31,139],"performance":[32,188],"and":[33,52,57,94,117,141,185],"margin.":[35],"However,":[36],"existing":[37],"DRM":[38,178],"methods":[39],"are":[40,79],"hampered":[41],"by":[42],"fact":[44],"that":[45,75,108],"they":[46,70],"do":[47],"not":[48],"accurately":[49],"model":[50],"spatial":[51],"temporal":[53],"variations":[54,93,112],"in":[55,113],"process":[56,116],"temperature":[58],"parameters":[59],"which":[60],"strong":[63],"impact":[64],"on":[65,172,190],"chip":[66],"reliability.":[67],"addition,":[69],"make":[71],"simplifying":[73],"assumption":[74],"future":[77],"workloads":[78],"identical":[80],"currently":[83],"observed":[84],"one.":[85],"This":[86],"makes":[87],"them":[88],"sensitive":[89],"sudden":[91],"workload":[92,127],"outliers.":[95],"this":[97],"paper,":[98],"we":[99,151],"present":[100],"novel":[102],"workload-aware":[103],"dynamic":[104,132],"framework":[107,179],"accounts":[109],"for":[110],"local":[111],"both":[114],"temperature.":[118],"The":[119],"estimation,":[121],"along":[122],"with":[123,158],"predicted":[125],"remaining":[126],"is":[128],"fed":[129],"voltage/frequency":[133],"scaling":[134],"module":[135],"manage":[137],"optimize":[142],"processor":[143,175],"performance.":[144],"Using":[145],"fast":[147],"on-line":[148],"analytical/table-look-up":[149],"method":[150],"demonstrate":[152],"an":[153,173],"average":[154],"error":[155],"of":[156,163],"1%":[157],"up":[159],"5":[161],"orders":[162],"magnitude":[164],"speedup":[165],"compared":[166],"Monte":[168],"Carlo":[169],"simulation.":[170],"Experiments":[171],"Alpha-like":[174],"show":[176],"our":[177],"fully":[180],"utilizes":[181],"available":[183],"margin":[184],"achieves":[186],"28.7%":[187],"improvement":[189],"average.":[191]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}