{"id":"https://openalex.org/W3090022958","doi":"https://doi.org/10.1109/iscas45731.2020.9180472","title":"A Reliability-Oriented Machine Learning Strategy for Heterogeneous Multicore Application Mapping","display_name":"A Reliability-Oriented Machine Learning Strategy for Heterogeneous Multicore Application Mapping","publication_year":2020,"publication_date":"2020-09-29","ids":{"openalex":"https://openalex.org/W3090022958","doi":"https://doi.org/10.1109/iscas45731.2020.9180472","mag":"3090022958"},"language":"en","primary_location":{"id":"doi:10.1109/iscas45731.2020.9180472","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas45731.2020.9180472","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5086087895","display_name":"Rafael Billig Tonetto","orcid":null},"institutions":[{"id":"https://openalex.org/I130442723","display_name":"Universidade Federal do Rio Grande do Sul","ror":"https://ror.org/041yk2d64","country_code":"BR","type":"education","lineage":["https://openalex.org/I130442723"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Rafael B. Tonetto","raw_affiliation_strings":["Federal University of Rio Grande do Sul (UFRGS)","Federal University of Rio Grande do Sul, Porto Alegre, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Rio Grande do Sul (UFRGS)","institution_ids":["https://openalex.org/I130442723"]},{"raw_affiliation_string":"Federal University of Rio Grande do Sul, Porto Alegre, Brazil","institution_ids":["https://openalex.org/I130442723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019705944","display_name":"Hiago Mayk G. de A. Rocha","orcid":"https://orcid.org/0000-0002-0827-0131"},"institutions":[{"id":"https://openalex.org/I130442723","display_name":"Universidade Federal do Rio Grande do Sul","ror":"https://ror.org/041yk2d64","country_code":"BR","type":"education","lineage":["https://openalex.org/I130442723"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Hiago M. G. de A. Rocha","raw_affiliation_strings":["Federal University of Rio Grande do Sul (UFRGS)","Federal University of Rio Grande do Sul, Porto Alegre, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Rio Grande do Sul (UFRGS)","institution_ids":["https://openalex.org/I130442723"]},{"raw_affiliation_string":"Federal University of Rio Grande do Sul, Porto Alegre, Brazil","institution_ids":["https://openalex.org/I130442723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057414253","display_name":"Bruno Zatt","orcid":"https://orcid.org/0000-0002-8045-957X"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Bruno Zatt","raw_affiliation_strings":["Federal University of Pelotas (UFPel)","Federal University of Pelotas, Pelotas, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Pelotas (UFPel)","institution_ids":["https://openalex.org/I169248161"]},{"raw_affiliation_string":"Federal University of Pelotas, Pelotas, Brazil","institution_ids":["https://openalex.org/I169248161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078952423","display_name":"Antonio Carlos Schneider Beck","orcid":"https://orcid.org/0000-0002-4492-1747"},"institutions":[{"id":"https://openalex.org/I130442723","display_name":"Universidade Federal do Rio Grande do Sul","ror":"https://ror.org/041yk2d64","country_code":"BR","type":"education","lineage":["https://openalex.org/I130442723"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Antonio Carlos S. Beck","raw_affiliation_strings":["Federal University of Rio Grande do Sul (UFRGS)","Federal University of Rio Grande do Sul, Porto Alegre, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Rio Grande do Sul (UFRGS)","institution_ids":["https://openalex.org/I130442723"]},{"raw_affiliation_string":"Federal University of Rio Grande do Sul, Porto Alegre, Brazil","institution_ids":["https://openalex.org/I130442723"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064852217","display_name":"Gabriel L. Nazar","orcid":"https://orcid.org/0000-0001-7202-7139"},"institutions":[{"id":"https://openalex.org/I130442723","display_name":"Universidade Federal do Rio Grande do Sul","ror":"https://ror.org/041yk2d64","country_code":"BR","type":"education","lineage":["https://openalex.org/I130442723"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Gabriel L. Nazar","raw_affiliation_strings":["Federal University of Rio Grande do Sul (UFRGS)","Federal University of Rio Grande do Sul, Porto Alegre, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Rio Grande do Sul (UFRGS)","institution_ids":["https://openalex.org/I130442723"]},{"raw_affiliation_string":"Federal University of Rio Grande do Sul, Porto Alegre, Brazil","institution_ids":["https://openalex.org/I130442723"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11005","display_name":"Radiation Effects in Electronics","score":0.9998999834060669,"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":0.9998999834060669,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9922999739646912,"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/T10933","display_name":"Real-Time Systems Scheduling","score":0.9916999936103821,"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/leverage","display_name":"Leverage (statistics)","score":0.7894794940948486},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.772720992565155},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.7138404846191406},{"id":"https://openalex.org/keywords/multi-core-processor","display_name":"Multi-core processor","score":0.7099671363830566},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5898557305335999},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.5581835508346558},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5437394976615906},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5116177201271057},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4964497685432434},{"id":"https://openalex.org/keywords/many-core","display_name":"Many core","score":0.4106053411960602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2649489641189575},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10360461473464966}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7894794940948486},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.772720992565155},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.7138404846191406},{"id":"https://openalex.org/C78766204","wikidata":"https://www.wikidata.org/wiki/Q555032","display_name":"Multi-core processor","level":2,"score":0.7099671363830566},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5898557305335999},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.5581835508346558},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5437394976615906},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5116177201271057},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4964497685432434},{"id":"https://openalex.org/C3020431745","wikidata":"https://www.wikidata.org/wiki/Q25325220","display_name":"Many core","level":2,"score":0.4106053411960602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2649489641189575},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10360461473464966},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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:10.1109/iscas45731.2020.9180472","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas45731.2020.9180472","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1976431848","https://openalex.org/W2054095206","https://openalex.org/W2090445739","https://openalex.org/W2098495359","https://openalex.org/W2134320686","https://openalex.org/W2144512449","https://openalex.org/W2160590289","https://openalex.org/W2588464298","https://openalex.org/W2613221718","https://openalex.org/W2798951245","https://openalex.org/W3149134903","https://openalex.org/W4210781224","https://openalex.org/W4230735214","https://openalex.org/W4245945453","https://openalex.org/W4249144718","https://openalex.org/W6680487673","https://openalex.org/W7055119176"],"related_works":["https://openalex.org/W4255057712","https://openalex.org/W4251458280","https://openalex.org/W2512412909","https://openalex.org/W1547865754","https://openalex.org/W2126398188","https://openalex.org/W2116570023","https://openalex.org/W4210605172","https://openalex.org/W2127157145","https://openalex.org/W4245707462","https://openalex.org/W4248999141"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,68,84],"methodology":[3],"to":[4,16,77,83,101],"transparently":[5],"estimate":[6],"near-optimal":[7],"application":[8],"mappings":[9,50],"aiming":[10],"at":[11,41],"increasing":[12],"the":[13,35,78],"Mean":[14],"Workload":[15],"Failure":[17],"(MWTF)":[18],"in":[19,70,97],"heterogeneous":[20,92],"multicore":[21],"processors.":[22],"For":[23],"that,":[24],"we":[25],"leverage":[26],"an":[27],"Artificial":[28],"Neural":[29],"Network":[30],"(ANN)":[31],"capable":[32],"of":[33,38,72,88,99],"estimating":[34],"vulnerability":[36],"factor":[37],"RISC-V":[39],"cores":[40],"runtime,":[42],"which":[43],"allows":[44],"for":[45],"efficient":[46],"and":[47,54],"dynamic":[48],"application-to-core":[49],"targeting":[51],"better":[52],"MWTF":[53,71,98],"MWTF/energy":[55],"tradeoffs.":[56],"Results":[57],"show":[58],"that":[59],"our":[60],"ANN-based":[61],"mapping":[62],"yields":[63],"very":[64],"close-to-optimal":[65],"solutions,":[66],"with":[67],"difference":[69],"only":[73,89],"3%":[74],"when":[75],"compared":[76,82],"optimal":[79],"mapping.":[80],"When":[81],"homogeneous":[85],"architecture":[86],"composed":[87],"big":[90],"cores,":[91],"architectures":[93],"may":[94],"provide":[95],"improvement":[96],"up":[100],"20.5%":[102],"while":[103],"impacting":[104],"12.2%":[105],"on":[106],"performance.":[107]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
