{"id":"https://openalex.org/W4246422893","doi":"https://doi.org/10.1109/iccad.2015.7372655","title":"Reducing post-silicon coverage monitoring overhead with emulation and Bayesian feature selection","display_name":"Reducing post-silicon coverage monitoring overhead with emulation and Bayesian feature selection","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W4246422893","doi":"https://doi.org/10.1109/iccad.2015.7372655"},"language":"en","primary_location":{"id":"doi:10.1109/iccad.2015.7372655","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2015.7372655","pdf_url":null,"source":{"id":"https://openalex.org/S4363608324","display_name":"2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","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/A5079718284","display_name":"Ricardo Ochoa Gallardo","orcid":null},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Ricardo Ochoa Gallardo","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of British Columbia"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of British Columbia","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004153112","display_name":"Alan J. Huy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alan J. Huy","raw_affiliation_strings":["The University of British Columbia Faculty of Medicine, Vancouver, BC, CA"],"affiliations":[{"raw_affiliation_string":"The University of British Columbia Faculty of Medicine, Vancouver, BC, CA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062724257","display_name":"A. Ivanov","orcid":"https://orcid.org/0000-0002-0882-6750"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Andre Ivanov","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of British Columbia"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of British Columbia","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024703221","display_name":"Maryam S. Mirian","orcid":"https://orcid.org/0000-0001-5411-9902"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Maryam S. Mirian","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Tehran"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Tehran","institution_ids":["https://openalex.org/I23946033"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079718284"],"corresponding_institution_ids":["https://openalex.org/I141945490"],"apc_list":null,"apc_paid":null,"fwci":0.3771,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.46608315,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"816","last_page":"823"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9997000098228455,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T12423","display_name":"Software Reliability and Analysis Research","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/observability","display_name":"Observability","score":0.7482062578201294},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.716661274433136},{"id":"https://openalex.org/keywords/emulation","display_name":"Emulation","score":0.7119535207748413},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5353010296821594},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5176334977149963},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.50050950050354},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4685657322406769},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42779541015625},{"id":"https://openalex.org/keywords/coverage-probability","display_name":"Coverage probability","score":0.42772093415260315},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33741670846939087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17022183537483215},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15198686718940735},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15025392174720764},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.140926331281662}],"concepts":[{"id":"https://openalex.org/C36299963","wikidata":"https://www.wikidata.org/wiki/Q1369844","display_name":"Observability","level":2,"score":0.7482062578201294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.716661274433136},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.7119535207748413},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5353010296821594},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5176334977149963},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.50050950050354},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4685657322406769},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42779541015625},{"id":"https://openalex.org/C2776292839","wikidata":"https://www.wikidata.org/wiki/Q5179217","display_name":"Coverage probability","level":3,"score":0.42772093415260315},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33741670846939087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17022183537483215},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15198686718940735},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15025392174720764},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.140926331281662},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccad.2015.7372655","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2015.7372655","pdf_url":null,"source":{"id":"https://openalex.org/S4363608324","display_name":"2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1517993545","https://openalex.org/W1544635590","https://openalex.org/W1619226191","https://openalex.org/W1980282924","https://openalex.org/W1981523793","https://openalex.org/W1989578025","https://openalex.org/W2024436253","https://openalex.org/W2030959856","https://openalex.org/W2075816212","https://openalex.org/W2090692734","https://openalex.org/W2101700684","https://openalex.org/W2148633389","https://openalex.org/W2166862343","https://openalex.org/W2170285316","https://openalex.org/W2979006918","https://openalex.org/W3139542001","https://openalex.org/W3201444869","https://openalex.org/W4234474371","https://openalex.org/W4236354166","https://openalex.org/W4238083723","https://openalex.org/W4243872270","https://openalex.org/W4252327938","https://openalex.org/W6656661298","https://openalex.org/W6768650569","https://openalex.org/W6801407141"],"related_works":["https://openalex.org/W2046459260","https://openalex.org/W2765830098","https://openalex.org/W2967463586","https://openalex.org/W1971989957","https://openalex.org/W2517338020","https://openalex.org/W3157641275","https://openalex.org/W4312300846","https://openalex.org/W4206221578","https://openalex.org/W3029572990","https://openalex.org/W2615757685"],"abstract_inverted_index":{"With":[0],"increasing":[1],"design":[2,72],"complexity,":[3],"post-silicon":[4,66],"validation":[5,20],"has":[6,43],"become":[7],"a":[8,37,53,62,90,125,145],"critical":[9],"problem.":[10],"In":[11,142],"pre-silicon":[12],"validation,":[13],"coverage":[14,30,34,57,67,80,94,97,105,140,154,165],"is":[15,48,115],"the":[16,25,46,71,77,103,121,136,151],"primary":[17],"metric":[18],"of":[19,27,56,93,139,153],"effectiveness,":[21],"but":[22,40],"in":[23,73],"post-silicon,":[24],"lack":[26],"observability":[28],"makes":[29],"measurement":[31],"problematic.":[32],"On-chip":[33],"monitors":[35,155],"are":[36,107,167],"possible":[38],"solution,":[39],"prior":[41],"research":[42],"shown":[44],"that":[45,101,112,163],"overhead":[47],"prohibitive":[49],"for":[50,65],"anything":[51],"beyond":[52],"small":[54,91,113,137],"number":[55,152],"points.":[58,141],"This":[59],"paper":[60],"presents":[61],"novel":[63],"solution":[64],"monitoring:":[68],"fully":[69],"instrument":[70],"emulation":[74],"to":[75,88,134],"sample":[76],"relationships":[78],"between":[79],"points,":[81],"and":[82],"then":[83],"use":[84],"this":[85],"statistical":[86],"data":[87],"choose":[89,135],"set":[92,114,138],"points":[95,106,166],"whose":[96],"provides":[98],"high":[99],"probability":[100,162],"all":[102,164],"other":[104],"covered":[108],"as":[109],"well;":[110],"only":[111],"instrumented":[116],"on":[117,131],"silicon.":[118],"To":[119],"demonstrate":[120],"method,":[122],"we":[123],"propose":[124],"simple":[126],"feature":[127],"selection":[128],"algorithm":[129],"based":[130],"Bayesian":[132],"networks":[133],"experiments":[143],"emulating":[144],"non-trivial":[146],"SoC,":[147],"our":[148],"technique":[149],"reduces":[150],"by":[156],"92%,":[157],"yet":[158],"predicts":[159],"over":[160],"98%":[161],"covered.":[168]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
