{"id":"https://openalex.org/W4387398469","doi":"https://doi.org/10.1145/3626321","title":"Yield Optimization for Analog Circuits over Multiple Corners via Bayesian Neural Networks: Enhancing Circuit Reliability under Environmental Variation","display_name":"Yield Optimization for Analog Circuits over Multiple Corners via Bayesian Neural Networks: Enhancing Circuit Reliability under Environmental Variation","publication_year":2023,"publication_date":"2023-10-06","ids":{"openalex":"https://openalex.org/W4387398469","doi":"https://doi.org/10.1145/3626321"},"language":"en","primary_location":{"id":"doi:10.1145/3626321","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3626321","pdf_url":null,"source":{"id":"https://openalex.org/S105046310","display_name":"ACM Transactions on Design Automation of Electronic Systems","issn_l":"1084-4309","issn":["1084-4309","1557-7309"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Design Automation of Electronic Systems","raw_type":"journal-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/A5011440543","display_name":"Nanlin Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nanlin Guo","raw_affiliation_strings":["Fudan University"],"raw_orcid":"https://orcid.org/0000-0002-3681-9144","affiliations":[{"raw_affiliation_string":"Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065278925","display_name":"Fulin Peng","orcid":"https://orcid.org/0000-0003-2187-8296"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fulin Peng","raw_affiliation_strings":["Fudan University"],"raw_orcid":"https://orcid.org/0000-0003-2187-8296","affiliations":[{"raw_affiliation_string":"Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080925768","display_name":"Jiahe Shi","orcid":"https://orcid.org/0000-0003-3733-9895"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahe Shi","raw_affiliation_strings":["Fudan University"],"raw_orcid":"https://orcid.org/0000-0003-3733-9895","affiliations":[{"raw_affiliation_string":"Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045464812","display_name":"Fan Yang","orcid":"https://orcid.org/0000-0003-2164-8175"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Yang","raw_affiliation_strings":["Fudan University"],"raw_orcid":"https://orcid.org/0000-0003-2164-8175","affiliations":[{"raw_affiliation_string":"Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062927280","display_name":"Jun Tao","orcid":"https://orcid.org/0000-0001-8742-687X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Tao","raw_affiliation_strings":["Fudan University"],"raw_orcid":"https://orcid.org/0000-0001-8742-687X","affiliations":[{"raw_affiliation_string":"Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064213921","display_name":"Xuan Zeng","orcid":"https://orcid.org/0000-0002-8097-4053"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Zeng","raw_affiliation_strings":["Fudan University"],"raw_orcid":"https://orcid.org/0000-0002-8097-4053","affiliations":[{"raw_affiliation_string":"Fudan University","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4909,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.64225641,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"29","issue":"1","first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9995999932289124,"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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9995999932289124,"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":0.9991000294685364,"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9990000128746033,"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":0.7198094129562378},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6195269823074341},{"id":"https://openalex.org/keywords/process-variation","display_name":"Process variation","score":0.5440565347671509},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5346279144287109},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.5149165391921997},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.5139512419700623},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5088332295417786},{"id":"https://openalex.org/keywords/electronic-circuit","display_name":"Electronic circuit","score":0.4757761061191559},{"id":"https://openalex.org/keywords/integrated-circuit","display_name":"Integrated circuit","score":0.44395047426223755},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.384274959564209},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.37908047437667847},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26956459879875183},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.09719294309616089}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7198094129562378},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6195269823074341},{"id":"https://openalex.org/C93389723","wikidata":"https://www.wikidata.org/wiki/Q7247313","display_name":"Process variation","level":3,"score":0.5440565347671509},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5346279144287109},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.5149165391921997},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.5139512419700623},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5088332295417786},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.4757761061191559},{"id":"https://openalex.org/C530198007","wikidata":"https://www.wikidata.org/wiki/Q80831","display_name":"Integrated circuit","level":2,"score":0.44395047426223755},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.384274959564209},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.37908047437667847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26956459879875183},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.09719294309616089},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"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},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3626321","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3626321","pdf_url":null,"source":{"id":"https://openalex.org/S105046310","display_name":"ACM Transactions on Design Automation of Electronic Systems","issn_l":"1084-4309","issn":["1084-4309","1557-7309"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Design Automation of Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1095761577","display_name":null,"funder_award_id":"2020YFA0711900 and 2020YFA0711901","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G1452377411","display_name":null,"funder_award_id":"2020YFA0711900","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5071938314","display_name":null,"funder_award_id":"62141407","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6197183902","display_name":null,"funder_award_id":"61929102","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6592732141","display_name":null,"funder_award_id":"2020YFA0711901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7330262771","display_name":null,"funder_award_id":"62141408","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8039800872","display_name":null,"funder_award_id":"62141408 62141407 and 61929102","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W111129777","https://openalex.org/W1510052597","https://openalex.org/W2015616421","https://openalex.org/W2021819681","https://openalex.org/W2067964949","https://openalex.org/W2093625674","https://openalex.org/W2113322447","https://openalex.org/W2117648153","https://openalex.org/W2126639080","https://openalex.org/W2134560383","https://openalex.org/W2158748535","https://openalex.org/W2535919346","https://openalex.org/W2572378421","https://openalex.org/W2603178913","https://openalex.org/W2768460200","https://openalex.org/W2799462322","https://openalex.org/W2913252637","https://openalex.org/W2945804086","https://openalex.org/W2962994101","https://openalex.org/W2972619754","https://openalex.org/W3000277453","https://openalex.org/W3014426053","https://openalex.org/W3098780461","https://openalex.org/W3186609514","https://openalex.org/W4210918606","https://openalex.org/W4212863985","https://openalex.org/W4242472899","https://openalex.org/W4299617642","https://openalex.org/W4303983220"],"related_works":["https://openalex.org/W3106461837","https://openalex.org/W3168182983","https://openalex.org/W4321472004","https://openalex.org/W4283700523","https://openalex.org/W4387079005","https://openalex.org/W2968265130","https://openalex.org/W4221166418","https://openalex.org/W3215142653","https://openalex.org/W1487051936","https://openalex.org/W194748710"],"abstract_inverted_index":{"The":[0],"reliability":[1],"of":[2,33,48,69,91,120,146,162],"circuits":[3,71],"is":[4,41,63,125],"significantly":[5],"affected":[6],"by":[7,105],"process":[8,22],"variations":[9,23,35],"in":[10,44,72,93,122,128],"manufacturing":[11],"and":[12,38,58,89,118,139],"environmental":[13,34,74],"variation":[14],"during":[15],"operation.":[16],"Current":[17],"yield":[18,68,100,147,193],"optimization":[19,101,111],"algorithms":[20],"take":[21],"into":[24,108],"consideration":[25],"to":[26,65,84,142,160,166,170],"improve":[27,143],"circuit":[28],"reliability.":[29],"However,":[30],"the":[31,49,67,87,98,114,129,144,154,172,179],"influence":[32],"(e.g.,":[36],"voltage":[37],"temperature":[39],"variations)":[40],"often":[42],"ignored":[43],"current":[45],"methods":[46,169],"because":[47],"high":[50],"computational":[51],"cost.":[52],"In":[53,176],"this":[54],"article,":[55],"a":[56,79,109],"novel":[57],"efficient":[59],"approach":[60],"named":[61],"BNN-BYO":[62],"proposed":[64,155,184],"optimize":[66],"analog":[70],"multiple":[73,94],"corners.":[75],"First,":[76],"we":[77],"use":[78],"Bayesian":[80,110],"Neural":[81],"Network":[82],"(BNN)":[83],"simultaneously":[85],"model":[86],"yields":[88,117,138],"performances":[90,119],"interest":[92,121],"corners":[95,124],"efficiently.":[96],"Next,":[97],"multi-corner":[99],"can":[102,157,186],"be":[103],"performed":[104],"embedding":[106],"BNN":[107,130],"framework.":[112],"Since":[113],"correlation":[115],"among":[116],"different":[123],"implicitly":[126],"encoded":[127],"model,":[131],"it":[132],"provides":[133],"great":[134],"modeling":[135],"capabilities":[136],"for":[137,178],"their":[140],"uncertainties":[141],"efficiency":[145],"optimization.":[148],"Our":[149],"experimental":[150],"results":[151],"demonstrate":[152],"that":[153],"method":[156,185],"save":[158],"up":[159],"45.3%":[161],"simulation":[163,181],"cost":[164],"compared":[165],"other":[167],"baseline":[168],"achieve":[171],"same":[173,180],"target":[174],"yield.":[175],"addition,":[177],"cost,":[182],"our":[183],"find":[187],"better":[188],"design":[189],"points":[190],"with":[191],"3.2%":[192],"improvement.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}