{"id":"https://openalex.org/W4379115668","doi":"https://doi.org/10.1109/vts56346.2023.10140070","title":"Special Session: Using Graph Neural Networks for Tier-Level Fault Localization in Monolithic 3D ICs <sup>*</sup>","display_name":"Special Session: Using Graph Neural Networks for Tier-Level Fault Localization in Monolithic 3D ICs <sup>*</sup>","publication_year":2023,"publication_date":"2023-04-24","ids":{"openalex":"https://openalex.org/W4379115668","doi":"https://doi.org/10.1109/vts56346.2023.10140070"},"language":"en","primary_location":{"id":"doi:10.1109/vts56346.2023.10140070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts56346.2023.10140070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 41st VLSI Test Symposium (VTS)","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/A5026176966","display_name":"Shao-Chun Hung","orcid":"https://orcid.org/0000-0003-1125-6709"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shao-Chun Hung","raw_affiliation_strings":["Duke University,Department of Electrical and Computer Engineering","Department of Electrical and Computer Engineering, Duke University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090354528","display_name":"Arjun Chaudhuri","orcid":"https://orcid.org/0000-0001-9353-6397"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arjun Chaudhuri","raw_affiliation_strings":["Duke University,Department of Electrical and Computer Engineering","Department of Electrical and Computer Engineering, Duke University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052051759","display_name":"Sanmitra Banerjee","orcid":"https://orcid.org/0000-0002-1136-9220"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanmitra Banerjee","raw_affiliation_strings":["NVIDIA Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA Corporation","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033880864","display_name":"Krishnendu Chakrabarty","orcid":"https://orcid.org/0000-0003-4475-6435"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Krishnendu Chakrabarty","raw_affiliation_strings":["Arizona State University,School of Electrical, Computer and Energy Engineering","School of Electrical, Computer and Energy Engineering, Arizona State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University,School of Electrical, Computer and Energy Engineering","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"School of Electrical, Computer and Energy Engineering, Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04572455,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11527","display_name":"3D IC and TSV technologies","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/T11527","display_name":"3D IC and TSV technologies","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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9980999827384949,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9957000017166138,"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/computer-science","display_name":"Computer science","score":0.6898522973060608},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4751429557800293},{"id":"https://openalex.org/keywords/integrated-circuit","display_name":"Integrated circuit","score":0.4454687535762787},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43358325958251953},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42377984523773193},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.42008793354034424},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.41870248317718506},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3997635841369629},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.39208269119262695},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3766426146030426},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3594967722892761},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.33401960134506226},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21420446038246155},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20040297508239746},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.10758504271507263}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6898522973060608},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4751429557800293},{"id":"https://openalex.org/C530198007","wikidata":"https://www.wikidata.org/wiki/Q80831","display_name":"Integrated circuit","level":2,"score":0.4454687535762787},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43358325958251953},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42377984523773193},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.42008793354034424},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.41870248317718506},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3997635841369629},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.39208269119262695},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3766426146030426},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3594967722892761},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.33401960134506226},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21420446038246155},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20040297508239746},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.10758504271507263},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vts56346.2023.10140070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts56346.2023.10140070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 41st VLSI Test Symposium (VTS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1983868989","https://openalex.org/W2002006950","https://openalex.org/W2050766394","https://openalex.org/W2146990954","https://openalex.org/W2163262984","https://openalex.org/W2169528473","https://openalex.org/W2735555835","https://openalex.org/W2787438330","https://openalex.org/W2791477613","https://openalex.org/W3092072718","https://openalex.org/W3152893301","https://openalex.org/W4280589658","https://openalex.org/W6837987081"],"related_works":["https://openalex.org/W2534928293","https://openalex.org/W2150099345","https://openalex.org/W3004580327","https://openalex.org/W1490077415","https://openalex.org/W2160318243","https://openalex.org/W4293463510","https://openalex.org/W2182874356","https://openalex.org/W3034806817","https://openalex.org/W2375757266","https://openalex.org/W4389045579"],"abstract_inverted_index":{"Monolithic":[0],"3D":[1],"(M3D)":[2],"integration":[3],"leverages":[4],"fine-grained":[5],"monolithic":[6],"inter-tier":[7],"vias":[8],"(MIVs)":[9],"to":[10,20,32,50,80,93,112],"achieve":[11],"significant":[12],"improvements":[13],"in":[14],"power,":[15],"performance,":[16],"and":[17,38,62,84,96],"area":[18],"compared":[19],"conventional":[21],"2D":[22],"integrated":[23],"circuits":[24],"(ICs).":[25],"However,":[26],"immature":[27],"M3D":[28,127],"fabrication":[29],"flows":[30],"lead":[31],"the":[33,55,94,98,106,130,133],"degradation":[34],"of":[35,100,105,132],"device":[36,82],"performance":[37,122],"unreliable":[39],"interconnects":[40],"between":[41],"tiers.":[42],"To":[43],"improve":[44],"yield":[45],"learning,":[46],"it":[47,110],"is":[48],"essential":[49],"perform":[51,113],"fault":[52],"localization":[53],"at":[54],"tier":[56,83],"level,":[57],"which":[58],"enables":[59],"targeted":[60],"diagnosis":[61,74,101,114],"process":[63],"optimization":[64],"efforts.":[65],"This":[66],"paper":[67],"presents":[68],"a":[69,81],"graph":[70],"neural":[71],"network-based":[72],"(GNN-based)":[73],"framework":[75],"that":[76],"efficiently":[77],"localizes":[78],"faults":[79],"susceptible":[85],"MIVs.":[86],"The":[87,103],"proposed":[88,134],"solution":[89],"offers":[90],"rapid":[91],"feedback":[92],"foundry":[95],"improves":[97],"quality":[99],"reports.":[102],"transferability":[104],"GNN":[107],"models":[108],"makes":[109],"possible":[111],"on":[115],"designs":[116],"with":[117],"various":[118],"design":[119],"configurations":[120],"without":[121],"degradation.":[123],"Results":[124],"for":[125],"four":[126],"benchmarks":[128],"highlight":[129],"effectiveness":[131],"framework.":[135]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
