{"id":"https://openalex.org/W3010987747","doi":"https://doi.org/10.1145/3372780.3375562","title":"Lookahead Placement Optimization with Cell Library-based Pin Accessibility Prediction via Active Learning","display_name":"Lookahead Placement Optimization with Cell Library-based Pin Accessibility Prediction via Active Learning","publication_year":2020,"publication_date":"2020-03-20","ids":{"openalex":"https://openalex.org/W3010987747","doi":"https://doi.org/10.1145/3372780.3375562","mag":"3010987747"},"language":"en","primary_location":{"id":"doi:10.1145/3372780.3375562","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372780.3375562","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Symposium on Physical Design","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/A5064936875","display_name":"Tao-Chun Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tao-Chun Yu","raw_affiliation_strings":["National Taiwan University of Science and Technology, Taipei, Taiwan Roc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology, Taipei, Taiwan Roc","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065439030","display_name":"Shao\u2010Yun Fang","orcid":"https://orcid.org/0000-0001-6675-2676"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shao-Yun Fang","raw_affiliation_strings":["National Taiwan University of Science and Technology, Taipei, Taiwan Roc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology, Taipei, Taiwan Roc","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063603943","display_name":"Hsien-Shih Chiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hsien-Shih Chiu","raw_affiliation_strings":["Synopsys Taiwan Co., Ltd., Taipei, Taiwan Roc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Synopsys Taiwan Co., Ltd., Taipei, Taiwan Roc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070386334","display_name":"Kaishun Hu","orcid":"https://orcid.org/0000-0003-2157-6239"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kai-Shun Hu","raw_affiliation_strings":["Synopsys Taiwan Co., Ltd., Taipei, Taiwan Roc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Synopsys Taiwan Co., Ltd., Taipei, Taiwan Roc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075450046","display_name":"Philip Hui-Yuh Tai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210088951","display_name":"Synopsys (United States)","ror":"https://ror.org/013by2m91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210088951"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip Hui-Yuh Tai","raw_affiliation_strings":["Synopsys, Inc., Mountain View, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Synopsys, Inc., Mountain View, CA, USA","institution_ids":["https://openalex.org/I4210088951"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067609420","display_name":"Cindy Shen","orcid":"https://orcid.org/0009-0008-6902-6600"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cindy Chin-Fang Shen","raw_affiliation_strings":["Synopsys Taiwan Co., Ltd., Taipei, Taiwan Roc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Synopsys Taiwan Co., Ltd., Taipei, Taiwan Roc","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034183596","display_name":"Henry Sheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210088951","display_name":"Synopsys (United States)","ror":"https://ror.org/013by2m91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210088951"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Henry Sheng","raw_affiliation_strings":["Synopsys, Inc., Mountain View, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Synopsys, Inc., Mountain View, CA, USA","institution_ids":["https://openalex.org/I4210088951"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8324,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.90491619,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"65","last_page":"72"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9998000264167786,"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":0.9998000264167786,"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/T11522","display_name":"VLSI and FPGA Design Techniques","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/T11338","display_name":"Advancements in Photolithography Techniques","score":0.9994999766349792,"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":0.7776474952697754},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.669803261756897},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6027020812034607},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5513076186180115},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5418922901153564},{"id":"https://openalex.org/keywords/standard-cell","display_name":"Standard cell","score":0.5404096841812134},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.5384315252304077},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5361812710762024},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.44791728258132935},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4279819428920746},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3523830771446228},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.09985676407814026},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.09807989001274109},{"id":"https://openalex.org/keywords/integrated-circuit","display_name":"Integrated circuit","score":0.09807845950126648}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7776474952697754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.669803261756897},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6027020812034607},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5513076186180115},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5418922901153564},{"id":"https://openalex.org/C78401558","wikidata":"https://www.wikidata.org/wiki/Q464496","display_name":"Standard cell","level":3,"score":0.5404096841812134},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.5384315252304077},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5361812710762024},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.44791728258132935},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4279819428920746},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3523830771446228},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.09985676407814026},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.09807989001274109},{"id":"https://openalex.org/C530198007","wikidata":"https://www.wikidata.org/wiki/Q80831","display_name":"Integrated circuit","level":2,"score":0.09807845950126648},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3372780.3375562","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372780.3375562","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Symposium on Physical Design","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2812098375","display_name":null,"funder_award_id":"108-2636-E-011-002","funder_id":"https://openalex.org/F4320327335","funder_display_name":"Minist\u00e9rio da Ci\u00eancia, Tecnologia, Inova\u00e7\u00f5es e Comunica\u00e7\u00f5es"}],"funders":[{"id":"https://openalex.org/F4320327335","display_name":"Minist\u00e9rio da Ci\u00eancia, Tecnologia, Inova\u00e7\u00f5es e Comunica\u00e7\u00f5es","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W66763315","https://openalex.org/W1562693942","https://openalex.org/W1675335411","https://openalex.org/W1966799294","https://openalex.org/W1972508834","https://openalex.org/W1995276688","https://openalex.org/W2006484294","https://openalex.org/W2033505180","https://openalex.org/W2040894443","https://openalex.org/W2063863981","https://openalex.org/W2090971357","https://openalex.org/W2118996030","https://openalex.org/W2135733005","https://openalex.org/W2139238311","https://openalex.org/W2140800546","https://openalex.org/W2142968870","https://openalex.org/W2144438170","https://openalex.org/W2155290553","https://openalex.org/W2296514843","https://openalex.org/W2343514605","https://openalex.org/W2406038381","https://openalex.org/W2554031552","https://openalex.org/W2589624049","https://openalex.org/W2604305190","https://openalex.org/W2604486584","https://openalex.org/W2624449764","https://openalex.org/W2625737522","https://openalex.org/W2626325543","https://openalex.org/W2735257517","https://openalex.org/W2808884553","https://openalex.org/W2899885603","https://openalex.org/W2945582997","https://openalex.org/W4233982390","https://openalex.org/W4285719527","https://openalex.org/W6602714489","https://openalex.org/W6675056011","https://openalex.org/W6677757056","https://openalex.org/W6682578415"],"related_works":["https://openalex.org/W3090875125","https://openalex.org/W2143608234","https://openalex.org/W88258363","https://openalex.org/W4200577934","https://openalex.org/W2119373721","https://openalex.org/W2134385741","https://openalex.org/W2604690070","https://openalex.org/W2085308054","https://openalex.org/W4380610161","https://openalex.org/W2111071331"],"abstract_inverted_index":{"With":[0],"the":[1,9,18,23,43,60,86,111,119,144,174,184,209,213],"development":[2],"of":[3,7,11,17,25,45,62,70,122,137,152,202,208,222],"advanced":[4],"process":[5],"nodes":[6],"semiconductor,":[8],"problem":[10,44],"pin":[12,125],"access":[13],"has":[14],"become":[15],"one":[16],"major":[19],"factors":[20],"to":[21,31,77,100,169,173,190],"impact":[22],"occurrences":[24],"design":[26,33],"rule":[27],"violations":[28],"(DRVs)":[29],"due":[30],"complex":[32],"rules":[34],"and":[35,94,205],"limited":[36],"routing":[37],"resource.":[38],"Many":[39],"state-of-the-art":[40],"works":[41],"address":[42],"DRV":[46],"prediction":[47,127],"by":[48,65,129,212],"adopting":[49],"supervised":[50,56],"machine":[51],"learning":[52,57,132],"approaches.":[53],"However,":[54],"those":[55,221],"approaches":[58],"extract":[59],"labels":[61],"training":[63,81,112],"data":[64,82,93],"generating":[66],"a":[67,162],"great":[68],"number":[69,201],"routed":[71],"designs":[72,103,171,194,210],"in":[73,110],"advance,":[74],"giving":[75],"rise":[76],"large":[78],"effort":[79],"on":[80],"preparation.":[83],"In":[84,114],"addition,":[85],"pre-trained":[87],"model":[88,148,164,186,215],"could":[89],"hardly":[90],"predict":[91,101,191],"unseen":[92],"thus":[95],"may":[96],"not":[97,108],"be":[98,167,188],"applied":[99,168,189],"other":[102],"containing":[104],"cells":[105],"that":[106,155,183],"are":[107,216],"used":[109],"data.":[113],"this":[115],"paper,":[116],"we":[117,160],"propose":[118,161],"first":[120],"work":[121],"cell":[123,139,177],"library-based":[124,163],"accessibility":[126],"(PAP)":[128],"using":[130],"active":[131],"techniques.":[133],"A":[134],"given":[135],"set":[136],"standard":[138,176],"libraries":[140],"is":[141],"served":[142],"as":[143],"only":[145],"input":[146],"for":[147],"training.":[149],"Unlike":[150],"most":[151],"existing":[153],"studies":[154],"aim":[156],"at":[157],"design-specific":[158,223],"training,":[159],"which":[165],"can":[166,187],"all":[170],"referencing":[172],"same":[175],"library":[178,198],"set.":[179],"Experimental":[180],"results":[181],"show":[182],"proposed":[185,214],"two":[192],"different":[193,196],"with":[195],"reference":[197],"sets.":[199],"The":[200],"remaining":[203],"DRVs":[204],"M2":[206],"shorts":[207],"optimized":[211],"also":[217],"much":[218],"fewer":[219],"than":[220],"models.":[224]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}