{"id":"https://openalex.org/W3128227371","doi":"https://doi.org/10.1145/3394885.3431547","title":"Fast and Efficient Constraint Evaluation of Analog Layout Using Machine Learning Models","display_name":"Fast and Efficient Constraint Evaluation of Analog Layout Using Machine Learning Models","publication_year":2021,"publication_date":"2021-01-18","ids":{"openalex":"https://openalex.org/W3128227371","doi":"https://doi.org/10.1145/3394885.3431547","mag":"3128227371"},"language":"en","primary_location":{"id":"doi:10.1145/3394885.3431547","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3394885.3431547","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3394885.3431547","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th Asia and South Pacific Design Automation Conference","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3394885.3431547","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006995274","display_name":"Tonmoy Dhar","orcid":"https://orcid.org/0000-0003-0980-9749"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tonmoy Dhar","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004779677","display_name":"Jitesh Poojary","orcid":"https://orcid.org/0000-0001-7548-9064"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jitesh Poojary","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101587350","display_name":"Yaguang Li","orcid":"https://orcid.org/0000-0001-9425-034X"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yaguang Li","raw_affiliation_strings":["Texas A&amp;M University, College Station, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&amp;M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063963932","display_name":"Kishor Kunal","orcid":"https://orcid.org/0000-0003-3510-9850"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kishor Kunal","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063857392","display_name":"Meghna Madhusudan","orcid":"https://orcid.org/0000-0001-5101-2421"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Meghna Madhusudan","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100732194","display_name":"Arvind Sharma","orcid":"https://orcid.org/0000-0002-9250-9642"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arvind K. Sharma","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004590102","display_name":"Susmita Dey Manasi","orcid":"https://orcid.org/0000-0001-9358-6255"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Susmita Dey Manasi","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103246390","display_name":"Jiang Hu","orcid":"https://orcid.org/0000-0003-1157-7799"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiang Hu","raw_affiliation_strings":["Texas A&amp;M University, College Station, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&amp;M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059037025","display_name":"Ramesh Harjani","orcid":"https://orcid.org/0000-0001-7691-566X"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramesh Harjani","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068714995","display_name":"Sachin S. Sapatnekar","orcid":"https://orcid.org/0000-0002-5353-2364"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sachin S. Sapatnekar","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]}],"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":true,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"158","last_page":"163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":1.0,"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":1.0,"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":0.9998000264167786,"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/T11338","display_name":"Advancements in Photolithography Techniques","score":0.9997000098228455,"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":0.689335823059082},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.607472836971283},{"id":"https://openalex.org/keywords/analogue-electronics","display_name":"Analogue electronics","score":0.5587831735610962},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5502005219459534},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.48787927627563477},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4688390791416168},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.452706515789032},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4512171745300293},{"id":"https://openalex.org/keywords/latin-hypercube-sampling","display_name":"Latin hypercube sampling","score":0.42251116037368774},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41297584772109985},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.41236376762390137},{"id":"https://openalex.org/keywords/integrated-circuit-layout","display_name":"Integrated circuit layout","score":0.4118489623069763},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3979436755180359},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39261290431022644},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3441512882709503},{"id":"https://openalex.org/keywords/electronic-circuit","display_name":"Electronic circuit","score":0.28708356618881226},{"id":"https://openalex.org/keywords/integrated-circuit","display_name":"Integrated circuit","score":0.22019797563552856},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17802584171295166},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13355034589767456},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.12072572112083435}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.689335823059082},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.607472836971283},{"id":"https://openalex.org/C29074008","wikidata":"https://www.wikidata.org/wiki/Q174925","display_name":"Analogue electronics","level":3,"score":0.5587831735610962},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5502005219459534},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.48787927627563477},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4688390791416168},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.452706515789032},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4512171745300293},{"id":"https://openalex.org/C20820323","wikidata":"https://www.wikidata.org/wiki/Q6496514","display_name":"Latin hypercube sampling","level":3,"score":0.42251116037368774},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41297584772109985},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.41236376762390137},{"id":"https://openalex.org/C2765594","wikidata":"https://www.wikidata.org/wiki/Q2624187","display_name":"Integrated circuit layout","level":3,"score":0.4118489623069763},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3979436755180359},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39261290431022644},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3441512882709503},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.28708356618881226},{"id":"https://openalex.org/C530198007","wikidata":"https://www.wikidata.org/wiki/Q80831","display_name":"Integrated circuit","level":2,"score":0.22019797563552856},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17802584171295166},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13355034589767456},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.12072572112083435},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394885.3431547","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3394885.3431547","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3394885.3431547","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th Asia and South Pacific Design Automation Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3394885.3431547","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3394885.3431547","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3394885.3431547","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th Asia and South Pacific Design Automation Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2277698948","display_name":null,"funder_award_id":"N660011824048","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G960639874","display_name":null,"funder_award_id":"CCF-1714805","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3128227371.pdf","grobid_xml":"https://content.openalex.org/works/W3128227371.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W1481744301","https://openalex.org/W1560724230","https://openalex.org/W1680603978","https://openalex.org/W2020787948","https://openalex.org/W2100776169","https://openalex.org/W2108229403","https://openalex.org/W2156110154","https://openalex.org/W2945221971","https://openalex.org/W2968056168","https://openalex.org/W2997579412","https://openalex.org/W3036164688","https://openalex.org/W3092098889","https://openalex.org/W3130356386","https://openalex.org/W3145506661","https://openalex.org/W4213283575"],"related_works":["https://openalex.org/W2364245233","https://openalex.org/W2154735538","https://openalex.org/W2218563287","https://openalex.org/W2352984759","https://openalex.org/W2107461746","https://openalex.org/W2146537238","https://openalex.org/W2076146297","https://openalex.org/W4237705761","https://openalex.org/W2168223448","https://openalex.org/W2169238810"],"abstract_inverted_index":{"Placement":[0],"algorithms":[1],"for":[2,88,126],"analog":[3,128],"circuits":[4],"explore":[5],"numerous":[6],"layout":[7,37,46],"configurations":[8],"in":[9,117],"their":[10],"iterative":[11],"search.":[12],"To":[13],"steer":[14],"these":[15],"engines":[16],"towards":[17],"layouts":[18,125],"that":[19],"meet":[20],"the":[21,25,36,50,63,68,89,93],"electrical":[22],"constraints":[23,94],"on":[24,45],"design,":[26],"this":[27],"work":[28],"develops":[29],"a":[30,54,74,82,100,118],"fast":[31],"feasibility":[32],"predictor":[33],"to":[34,61,97,112,123],"guide":[35],"engine.":[38],"The":[39,106],"flow":[40],"first":[41],"discerns":[42],"rough":[43],"bounds":[44],"parasitics":[47],"and":[48,67,120],"prunes":[49],"feature":[51],"space.":[52],"Next,":[53],"Latin":[55],"hypercube":[56],"sampling":[57],"technique":[58],"is":[59,86,104,121],"used":[60,87,122],"sample":[62,84],"reduced":[64],"search":[65],"space,":[66],"labeled":[69],"samples":[70],"are":[71,95],"classified":[72],"by":[73],"linear":[75],"support":[76],"vector":[77],"machine":[78,108],"(SVM).":[79],"If":[80],"necessary,":[81],"denser":[83],"set":[85],"SVM,":[90],"or":[91],"if":[92],"found":[96],"be":[98],"nonlinear,":[99],"multilayer":[101],"perceptron":[102],"(MLP)":[103],"employed.":[105],"resulting":[107],"learning":[109],"model":[110],"demonstrated":[111],"rapidly":[113],"evaluate":[114],"candidate":[115],"placements":[116],"placer,":[119],"build":[124],"several":[127],"blocks.":[129]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
