{"id":"https://openalex.org/W3013899498","doi":"https://doi.org/10.1109/asp-dac47756.2020.9045201","title":"FIST: A Feature-Importance Sampling and Tree-Based Method for Automatic Design Flow Parameter Tuning","display_name":"FIST: A Feature-Importance Sampling and Tree-Based Method for Automatic Design Flow Parameter Tuning","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3013899498","doi":"https://doi.org/10.1109/asp-dac47756.2020.9045201","mag":"3013899498"},"language":"en","primary_location":{"id":"doi:10.1109/asp-dac47756.2020.9045201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac47756.2020.9045201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2011.13493","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075696558","display_name":"Zhiyao Xie","orcid":"https://orcid.org/0000-0002-4442-592X"},"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":"Zhiyao Xie","raw_affiliation_strings":["Duke University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004534427","display_name":"Guan-Qi Fang","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":"Guan-Qi Fang","raw_affiliation_strings":["National Taiwan University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108833299","display_name":"Yu-Hung Huang","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":"Yu-Hung Huang","raw_affiliation_strings":["National Taiwan University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029928585","display_name":"Haoxing Ren","orcid":"https://orcid.org/0000-0003-1028-3860"},"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":"Haoxing Ren","raw_affiliation_strings":["Nvidia Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nvidia Corporation","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100612108","display_name":"Yanqing Zhang","orcid":"https://orcid.org/0009-0001-0812-3924"},"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":"Yanqing Zhang","raw_affiliation_strings":["Nvidia Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nvidia Corporation","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010156116","display_name":"Brucek Khailany","orcid":"https://orcid.org/0000-0002-7584-3489"},"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":"Brucek Khailany","raw_affiliation_strings":["Nvidia Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nvidia Corporation","institution_ids":["https://openalex.org/I4210127875"]}]},{"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"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology","institution_ids":["https://openalex.org/I154864474"]}]},{"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/I2801613365","display_name":"Mitchell Institute","ror":"https://ror.org/03ds72003","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2801613365"]},{"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&M University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&M University","institution_ids":["https://openalex.org/I2801613365","https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058073627","display_name":"Yiran Chen","orcid":"https://orcid.org/0000-0002-1486-8412"},"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":"Yiran Chen","raw_affiliation_strings":["Duke University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103896848","display_name":"Erick Carvajal Barboza","orcid":null},"institutions":[{"id":"https://openalex.org/I2801613365","display_name":"Mitchell Institute","ror":"https://ror.org/03ds72003","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2801613365"]},{"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":"Erick Carvajal Barboza","raw_affiliation_strings":["Texas A&M University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&M University","institution_ids":["https://openalex.org/I2801613365","https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"19","last_page":"25"},"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9983000159263611,"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":0.9970999956130981,"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":0.8080694675445557},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6899220943450928},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5831922292709351},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5583178400993347},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5118128657341003},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.47001174092292786},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4664442241191864},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45559147000312805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44561058282852173},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11472216248512268}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8080694675445557},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6899220943450928},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5831922292709351},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5583178400993347},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5118128657341003},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.47001174092292786},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4664442241191864},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45559147000312805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44561058282852173},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11472216248512268},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/asp-dac47756.2020.9045201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac47756.2020.9045201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2011.13493","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.13493","pdf_url":"https://arxiv.org/pdf/2011.13493","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-117893","is_oa":false,"landing_page_url":"http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=&rft.volume=&rft.issue=&rft.date=2020&rft.spage=19&rft.aulast=Xie&rft.aufirst=&rft.atitle=FIST%3A+A+Feature-Importance+Sampling+and+Tree-Based+Method+for+Automatic+Design+Flow+Parameter+Tuning&rft.title=Proceedings+of+the+Asia+and+South+Pacific+Design+Automation+Conference%2C+ASP-DAC","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2011.13493","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.13493","pdf_url":"https://arxiv.org/pdf/2011.13493","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1678356000","https://openalex.org/W1970392525","https://openalex.org/W2013135502","https://openalex.org/W2039856364","https://openalex.org/W2076592191","https://openalex.org/W2097571405","https://openalex.org/W2109255166","https://openalex.org/W2138209363","https://openalex.org/W2143785942","https://openalex.org/W2249579962","https://openalex.org/W2284148283","https://openalex.org/W2295598076","https://openalex.org/W2338895534","https://openalex.org/W2345438070","https://openalex.org/W2345855315","https://openalex.org/W2485968118","https://openalex.org/W2911964244","https://openalex.org/W2944892277","https://openalex.org/W2964391226","https://openalex.org/W3102476541","https://openalex.org/W3144874526","https://openalex.org/W4246385064","https://openalex.org/W6675603290","https://openalex.org/W6680485443","https://openalex.org/W6681338486"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W3009056573","https://openalex.org/W4297676672","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W4221142204"],"abstract_inverted_index":{"Design":[0],"flow":[1,23],"parameters":[2],"are":[3],"of":[4,63,66,143,163],"utmost":[5],"importance":[6],"to":[7,17,53,110,135,175],"chip":[8],"design":[9,57,126],"quality":[10,58,127],"and":[11,76,103,172],"require":[12],"a":[13,44,60,99,105,144],"painfully":[14],"long":[15],"time":[16],"evaluate":[18],"their":[19],"effects.":[20],"In":[21,39],"reality,":[22],"parameter":[24,48,165],"tuning":[25,49,82],"is":[26,140,151],"usually":[27],"performed":[28],"manually":[29],"based":[30],"on":[31,115,154],"designers'":[32],"experience":[33],"in":[34,69,87,125,131],"an":[35],"ad":[36],"hoc":[37],"manner.":[38],"this":[40,88],"work,":[41],"we":[42,73,97],"introduce":[43],"machine":[45,70],"learning-based":[46],"automatic":[47],"methodology":[50],"that":[51,119],"aims":[52],"find":[54],"the":[55,141,176],"best":[56,177],"with":[59],"limited":[61],"number":[62],"trials.":[64],"Instead":[65],"merely":[67],"plugging":[68],"learning":[71],"engines,":[72],"develop":[74],"clustering":[75],"approximate":[77],"sampling":[78,132,159],"techniques":[79],"for":[80],"improving":[81],"efficiency.":[83],"The":[84],"feature":[85],"extraction":[86],"method":[89],"can":[90],"reuse":[91],"knowledge":[92],"from":[93],"prior":[94],"designs.":[95,157],"Furthermore,":[96],"leverage":[98],"state-of-the-art":[100],"XGBoost":[101],"model":[102],"propose":[104],"novel":[106],"dynamic":[107],"tree":[108],"technique":[109],"overcome":[111],"overfitting.":[112],"Experimental":[113],"results":[114],"benchmark":[116],"circuits":[117],"show":[118],"our":[120],"approach":[121,150],"achieves":[122],"25%":[123],"improvement":[124],"or":[128],"37%":[129],"reduction":[130],"cost":[133],"compared":[134,174],"random":[136],"forest":[137],"method,":[138],"which":[139],"kernel":[142],"highly":[145],"cited":[146],"previous":[147],"work.":[148],"Our":[149],"further":[152],"validated":[153],"two":[155],"industrial":[156],"By":[158],"less":[160],"than":[161],"0.02%":[162],"possible":[164],"sets,":[166],"it":[167],"reduces":[168],"area":[169],"by":[170,180],"1.83%":[171],"1.43%":[173],"solutions":[178],"hand-tuned":[179],"experienced":[181],"designers.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":6}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}