{"id":"https://openalex.org/W4411259588","doi":"https://doi.org/10.1145/3735452.3735538","title":"Multi-level Machine Learning-Guided Autotuning for Efficient Code Generation on a Deep Learning Accelerator","display_name":"Multi-level Machine Learning-Guided Autotuning for Efficient Code Generation on a Deep Learning Accelerator","publication_year":2025,"publication_date":"2025-06-13","ids":{"openalex":"https://openalex.org/W4411259588","doi":"https://doi.org/10.1145/3735452.3735538"},"language":"en","primary_location":{"id":"doi:10.1145/3735452.3735538","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3735452.3735538","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3735452.3735538","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems","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/10.1145/3735452.3735538","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055570848","display_name":"Jungwon Cha","orcid":"https://orcid.org/0009-0008-2123-454X"},"institutions":[{"id":"https://openalex.org/I88761825","display_name":"Korea University of Science and Technology","ror":"https://ror.org/000qzf213","country_code":"KR","type":"education","lineage":["https://openalex.org/I88761825"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"JooHyoung Cha","raw_affiliation_strings":["University of Science and Technology, Daejeon, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0008-2123-454X","affiliations":[{"raw_affiliation_string":"University of Science and Technology, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I88761825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000297383","display_name":"Munyoung Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Munyoung Lee","raw_affiliation_strings":["Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0009-3667-7455","affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062228838","display_name":"Jinse Kwon","orcid":"https://orcid.org/0000-0003-3091-9926"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jinse Kwon","raw_affiliation_strings":["Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-3091-9926","affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101558196","display_name":"Jemin Lee","orcid":"https://orcid.org/0000-0002-9332-3508"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jemin Lee","raw_affiliation_strings":["Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-9332-3508","affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080783573","display_name":"Yongin Kwon","orcid":"https://orcid.org/0000-0003-2973-246X"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongin Kwon","raw_affiliation_strings":["Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-2973-246X","affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1222,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72182933,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"134","last_page":"145"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9789999723434448,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7597417235374451},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5526314377784729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5183021426200867},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4421655237674713},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.343708872795105}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7597417235374451},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5526314377784729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5183021426200867},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4421655237674713},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.343708872795105},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3735452.3735538","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3735452.3735538","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3735452.3735538","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3735452.3735538","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3735452.3735538","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3735452.3735538","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7022013420","display_name":null,"funder_award_id":"RS-2023-00277060","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411259588.pdf","grobid_xml":"https://content.openalex.org/works/W4411259588.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W2153185479","https://openalex.org/W2156560068","https://openalex.org/W2194775991","https://openalex.org/W2245493112","https://openalex.org/W2295598076","https://openalex.org/W2734941459","https://openalex.org/W2997591727","https://openalex.org/W3023081374","https://openalex.org/W3034143844","https://openalex.org/W3098251449","https://openalex.org/W3117523176","https://openalex.org/W3163661296","https://openalex.org/W4221062244","https://openalex.org/W4251637954","https://openalex.org/W4313442384","https://openalex.org/W4320519434","https://openalex.org/W4327511290","https://openalex.org/W4327930463","https://openalex.org/W4381785750","https://openalex.org/W4384111957","https://openalex.org/W4385453308","https://openalex.org/W4385695859","https://openalex.org/W4386709679","https://openalex.org/W4388483669","https://openalex.org/W4393145114","https://openalex.org/W4394998532","https://openalex.org/W4395106432","https://openalex.org/W4399282189","https://openalex.org/W4400490265","https://openalex.org/W4403223472","https://openalex.org/W4403865930","https://openalex.org/W4408894246","https://openalex.org/W6950140870"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W3086377361"],"abstract_inverted_index":{"The":[0],"growing":[1],"complexity":[2],"of":[3,47,126,142],"deep":[4,15],"learning":[5,16],"models":[6],"necessitates":[7],"specialized":[8],"hardware":[9],"and":[10,35,73,93,134],"software":[11],"optimizations,":[12],"particularly":[13],"for":[14],"accelerators.":[17],"While":[18],"machine":[19,65],"learning-based":[20],"autotuning":[21,67,149],"methods":[22],"have":[23],"emerged":[24],"as":[25],"a":[26,63,81,131],"promising":[27],"solution":[28],"to":[29,44,70,85,91,147],"reduce":[30],"manual":[31],"effort,":[32],"both":[33],"template-based":[34],"template-free":[36],"approaches":[37],"suffer":[38],"from":[39],"prolonged":[40],"tuning":[41],"times":[42],"due":[43],"the":[45,106,127],"profiling":[46,137],"invalid":[48,88,136,154],"configurations,":[49],"which":[50],"may":[51],"result":[52],"in":[53],"runtime":[54],"errors.":[55],"To":[56],"address":[57],"this":[58],"issue,":[59],"we":[60],"propose":[61],"ML2Tuner,":[62],"multi-level":[64],"learning-guided":[66],"technique":[68],"designed":[69],"improve":[71],"efficiency":[72],"robustness.":[74],"ML2Tuner":[75,118],"introduces":[76],"two":[77],"key":[78],"ideas:":[79],"(1)":[80],"validity":[82],"prediction":[83,98],"model":[84,99],"filter":[86],"out":[87,153],"configurations":[89],"prior":[90],"profiling,":[92],"(2)":[94],"an":[95,112,140],"advanced":[96],"performance":[97,121,150],"that":[100,117],"leverages":[101],"hidden":[102],"features":[103],"extracted":[104],"during":[105],"compilation":[107],"process.":[108],"Experimental":[109],"results":[110],"on":[111],"extended":[113],"VTA":[114],"accelerator":[115],"demonstrate":[116],"achieves":[119],"equivalent":[120],"improvements":[122],"using":[123],"only":[124],"12.3%":[125],"samples":[128],"required":[129],"by":[130,139,151],"TVM-like":[132],"approach":[133],"reduces":[135],"attempts":[138],"average":[141],"60.8%,":[143],"highlighting":[144],"its":[145],"potential":[146],"enhance":[148],"filtering":[152],"configurations.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}