{"id":"https://openalex.org/W2147370410","doi":"https://doi.org/10.1145/2737924.2737969","title":"Autotuning algorithmic choice for input sensitivity","display_name":"Autotuning algorithmic choice for input sensitivity","publication_year":2015,"publication_date":"2015-06-03","ids":{"openalex":"https://openalex.org/W2147370410","doi":"https://doi.org/10.1145/2737924.2737969","mag":"2147370410"},"language":"en","primary_location":{"id":"doi:10.1145/2737924.2737969","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2737924.2737969","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2737924.2737969","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/2737924.2737969","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048052285","display_name":"Yufei Ding","orcid":"https://orcid.org/0000-0002-8716-5793"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yufei Ding","raw_affiliation_strings":["North Carolina State University, USA"],"affiliations":[{"raw_affiliation_string":"North Carolina State University, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089997788","display_name":"Jason Ansel","orcid":"https://orcid.org/0009-0007-5207-2179"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jason Ansel","raw_affiliation_strings":["Massachusetts Institute of Technology, USA","Massachusetts Institute Of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]},{"raw_affiliation_string":"Massachusetts Institute Of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067352490","display_name":"Kalyan Veeramachaneni","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kalyan Veeramachaneni","raw_affiliation_strings":["Massachusetts Institute of Technology, USA","Massachusetts Institute Of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]},{"raw_affiliation_string":"Massachusetts Institute Of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100624451","display_name":"Xipeng Shen","orcid":"https://orcid.org/0000-0003-3599-8010"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xipeng Shen","raw_affiliation_strings":["North Carolina State University, USA"],"affiliations":[{"raw_affiliation_string":"North Carolina State University, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000646181","display_name":"Una-May O\u2019Reilly","orcid":"https://orcid.org/0000-0001-6923-8445"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Una-May O\u2019Reilly","raw_affiliation_strings":["Massachusetts Institute of Technology, USA","Massachusetts Institute Of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]},{"raw_affiliation_string":"Massachusetts Institute Of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046791216","display_name":"Saman Amarasinghe","orcid":"https://orcid.org/0000-0002-7231-7643"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saman Amarasinghe","raw_affiliation_strings":["Massachusetts Institute of Technology, USA","Massachusetts Institute Of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]},{"raw_affiliation_string":"Massachusetts Institute Of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5048052285"],"corresponding_institution_ids":["https://openalex.org/I137902535"],"apc_list":null,"apc_paid":null,"fwci":15.502,"has_fulltext":true,"cited_by_count":91,"citation_normalized_percentile":{"value":0.99421366,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"379","last_page":"390"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","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/T10054","display_name":"Parallel Computing and Optimization Techniques","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/T10126","display_name":"Logic, programming, and type systems","score":0.9912999868392944,"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"}},{"id":"https://openalex.org/T11697","display_name":"Numerical Methods and Algorithms","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/speedup","display_name":"Speedup","score":0.8478466272354126},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7660468816757202},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5807059407234192},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.5526531338691711},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5016579627990723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4727412462234497},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.46492457389831543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43764933943748474},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.42083272337913513},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.382534921169281},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3503054976463318},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.15492931008338928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11233541369438171},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08527609705924988}],"concepts":[{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.8478466272354126},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7660468816757202},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5807059407234192},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.5526531338691711},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5016579627990723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4727412462234497},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.46492457389831543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43764933943748474},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.42083272337913513},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.382534921169281},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3503054976463318},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.15492931008338928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11233541369438171},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08527609705924988},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/2737924.2737969","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2737924.2737969","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2737924.2737969","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.897.9041","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.897.9041","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://dspace.mit.edu/bitstream/handle/1721.1/88083/MIT-CSAIL-TR-2014-014.pdf%3Bjsessionid%3DCAFBEBBDBC2DC29EA989E3AC9FB88DF7?sequence%3D1","raw_type":"text"},{"id":"pmh:oai:dspace.mit.edu:1721.1/88083","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/88083","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"pmh:oai:dspace.mit.edu:1721.1/99720","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/99720","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"MIT web domain","raw_type":"http://purl.org/eprint/type/ConferencePaper"}],"best_oa_location":{"id":"doi:10.1145/2737924.2737969","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2737924.2737969","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2737924.2737969","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G460697733","display_name":null,"funder_award_id":"1320796","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6283244133","display_name":null,"funder_award_id":"1320796 and CAREER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6593955126","display_name":null,"funder_award_id":"1464216,1320796,CAREER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6671297155","display_name":null,"funder_award_id":"CAREER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G887183687","display_name":"CRII: SHF: A Compiler and Runtime Infrastructure for Flexible Scheduling and Scheduling-Enabled Optimizations on GPUs","funder_award_id":"1464216","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G971888425","display_name":null,"funder_award_id":"DE-SC0005288, DE-SC0008923, Early Career","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2147370410.pdf","grobid_xml":"https://content.openalex.org/works/W2147370410.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1480376833","https://openalex.org/W1492552760","https://openalex.org/W1499644348","https://openalex.org/W1518969538","https://openalex.org/W1535785330","https://openalex.org/W1587708554","https://openalex.org/W1599660606","https://openalex.org/W1964031104","https://openalex.org/W1971367716","https://openalex.org/W1972209410","https://openalex.org/W1980225486","https://openalex.org/W1991591392","https://openalex.org/W2000873501","https://openalex.org/W2001784723","https://openalex.org/W2009418036","https://openalex.org/W2044280736","https://openalex.org/W2052934867","https://openalex.org/W2062060002","https://openalex.org/W2072707864","https://openalex.org/W2079219249","https://openalex.org/W2093708648","https://openalex.org/W2094190665","https://openalex.org/W2099625934","https://openalex.org/W2100218206","https://openalex.org/W2102182691","https://openalex.org/W2104306032","https://openalex.org/W2111444234","https://openalex.org/W2114703523","https://openalex.org/W2116210226","https://openalex.org/W2116466695","https://openalex.org/W2118460293","https://openalex.org/W2124853563","https://openalex.org/W2130289795","https://openalex.org/W2134222034","https://openalex.org/W2135653967","https://openalex.org/W2135858107","https://openalex.org/W2136628731","https://openalex.org/W2136952590","https://openalex.org/W2137824953","https://openalex.org/W2149706766","https://openalex.org/W2160786443","https://openalex.org/W2161363082","https://openalex.org/W2163491234","https://openalex.org/W2168519934","https://openalex.org/W2171601645","https://openalex.org/W2600258283","https://openalex.org/W2990714382","https://openalex.org/W4214807841","https://openalex.org/W4239625798","https://openalex.org/W4243796884","https://openalex.org/W4253417586"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W4391547476","https://openalex.org/W2597809628"],"abstract_inverted_index":{"A":[0],"daunting":[1],"challenge":[2,34],"faced":[3],"by":[4,85],"program":[5,135],"performance":[6],"autotuning":[7,40],"is":[8],"input":[9,20,28,50,56,87,132],"sensitivity,":[10],"where":[11],"the":[12,33,79,104],"best":[13],"autotuned":[14],"configuration":[15,117],"may":[16],"vary":[17],"with":[18],"different":[19],"sets.":[21],"This":[22],"paper":[23],"presents":[24],"a":[25,48,66,110,115,122,126],"novel":[26],"two-level":[27,49],"learning":[29],"algorithm":[30],"to":[31,53,75,109],"tackle":[32],"for":[35,118,130],"an":[36],"important":[37],"class":[38],"of":[39,68,97],"problems,":[41],"algorithmic":[42,76,98],"autotuning.":[43],"The":[44],"new":[45,105],"approach":[46],"uses":[47],"clustering":[51],"method":[52,129],"automatically":[54],"refine":[55],"grouping,":[57],"feature":[58,92],"selection,":[59],"and":[60,94,121],"classifier":[61],"construction.":[62],"Its":[63],"design":[64],"solves":[65],"series":[67],"open":[69],"issues":[70],"that":[71,103],"are":[72],"particularly":[73],"essential":[74],"autotuning,":[77],"including":[78],"enormous":[80],"optimization":[81],"space,":[82],"complex":[83],"influence":[84],"deep":[86],"features,":[88],"high":[89],"cost":[90],"in":[91,134],"extraction,":[93],"variable":[95],"accuracy":[96],"choices.":[99],"Experimental":[100],"results":[101],"show":[102],"solution":[106],"yields":[107],"up":[108],"3x":[111],"speedup":[112,124],"over":[113,125],"using":[114],"single":[116],"all":[119],"inputs,":[120],"34x":[123],"traditional":[127],"one-level":[128],"addressing":[131],"sensitivity":[133],"optimizations.":[136]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":18},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":17},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
