{"id":"https://openalex.org/W2888295354","doi":"https://doi.org/10.1109/access.2018.2867151","title":"Using Ensemble Learning to Improve Automatic Vectorization of Tensor Contraction Program","display_name":"Using Ensemble Learning to Improve Automatic Vectorization of Tensor Contraction Program","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2888295354","doi":"https://doi.org/10.1109/access.2018.2867151","mag":"2888295354"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2867151","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2867151","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2867151","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101544022","display_name":"Liu Hui","orcid":"https://orcid.org/0000-0002-9607-8069"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hui Liu","raw_affiliation_strings":["State Key Laboratory of Mathematical Engineering and Advanced Computing, PLA Information Engineering University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mathematical Engineering and Advanced Computing, PLA Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113746674","display_name":"Rongcai Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongcai Zhao","raw_affiliation_strings":["State Key Laboratory of Mathematical Engineering and Advanced Computing, PLA Information Engineering University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mathematical Engineering and Advanced Computing, PLA Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019824583","display_name":"Kai Nie","orcid":"https://orcid.org/0000-0001-7568-4628"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Nie","raw_affiliation_strings":["State Key Laboratory of Mathematical Engineering and Advanced Computing, PLA Information Engineering University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mathematical Engineering and Advanced Computing, PLA Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101544022"],"corresponding_institution_ids":["https://openalex.org/I169689159"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2525,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.50329993,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"6","issue":null,"first_page":"47112","last_page":"47124"},"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8291338682174683},{"id":"https://openalex.org/keywords/vectorization","display_name":"Vectorization (mathematics)","score":0.7145671844482422},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.564755916595459},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5621929168701172},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4961903691291809},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48750898241996765},{"id":"https://openalex.org/keywords/contraction","display_name":"Contraction (grammar)","score":0.4718197286128998},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.4662318229675293},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4328809976577759},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3514936566352844},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.26598361134529114},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19126364588737488},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10313406586647034}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8291338682174683},{"id":"https://openalex.org/C41681595","wikidata":"https://www.wikidata.org/wiki/Q7917855","display_name":"Vectorization (mathematics)","level":2,"score":0.7145671844482422},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.564755916595459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5621929168701172},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4961903691291809},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48750898241996765},{"id":"https://openalex.org/C163415756","wikidata":"https://www.wikidata.org/wiki/Q126473","display_name":"Contraction (grammar)","level":2,"score":0.4718197286128998},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.4662318229675293},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4328809976577759},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3514936566352844},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.26598361134529114},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19126364588737488},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10313406586647034},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2867151","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2867151","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:cd4a19c1313a4644b5c7cb7fb43c17c7","is_oa":true,"landing_page_url":"https://doaj.org/article/cd4a19c1313a4644b5c7cb7fb43c17c7","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 47112-47124 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2867151","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2867151","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5725478124","display_name":null,"funder_award_id":"2015QK21","funder_id":"https://openalex.org/F4320311345","funder_display_name":"Henan Normal University"}],"funders":[{"id":"https://openalex.org/F4320311345","display_name":"Henan Normal University","ror":"https://ror.org/00s13br28"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W59960346","https://openalex.org/W190064633","https://openalex.org/W1584675441","https://openalex.org/W1967382945","https://openalex.org/W1967846636","https://openalex.org/W2010941383","https://openalex.org/W2052902739","https://openalex.org/W2053732522","https://openalex.org/W2064441385","https://openalex.org/W2084482561","https://openalex.org/W2103006842","https://openalex.org/W2108737583","https://openalex.org/W2117612939","https://openalex.org/W2142079700","https://openalex.org/W2143124065","https://openalex.org/W2147370410","https://openalex.org/W2147623728","https://openalex.org/W2156560068","https://openalex.org/W2166061155","https://openalex.org/W2168519934","https://openalex.org/W2330621167","https://openalex.org/W4234918759","https://openalex.org/W6607680086","https://openalex.org/W6671713069","https://openalex.org/W6673720697","https://openalex.org/W6676176808","https://openalex.org/W6681165643","https://openalex.org/W6681980112","https://openalex.org/W6682271648","https://openalex.org/W6684464923"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W1038900426","https://openalex.org/W2150029999","https://openalex.org/W2099182244","https://openalex.org/W1580150424","https://openalex.org/W2325482571","https://openalex.org/W4241032203","https://openalex.org/W2127236386","https://openalex.org/W2294552197"],"abstract_inverted_index":{"Automatic":[0],"vectorization":[1,30,159,183,189],"is":[2,48,58,64,90,145,264,273],"crucial":[3],"for":[4,18,191,210],"improving":[5],"the":[6,27,36,52,62,65,70,75,119,128,133,175,187,192,196,201,215,226,235,258,261,269],"performance":[7,45,72,160,176,272],"of":[8,29,38,136,177,200,275,281],"computationally":[9],"intensive":[10,85],"programs.":[11],"Existing":[12],"compilers":[13],"use":[14,37,132],"conservative":[15],"optimization":[16,67],"strategies":[17,68,184],"automatic":[19,158],"vectorization,":[20],"which,":[21],"in":[22,92],"many":[23],"cases,":[24],"lead":[25],"to":[26,42,50,74,110,139,147,173,195],"loss":[28],"opportunity.":[31],"Studies":[32],"have":[33,118],"shown":[34],"that":[35,234],"machine":[39,98],"learning":[40,99,137,142,171,218,223,228],"algorithms":[41],"build":[43],"a":[44,83,141,207],"prediction":[46,236,242,262],"model":[47,56,172,237],"beneficial":[49],"improve":[51],"program":[53,59,71],"performance.":[54],"The":[55,230],"input":[57],"features,":[60],"and":[61,104,122,149,185,240,254,279],"output":[63],"predicted":[66],"or":[69],"related":[73],"optimization.":[76],"In":[77,126,152,267],"this":[78,153],"paper,":[79,154],"we":[80,155,205,220],"focus":[81],"on":[82,102,164,214,244],"computational":[84],"loop":[86],"structure-tensor":[87],"contraction,":[88],"which":[89,144],"common":[91],"quantum":[93],"chemical":[94],"simulations.":[95],"Most":[96],"existing":[97,129,259],"methods":[100,130],"rely":[101],"control":[103,121],"data":[105,123,252],"flow":[106,124],"graphs":[107],"as":[108],"features":[109,211],"represent":[111],"programs,":[112],"but":[113],"different":[114,182,246,249],"tensor":[115,178,202],"contraction":[116,179,203],"kernels":[117,180],"same":[120,134],"graphs.":[125],"addition,":[127,268],"often":[131],"kind":[135],"algorithm":[138],"construct":[140,168],"model,":[143],"prone":[146],"overfitting":[148],"low-precision":[150],"problems.":[151],"propose":[156,206],"an":[157,169],"enhancement":[161],"method":[162,209],"based":[163],"ensemble":[165,170,217],"learning.":[166],"We":[167],"predict":[174],"with":[181,248,257],"select":[186],"best":[188],"strategy":[190],"kernels.":[193],"According":[194],"storage":[197],"access":[198],"patterns":[199],"kernels,":[204],"static":[208],"representation.":[212],"Based":[213],"multi-algorithm":[216],"strategy,":[219],"obtain":[221],"better":[222],"results":[224,232],"than":[225],"single":[227],"algorithm.":[229],"experimental":[231],"show":[233],"achieves":[238],"88%":[239],"87%":[241],"efficiency":[243,263],"two":[245],"platforms":[247],"instruction":[250],"sets,":[251],"types,":[253],"compilers.":[255],"Compared":[256],"methods,":[260],"greatly":[265],"improved.":[266],"average":[270],"peak":[271],"2.96\u00d7":[274],"Intel":[276],"ICC":[277],"12.0":[278],"2.98\u00d7":[280],"GCC":[282],"4.6":[283],"compiler,":[284],"respectively.":[285]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}