{"id":"https://openalex.org/W2052647915","doi":"https://doi.org/10.1145/1089008.1089011","title":"Merging path and gshare indexing in perceptron branch prediction","display_name":"Merging path and gshare indexing in perceptron branch prediction","publication_year":2005,"publication_date":"2005-09-01","ids":{"openalex":"https://openalex.org/W2052647915","doi":"https://doi.org/10.1145/1089008.1089011","mag":"2052647915"},"language":"en","primary_location":{"id":"doi:10.1145/1089008.1089011","is_oa":true,"landing_page_url":"https://doi.org/10.1145/1089008.1089011","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/1089008.1089011","source":{"id":"https://openalex.org/S26056741","display_name":"ACM Transactions on Architecture and Code Optimization","issn_l":"1544-3566","issn":["1544-3566","1544-3973"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Architecture and Code Optimization","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/1089008.1089011","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061578459","display_name":"David Tarjan","orcid":null},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"David Tarjan","raw_affiliation_strings":["University of Virginia, Charlottesville, VA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074818897","display_name":"Kevin Skadron","orcid":"https://orcid.org/0000-0002-8091-9302"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin Skadron","raw_affiliation_strings":["University of Virginia, Charlottesville, VA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5061578459"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":3.4316,"has_fulltext":true,"cited_by_count":63,"citation_normalized_percentile":{"value":0.92283919,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2","issue":"3","first_page":"280","last_page":"300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9975000023841858,"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":0.9975000023841858,"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/T10320","display_name":"Neural Networks and Applications","score":0.9865999817848206,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9847999811172485,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7845894694328308},{"id":"https://openalex.org/keywords/branch-predictor","display_name":"Branch predictor","score":0.7294676303863525},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6826836466789246},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5690737962722778},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5480988621711731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5312215089797974},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5158502459526062},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45654842257499695},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4525761008262634},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43719664216041565},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.43390417098999023},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36351582407951355},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.17275470495224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7845894694328308},{"id":"https://openalex.org/C168522837","wikidata":"https://www.wikidata.org/wiki/Q679552","display_name":"Branch predictor","level":2,"score":0.7294676303863525},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6826836466789246},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5690737962722778},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5480988621711731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5312215089797974},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5158502459526062},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45654842257499695},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4525761008262634},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43719664216041565},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.43390417098999023},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36351582407951355},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.17275470495224},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1089008.1089011","is_oa":true,"landing_page_url":"https://doi.org/10.1145/1089008.1089011","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/1089008.1089011","source":{"id":"https://openalex.org/S26056741","display_name":"ACM Transactions on Architecture and Code Optimization","issn_l":"1544-3566","issn":["1544-3566","1544-3973"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Architecture and Code Optimization","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.574.3","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.574.3","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://webspace.ulbsibiu.ro/lucian.vintan/html/Citare_2005.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/1089008.1089011","is_oa":true,"landing_page_url":"https://doi.org/10.1145/1089008.1089011","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/1089008.1089011","source":{"id":"https://openalex.org/S26056741","display_name":"ACM Transactions on Architecture and Code Optimization","issn_l":"1544-3566","issn":["1544-3566","1544-3973"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Architecture and Code Optimization","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6997328974","display_name":"Research Resources:  A High-Performance Shared-Purpose Cluster for Computer Architectural Simulation and Perceptual Interactive Ray Tracing","funder_award_id":"0224434","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7847790072","display_name":"CAREER:  Control-Theoretic Techniques and Thermal/Power Modeling for Dynamically Managing Temperature and Power in Microprocessors","funder_award_id":"0133634","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"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306170","display_name":"Intel Foundation","ror":"https://ror.org/01ek73717"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2052647915.pdf","grobid_xml":"https://content.openalex.org/works/W2052647915.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W63944998","https://openalex.org/W70582104","https://openalex.org/W134620092","https://openalex.org/W1569032152","https://openalex.org/W2025106479","https://openalex.org/W2081071903","https://openalex.org/W2096893988","https://openalex.org/W2098625517","https://openalex.org/W2108305176","https://openalex.org/W2118859527","https://openalex.org/W2123412482","https://openalex.org/W2127950539","https://openalex.org/W2129445095","https://openalex.org/W2130829030","https://openalex.org/W2137156241","https://openalex.org/W2138890053","https://openalex.org/W2144416297","https://openalex.org/W2144764850","https://openalex.org/W2149051149","https://openalex.org/W2153456949","https://openalex.org/W2156484396","https://openalex.org/W2542426564","https://openalex.org/W2752885492","https://openalex.org/W3005219185","https://openalex.org/W3145128584","https://openalex.org/W4210401038","https://openalex.org/W6602613798"],"related_works":["https://openalex.org/W3217435224","https://openalex.org/W1986441791","https://openalex.org/W4245248941","https://openalex.org/W3106494386","https://openalex.org/W4231994957","https://openalex.org/W4285741730","https://openalex.org/W3128183380","https://openalex.org/W2924231309","https://openalex.org/W2941320171","https://openalex.org/W2940336242"],"abstract_inverted_index":{"We":[0,43],"introduce":[1],"the":[2,8,11,33,41,61,66],"hashed":[3,67],"perceptron":[4,15,30,68],"predictor,":[5,31],"which":[6],"merges":[7],"concepts":[9],"behind":[10],"gshare,":[12],"path-based":[13,26,83],"and":[14,27,79],"branch":[16,37],"predictors.":[17],"This":[18],"predictor":[19,49,69],"can":[20,50],"achieve":[21],"superior":[22],"accuracy":[23,71],"to":[24,54,74],"a":[25,28,48,77,82],"global":[29],"previously":[32],"most":[34],"accurate":[35],"dynamic":[36],"predictors":[38],"known":[39],"in":[40],"literature.":[42],"also":[44],"show":[45],"how":[46],"such":[47],"be":[51],"ahead":[52],"pipelined":[53],"yield":[55],"one":[56],"cycle":[57],"effective":[58],"latency.":[59],"On":[60],"SPECint2000":[62],"set":[63],"of":[64],"benchmarks,":[65],"improves":[70],"by":[72],"up":[73],"15.6%":[75],"over":[76,81],"MAC-RHSP":[78],"27.2%":[80],"neural":[84],"predictor.":[85]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
