{"id":"https://openalex.org/W2798299359","doi":"https://doi.org/10.23919/date.2018.8342001","title":"CCR: A concise convolution rule for sparse neural network accelerators","display_name":"CCR: A concise convolution rule for sparse neural network accelerators","publication_year":2018,"publication_date":"2018-03-01","ids":{"openalex":"https://openalex.org/W2798299359","doi":"https://doi.org/10.23919/date.2018.8342001","mag":"2798299359"},"language":"en","primary_location":{"id":"doi:10.23919/date.2018.8342001","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date.2018.8342001","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100352041","display_name":"Jiajun Li","orcid":"https://orcid.org/0000-0002-7208-9345"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajun Li","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108793944","display_name":"Guihai Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guihai Yan","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102393841","display_name":"Wenyan L\u00fc","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyan Lu","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034121567","display_name":"Shuhao Jiang","orcid":"https://orcid.org/0000-0002-7706-063X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhao Jiang","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101372514","display_name":"Shijun Gong","orcid":"https://orcid.org/0000-0002-0887-316X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shijun Gong","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018329525","display_name":"Jingya Wu","orcid":"https://orcid.org/0000-0003-4938-5899"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingya Wu","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023380073","display_name":"Xiaowei Li","orcid":"https://orcid.org/0000-0002-0874-814X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Li","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"189","last_page":"194"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9986000061035156,"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/T12676","display_name":"Machine Learning and ELM","score":0.9983000159263611,"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":0.7942947149276733},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7397934198379517},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.7203567028045654},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7195976376533508},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6576775312423706},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.6552000641822815},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.48464447259902954},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.43182867765426636},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.4117045998573303},{"id":"https://openalex.org/keywords/computational-science","display_name":"Computational science","score":0.3383885622024536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2892279624938965},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2853989899158478},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2793818712234497},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08735111355781555}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7942947149276733},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7397934198379517},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.7203567028045654},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7195976376533508},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6576775312423706},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.6552000641822815},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.48464447259902954},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.43182867765426636},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.4117045998573303},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.3383885622024536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2892279624938965},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2853989899158478},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2793818712234497},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08735111355781555},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/date.2018.8342001","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date.2018.8342001","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.9100000262260437}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2062227835","https://openalex.org/W2067523571","https://openalex.org/W2094756095","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2152839228","https://openalex.org/W2163605009","https://openalex.org/W2289252105","https://openalex.org/W2516141709","https://openalex.org/W2565851976","https://openalex.org/W2612076670","https://openalex.org/W2625457103","https://openalex.org/W2963674932","https://openalex.org/W4240168186","https://openalex.org/W6674330103","https://openalex.org/W6674479107","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W3157543420","https://openalex.org/W2964954556","https://openalex.org/W3034421924","https://openalex.org/W4386858688","https://openalex.org/W2982536526","https://openalex.org/W4380302312","https://openalex.org/W3008689640","https://openalex.org/W4385338604","https://openalex.org/W3081626085"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"networks":[2],"(CNNs)":[3],"have":[4,26],"achieved":[5,213],"great":[6],"success":[7],"in":[8,105,134],"a":[9,75,93,163,193,198,214,222],"broad":[10],"range":[11],"of":[12,36,56,65,173,183,206,216],"applications.":[13],"As":[14,192],"CNN-based":[15],"methods":[16],"are":[17,112,141],"often":[18],"both":[19,136],"computation":[20,37,174],"and":[21,38,58,69,87,99,122,125,139,175,237,242],"memory":[22,39,59,126,176],"intensive,":[23],"sparse":[24,70,85,94,199,230],"CNNs":[25,86],"emerged":[27],"as":[28,178,180],"an":[29],"effective":[30,98,132],"solution":[31],"to":[32,62,80,118,147,166,221],"reduce":[33],"the":[34,43,54,63,82,108,119,123,137,148,168,171,181,184,204,235],"amount":[35],"accesses":[40,60,127,177],"while":[41],"maintaining":[42],"high":[44],"accuracy.":[45],"However,":[46],"dense":[47,88,142,150,186,225],"CNN":[48,89,151,200],"accelerators":[49],"can":[50,128,143,233],"hardly":[51],"benefit":[52],"from":[53,170],"reduction":[55,172],"computations":[57,124],"due":[61],"lack":[64],"support":[66],"for":[67,159],"irregular":[68],"models.":[71],"This":[72],"paper":[73],"proposed":[74],"concise":[76],"convolution":[77,95],"rule":[78],"(CCR)":[79],"diminish":[81],"gap":[83],"between":[84],"accelerators.":[90,152],"CCR":[91,161],"transforms":[92],"into":[96],"multiple":[97],"ineffective":[100,103],"ones.":[101],"The":[102,131,208],"convolutions":[104,133],"which":[106,135,156],"either":[107],"neurons":[109,138],"or":[110],"synapses":[111,140],"all":[113],"zeros":[114],"do":[115],"not":[116],"contribute":[117],"final":[120],"results":[121],"be":[129,144],"eliminated.":[130],"easily":[145],"mapped":[146],"existing":[149,185],"Unlike":[153],"prior":[154],"approaches":[155],"trade":[157],"complexity":[158],"flexibility,":[160],"advocates":[162],"novel":[164],"approach":[165],"reaping":[167],"benefits":[169],"well":[179],"acceleration":[182],"architectures":[187],"without":[188],"intrusive":[189],"PE":[190],"modifications.":[191],"case":[194],"study,":[195],"we":[196],"implemented":[197],"accelerator,":[201],"SparseK,":[202],"following":[203],"rationale":[205],"CCR.":[207],"experiments":[209],"show":[210],"that":[211],"SparseK":[212,232],"speedup":[215],"2.9\u00d7":[217],"on":[218],"VGG16":[219],"compared":[220],"comparably":[223],"provisioned":[224],"architecture.":[226],"Compared":[227],"with":[228],"state-of-the-art":[229],"accelerators,":[231],"improve":[234],"performance":[236],"energy":[238],"efficiency":[239],"by":[240],"1.8\u00d7":[241],"1.5\u00d7,":[243],"respectively.":[244]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
