{"id":"https://openalex.org/W3169213526","doi":"https://doi.org/10.1109/tc.2021.3089366","title":"A Novel CONV Acceleration Strategy Based on Logical PE Set Segmentation for Row Stationary Dataflow","display_name":"A Novel CONV Acceleration Strategy Based on Logical PE Set Segmentation for Row Stationary Dataflow","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3169213526","doi":"https://doi.org/10.1109/tc.2021.3089366","mag":"3169213526"},"language":"en","primary_location":{"id":"doi:10.1109/tc.2021.3089366","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2021.3089366","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","0016-9340","1557-9956","2326-3814"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Computers","raw_type":"journal-article"},"type":"article","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/A5100385124","display_name":"Bowen Zhang","orcid":"https://orcid.org/0000-0001-6934-9487"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Zhang","raw_affiliation_strings":["State Key Lab of ISN, Xidian University, Xi'an, Shannxi, China, (e-mail: bwzhang1991@163.com)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of ISN, Xidian University, Xi'an, Shannxi, China, (e-mail: bwzhang1991@163.com)","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049448415","display_name":"Huaxi Gu","orcid":"https://orcid.org/0000-0002-6409-2229"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaxi Gu","raw_affiliation_strings":["State Key Lab of ISN, Xidian University, Xi'an, Shaanxi, China, 710071 (e-mail: hxgu@xidian.edu.cn)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of ISN, Xidian University, Xi'an, Shaanxi, China, 710071 (e-mail: hxgu@xidian.edu.cn)","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100366743","display_name":"Kun Wang","orcid":"https://orcid.org/0009-0005-5110-0153"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Wang","raw_affiliation_strings":["School of Computer Science, Xidian University, Xi'an, Shanxi, China, (e-mail: kwang@mail.xidian.edu.cn)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Xidian University, Xi'an, Shanxi, China, (e-mail: kwang@mail.xidian.edu.cn)","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100402361","display_name":"Yintang Yang","orcid":"https://orcid.org/0000-0001-9745-5404"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yintang Yang","raw_affiliation_strings":["Institute of Microelectronics, Xidian University, Xi'an, Shanxi, China, (e-mail: ytyang@xidian.edu.cn)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Xidian University, Xi'an, Shanxi, China, (e-mail: ytyang@xidian.edu.cn)","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.4917,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.62543994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9994000196456909,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dataflow","display_name":"Dataflow","score":0.9077562093734741},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7897331118583679},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6235799193382263},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5847871899604797},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5841986536979675},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5218407511711121},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.5182692408561707},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.495644211769104},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4848266839981079},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.475197434425354},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4657343924045563},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4564921259880066},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.45291540026664734},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4439363479614258},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3987509608268738},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3463659882545471}],"concepts":[{"id":"https://openalex.org/C96324660","wikidata":"https://www.wikidata.org/wiki/Q205446","display_name":"Dataflow","level":2,"score":0.9077562093734741},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7897331118583679},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6235799193382263},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5847871899604797},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5841986536979675},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5218407511711121},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.5182692408561707},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.495644211769104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4848266839981079},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.475197434425354},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4657343924045563},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4564921259880066},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.45291540026664734},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4439363479614258},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3987509608268738},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3463659882545471},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tc.2021.3089366","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2021.3089366","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","0016-9340","1557-9956","2326-3814"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9100000262260437,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2519052758","display_name":"\u81ea\u611f\u77e5\u81ea\u7ec4\u7ec7\u5f02\u6784\u4f17\u6838\u667a\u80fd\u82af\u7247\u7684\u4e92\u8fde\u4e0e\u5b58\u50a8\u6280\u672f\u7814\u7a76","funder_award_id":"61934002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5242644447","display_name":"\u4e09\u7ef4\u5149\u7535\u6df7\u5408\u7247\u4e0a\u7f51\u7edc\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61634004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2044535169","https://openalex.org/W2074278632","https://openalex.org/W2089155985","https://openalex.org/W2094756095","https://openalex.org/W2094806703","https://openalex.org/W2117696986","https://openalex.org/W2119677480","https://openalex.org/W2152839228","https://openalex.org/W2194775991","https://openalex.org/W2289252105","https://openalex.org/W2334805829","https://openalex.org/W2442974303","https://openalex.org/W2518281301","https://openalex.org/W2522548197","https://openalex.org/W2603836393","https://openalex.org/W2606722458","https://openalex.org/W2612076670","https://openalex.org/W2625457103","https://openalex.org/W2626429347","https://openalex.org/W2626712922","https://openalex.org/W2742597885","https://openalex.org/W2752782242","https://openalex.org/W2769815320","https://openalex.org/W2773339846","https://openalex.org/W2802367674","https://openalex.org/W2807091852","https://openalex.org/W2907885488","https://openalex.org/W2919115771","https://openalex.org/W2920326572","https://openalex.org/W2953915593","https://openalex.org/W2963125010","https://openalex.org/W2963446712","https://openalex.org/W2971734772","https://openalex.org/W3004171485","https://openalex.org/W3011803421","https://openalex.org/W3012504067","https://openalex.org/W3035560939","https://openalex.org/W3085277063","https://openalex.org/W3101558675","https://openalex.org/W4234863022","https://openalex.org/W4236868170","https://openalex.org/W4246193833","https://openalex.org/W4247470470","https://openalex.org/W4249932213","https://openalex.org/W4297775537","https://openalex.org/W6637373629","https://openalex.org/W6638783484","https://openalex.org/W6737664043"],"related_works":["https://openalex.org/W2293118914","https://openalex.org/W2998381397","https://openalex.org/W4236419692","https://openalex.org/W3167919718","https://openalex.org/W4251718783","https://openalex.org/W2171015181","https://openalex.org/W4239447582","https://openalex.org/W1484403103","https://openalex.org/W2807127337","https://openalex.org/W1998888015"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2,12],"networks":[3,13],"(DCNNs)":[4],"have":[5],"been":[6],"proposed":[7,125],"as":[8],"enhanced":[9],"developments":[10],"of":[11,18,33,37,48,60,130,172],"(NNs)":[14],"in":[15,25,44,54,79,175],"the":[16,31,35,55,80,84,100,128,140,150,170,176,183],"field":[17],"artificial":[19],"intelligence":[20],"(AI)":[21],"and":[22,50,57,62,68,88,133,165],"successfully":[23],"applied":[24],"deep":[26],"learning":[27],"(DL)":[28],"scenarios.":[29],"With":[30],"advancement":[32],"technology,":[34],"number":[36,47],"network":[38],"layers":[39],"has":[40,93],"continuously":[41],"increased,":[42],"resulting":[43],"a":[45,71,95,106],"huge":[46],"calculations":[49],"memory":[51,85],"accesses":[52],"required":[53],"training":[56],"inference":[58],"process":[59],"DCNNs":[61],"thereby":[63],"hindering":[64],"their":[65],"further":[66],"deployment":[67],"application.":[69],"Using":[70],"specific":[72],"dataflow":[73,123],"formed":[74],"by":[75,139],"reusable":[76],"DCNN":[77,90],"data":[78,177],"network-on-chip":[81],"(NoC),":[82],"reducing":[83],"access":[86],"pressure":[87],"improving":[89],"processing":[91,135,162],"efficiency":[92],"become":[94],"promising":[96],"acceleration":[97,111,167],"schemes":[98],"for":[99,119],"current":[101],"DCNN.":[102],"In":[103],"this":[104],"paper,":[105],"novel":[107],"convolution":[108],"layer":[109],"(CONV)":[110],"strategy":[112,153],"based":[113,154],"on":[114,155],"logical":[115],"PE":[116,156],"set":[117,157],"segmentation":[118,158],"row":[120],"stationary":[121],"(RS)":[122],"is":[124],"to":[126],"solve":[127],"problems":[129],"low":[131],"flexibility":[132],"inefficient":[134],"array":[136],"utilization":[137,164],"faced":[138],"conventional":[141,184],"folding":[142],"mapping":[143,152],"strategy.":[144,185],"The":[145],"simulation":[146],"results":[147],"show":[148],"that":[149],"new":[151],"can":[159],"achieve":[160],"better":[161],"element":[163],"CONV":[166],"improvement":[168],"at":[169],"expense":[171],"little":[173],"increase":[174],"movement":[178],"energy":[179],"consumption":[180],"compared":[181],"with":[182]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
