{"id":"https://openalex.org/W3206435118","doi":"https://doi.org/10.1109/tcsii.2021.3119369","title":"An Efficient Channel-Aware Sparse Binarized Neural Networks Inference Accelerator","display_name":"An Efficient Channel-Aware Sparse Binarized Neural Networks Inference Accelerator","publication_year":2021,"publication_date":"2021-10-13","ids":{"openalex":"https://openalex.org/W3206435118","doi":"https://doi.org/10.1109/tcsii.2021.3119369","mag":"3206435118"},"language":"en","primary_location":{"id":"doi:10.1109/tcsii.2021.3119369","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsii.2021.3119369","pdf_url":null,"source":{"id":"https://openalex.org/S93916849","display_name":"IEEE Transactions on Circuits & Systems II Express Briefs","issn_l":"1549-7747","issn":["1549-7747","1558-3791"],"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 Circuits and Systems II: Express Briefs","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/A5089589390","display_name":"Qingliang Liu","orcid":"https://orcid.org/0000-0003-0718-2620"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]},{"id":"https://openalex.org/I4210132426","display_name":"Shanghai Fudan Microelectronics (China)","ror":"https://ror.org/02vfj3j86","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132426"]},{"id":"https://openalex.org/I4391767673","display_name":"State Key Laboratory of ASIC and System","ror":"https://ror.org/01mamgv83","country_code":null,"type":"facility","lineage":["https://openalex.org/I24943067","https://openalex.org/I4391767673"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qingliang Liu","raw_affiliation_strings":["State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-0718-2620","affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I4210132426","https://openalex.org/I24943067","https://openalex.org/I4391767673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081419061","display_name":"Jinmei Lai","orcid":"https://orcid.org/0009-0003-5238-4720"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]},{"id":"https://openalex.org/I4210132426","display_name":"Shanghai Fudan Microelectronics (China)","ror":"https://ror.org/02vfj3j86","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132426"]},{"id":"https://openalex.org/I4391767673","display_name":"State Key Laboratory of ASIC and System","ror":"https://ror.org/01mamgv83","country_code":null,"type":"facility","lineage":["https://openalex.org/I24943067","https://openalex.org/I4391767673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinmei Lai","raw_affiliation_strings":["State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I4210132426","https://openalex.org/I24943067","https://openalex.org/I4391767673"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004231516","display_name":"Jiabao Gao","orcid":"https://orcid.org/0000-0002-6456-1590"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]},{"id":"https://openalex.org/I4210132426","display_name":"Shanghai Fudan Microelectronics (China)","ror":"https://ror.org/02vfj3j86","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132426"]},{"id":"https://openalex.org/I4391767673","display_name":"State Key Laboratory of ASIC and System","ror":"https://ror.org/01mamgv83","country_code":null,"type":"facility","lineage":["https://openalex.org/I24943067","https://openalex.org/I4391767673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiabao Gao","raw_affiliation_strings":["State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6456-1590","affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I4210132426","https://openalex.org/I24943067","https://openalex.org/I4391767673"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5089589390"],"corresponding_institution_ids":["https://openalex.org/I24943067","https://openalex.org/I4210132426","https://openalex.org/I4391767673"],"apc_list":null,"apc_paid":null,"fwci":0.4855,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.65791982,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"69","issue":"3","first_page":"1637","last_page":"1641"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9991000294685364,"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":0.9987999796867371,"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/inference","display_name":"Inference","score":0.7461985945701599},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.6174418926239014},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5746663212776184},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5744390487670898},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5537155270576477},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5315373539924622},{"id":"https://openalex.org/keywords/rectangle","display_name":"Rectangle","score":0.4531155824661255},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3764834403991699},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3338957130908966},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27723386883735657},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.23981744050979614},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.16642850637435913}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7461985945701599},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6174418926239014},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5746663212776184},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5744390487670898},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5537155270576477},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5315373539924622},{"id":"https://openalex.org/C2781302577","wikidata":"https://www.wikidata.org/wiki/Q209","display_name":"Rectangle","level":2,"score":0.4531155824661255},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3764834403991699},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3338957130908966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27723386883735657},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.23981744050979614},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.16642850637435913},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsii.2021.3119369","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsii.2021.3119369","pdf_url":null,"source":{"id":"https://openalex.org/S93916849","display_name":"IEEE Transactions on Circuits & Systems II Express Briefs","issn_l":"1549-7747","issn":["1549-7747","1558-3791"],"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 Circuits and Systems II: Express Briefs","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8799999952316284,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G4757893089","display_name":null,"funder_award_id":"U20A20202","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2300242332","https://openalex.org/W2565125333","https://openalex.org/W2604700561","https://openalex.org/W2618530766","https://openalex.org/W2624696420","https://openalex.org/W2765235648","https://openalex.org/W2963427045","https://openalex.org/W2972343638","https://openalex.org/W2984035546","https://openalex.org/W2998470761","https://openalex.org/W3009849929","https://openalex.org/W3025143601","https://openalex.org/W3040090953","https://openalex.org/W3044387456","https://openalex.org/W3047345547","https://openalex.org/W3091355409","https://openalex.org/W3118608800","https://openalex.org/W3159262856","https://openalex.org/W6639703010","https://openalex.org/W6787972765"],"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":{"The":[0],"binarized":[1,99],"neural":[2],"network":[3],"(BNN)":[4],"inference":[5],"accelerators":[6,20],"show":[7,164],"great":[8],"promise":[9],"in":[10,29,50,104],"cost-":[11],"and":[12,101,112,193],"power-restricted":[13],"domains.":[14],"However,":[15],"the":[16,26,43,48,59,62,80,85,114,127,147,157],"performances":[17],"of":[18,65,90,144,146],"these":[19,118],"are":[21],"still":[22],"severely":[23],"limited":[24],"by":[25,47,58,78,106,136],"significant":[27],"redundancies":[28,49],"BNNs":[30,51],"inference.":[31],"In":[32],"this":[33],"brief,":[34],"we":[35,83,150],"introduce":[36],"channel-aware":[37],"sparse":[38],"accelerator":[39],"(CAA)":[40],"to":[41,124,155],"alleviate":[42],"performance":[44],"degradations":[45],"induced":[46],"while":[52],"maintaining":[53],"original":[54,87],"accuracies.":[55],"First,":[56],"motivated":[57],"observation":[60],"that":[61,165],"convolution":[63],"processes":[64],"our":[66,137,166],"rebuilt":[67],"rectangle":[68,108],"kernels":[69],"contain":[70],"many":[71],"redundant":[72,159],"operations":[73,96,120],"which":[74],"can":[75,121],"be":[76,122],"skipped":[77],"exploiting":[79],"BNN-specific":[81],"property,":[82],"convert":[84],"entire":[86],"XNOR-popcount":[88],"convolutions":[89],"each":[91],"neuron":[92],"into":[93],"channel-aware-popcount":[94],"(CAP)":[95],"for":[97],"all":[98],"convolutional":[100],"fully-connected":[102],"layers":[103],"CAA":[105],"employing":[107],"kernel":[109],"simplification":[110],"strategy":[111],"eliminate":[113],"unnecessary":[115],"operations.":[116,161],"Meanwhile,":[117],"CAP":[119,148,160],"implemented":[123],"directly":[125],"gain":[126],"final":[128],"output":[129],"without":[130],"any":[131],"extra":[132],"steps.":[133],"Furthermore,":[134],"inspired":[135],"new":[138],"observations":[139],"on":[140,169],"two":[141],"specific":[142],"kinds":[143],"properties":[145],"operations,":[149],"adopt":[151],"group":[152],"pruning":[153],"approach":[154],"save":[156],"remaining":[158],"Experimental":[162],"results":[163],"design":[167],"evaluated":[168],"an":[170],"embedded":[171],"FPGA":[172],"achieves":[173],"4.2-":[174],"<inline-formula":[175,184,194],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[176,185,195],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[177,186,196],"<tex-math":[178,187,197],"notation=\"LaTeX\">$6.6{\\times":[179],"}$":[180,189,199],"</tex-math></inline-formula>":[181,190,200],"inference-speedup,":[182],"3.6-":[183],"notation=\"LaTeX\">$5.5{\\times":[188],"energy-efficiency":[191],"enhancement,":[192],"notation=\"LaTeX\">$1.35{\\times":[198],"resource-efficiency":[201],"improvement":[202],"compared":[203],"with":[204],"state-of-the-art":[205],"works.":[206]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
