{"id":"https://openalex.org/W2802200896","doi":"https://doi.org/10.1109/iscas.2018.8351666","title":"Bit-width Adaptive Accelerator Design for Convolution Neural Network","display_name":"Bit-width Adaptive Accelerator Design for Convolution Neural Network","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2802200896","doi":"https://doi.org/10.1109/iscas.2018.8351666","mag":"2802200896"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2018.8351666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2018.8351666","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5068876730","display_name":"Jianxin Guo","orcid":"https://orcid.org/0000-0003-3655-8914"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxin Guo","raw_affiliation_strings":["Institute of Microelectronics, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089","https://openalex.org/I4210119392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054524841","display_name":"Shouyi Yin","orcid":"https://orcid.org/0000-0003-2309-572X"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shouyi Yin","raw_affiliation_strings":["Institute of Microelectronics, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089","https://openalex.org/I4210119392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086894201","display_name":"Peng Ouyang","orcid":"https://orcid.org/0000-0001-6598-3472"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Ouyang","raw_affiliation_strings":["Institute of Microelectronics, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089","https://openalex.org/I4210119392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038947607","display_name":"Fengbin Tu","orcid":"https://orcid.org/0000-0003-2228-8829"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengbin Tu","raw_affiliation_strings":["Institute of Microelectronics, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089","https://openalex.org/I4210119392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101630686","display_name":"Shibin Tang","orcid":"https://orcid.org/0000-0002-7560-2239"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shibin Tang","raw_affiliation_strings":["Institute of Microelectronics, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089","https://openalex.org/I4210119392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100358856","display_name":"Leibo Liu","orcid":"https://orcid.org/0000-0001-7548-4116"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leibo Liu","raw_affiliation_strings":["Institute of Microelectronics, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089","https://openalex.org/I4210119392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036023084","display_name":"Shaojun Wei","orcid":"https://orcid.org/0000-0001-5117-7920"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaojun Wei","raw_affiliation_strings":["Institute of Microelectronics, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089","https://openalex.org/I4210119392"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9969000220298767,"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/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.8591325283050537},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8402377367019653},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8129128217697144},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5917907357215881},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.5511212348937988},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5106831192970276},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.44784465432167053},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.38594114780426025},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.38063549995422363},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3780078589916229},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.37184518575668335},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.36174893379211426},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.33013156056404114},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2569035291671753}],"concepts":[{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.8591325283050537},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8402377367019653},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8129128217697144},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5917907357215881},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.5511212348937988},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5106831192970276},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.44784465432167053},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.38594114780426025},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.38063549995422363},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3780078589916229},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.37184518575668335},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.36174893379211426},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.33013156056404114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2569035291671753},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iscas.2018.8351666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2018.8351666","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-153866","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-153866","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W16066432","https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W2016053056","https://openalex.org/W2094756095","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2246760854","https://openalex.org/W2276486856","https://openalex.org/W2395566064","https://openalex.org/W2524802307","https://openalex.org/W2563587242","https://openalex.org/W2962835968","https://openalex.org/W4247198796","https://openalex.org/W4299322810","https://openalex.org/W6637373629","https://openalex.org/W6639204139","https://openalex.org/W6684191040","https://openalex.org/W6711716804"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W2355315220","https://openalex.org/W3034421924","https://openalex.org/W2982536526","https://openalex.org/W4386858688","https://openalex.org/W4380302312","https://openalex.org/W3008689640","https://openalex.org/W4390971171","https://openalex.org/W4385338604","https://openalex.org/W3081626085"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4,15],"achieved":[5],"great":[6],"success":[7],"in":[8,48,74,90],"many":[9],"applications.":[10],"Recently,":[11],"various":[12,71],"FPGA-based":[13,27,124],"accelerators":[14,126],"been":[16],"proposed":[17],"to":[18,41,66,85,104,129],"improve":[19],"the":[20,31,67,87,95,106,122,139],"performance":[21,50],"of":[22,142],"CNNs.":[23,147],"However,":[24],"current":[25],"most":[26],"methods":[28],"only":[29],"use":[30,100],"same":[32,76],"bit-width":[33,58,72,82],"selection":[34],"for":[35],"all":[36],"CNN":[37,68,88,125],"layers":[38,69,89,141],"which":[39,63],"lead":[40],"very":[42],"low":[43],"resource":[44,108],"utilization":[45],"and":[46,99,131,144],"difficulty":[47],"further":[49],"improvement.":[51],"In":[52],"this":[53],"paper,":[54],"we":[55,137],"propose":[56],"a":[57,75,111],"adaptive":[59],"accelerator":[60],"design":[61,116],"approach":[62,103,117],"can":[64],"adapt":[65],"with":[70],"requirements":[73],"network.":[77],"We":[78,93],"construct":[79],"multiple":[80],"different":[81],"convolutional":[83,140],"processors":[84],"compute":[86],"parallel":[91],"way.":[92],"partition":[94],"FPGA":[96],"DSP":[97],"resources":[98],"our":[101,115],"optimization":[102],"find":[105],"optimal":[107],"allocation.":[109],"On":[110],"Xilinx":[112],"Virtex-7":[113],"FPGA,":[114],"achieves":[118],"higher":[119],"throughput":[120],"than":[121],"state-of-the-art":[123],"from":[127],"5.48\u00d7":[128],"7.25\u00d7":[130],"by":[132],"6.20\u00d7":[133],"on":[134],"average,":[135],"when":[136],"evaluate":[138],"AlexNet":[143],"deeper":[145],"VGG":[146]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}