{"id":"https://openalex.org/W2788181042","doi":"https://doi.org/10.1145/3174243.3174983","title":"Software-Defined FPGA-Based Accelerator for Deep Convolutional Neural Networks","display_name":"Software-Defined FPGA-Based Accelerator for Deep Convolutional Neural Networks","publication_year":2018,"publication_date":"2018-02-15","ids":{"openalex":"https://openalex.org/W2788181042","doi":"https://doi.org/10.1145/3174243.3174983","mag":"2788181042"},"language":"en","primary_location":{"id":"doi:10.1145/3174243.3174983","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3174243.3174983","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","raw_type":"proceedings-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/A5090097235","display_name":"Yankang Du","orcid":"https://orcid.org/0000-0002-2583-2802"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yankang Du","raw_affiliation_strings":["National Digital Switching System Engineering & Technology Research Center, ZhengZhou, China"],"affiliations":[{"raw_affiliation_string":"National Digital Switching System Engineering & Technology Research Center, ZhengZhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041609414","display_name":"Qinrang Liu","orcid":"https://orcid.org/0000-0002-9553-2282"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qinrang Liu","raw_affiliation_strings":["National Digital Switching System Engineering & Technology Research Center, ZhengZhou, China"],"affiliations":[{"raw_affiliation_string":"National Digital Switching System Engineering & Technology Research Center, ZhengZhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068681986","display_name":"Shuai Wei","orcid":"https://orcid.org/0000-0001-9564-6055"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuai Wei","raw_affiliation_strings":["National Digital Switching System Engineering & Technology Research Center, ZhengZhou, China"],"affiliations":[{"raw_affiliation_string":"National Digital Switching System Engineering & Technology Research Center, ZhengZhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005759434","display_name":"Chen Gao","orcid":"https://orcid.org/0000-0001-8700-1409"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen Gao","raw_affiliation_strings":["National Digital Switching System Engineering & Technology Research Center, ZhengZhou, China"],"affiliations":[{"raw_affiliation_string":"National Digital Switching System Engineering & Technology Research Center, ZhengZhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5090097235"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01039175,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"291","last_page":"291"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9991999864578247,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9947999715805054,"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/computer-science","display_name":"Computer science","score":0.8675914406776428},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8049643635749817},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.6843507289886475},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.5776907801628113},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.5728004574775696},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.5563765168190002},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5081677436828613},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.48430123925209045},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4582589864730835},{"id":"https://openalex.org/keywords/memory-bandwidth","display_name":"Memory bandwidth","score":0.4377155303955078},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.4012737274169922},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.37648433446884155},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.37338435649871826},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2724215090274811},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.2006838321685791},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.10832822322845459}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8675914406776428},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8049643635749817},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.6843507289886475},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5776907801628113},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.5728004574775696},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.5563765168190002},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5081677436828613},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.48430123925209045},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4582589864730835},{"id":"https://openalex.org/C188045654","wikidata":"https://www.wikidata.org/wiki/Q17148339","display_name":"Memory bandwidth","level":2,"score":0.4377155303955078},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.4012737274169922},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.37648433446884155},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.37338435649871826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2724215090274811},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.2006838321685791},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.10832822322845459}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3174243.3174983","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3174243.3174983","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","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":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1995562189","https://openalex.org/W2002555321","https://openalex.org/W2016053056","https://openalex.org/W2048266589","https://openalex.org/W2094756095","https://openalex.org/W2102605133","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2276486856","https://openalex.org/W2294282016","https://openalex.org/W2442974303","https://openalex.org/W2475840367","https://openalex.org/W2513568085","https://openalex.org/W2525740295","https://openalex.org/W2584311934","https://openalex.org/W2584616277","https://openalex.org/W2594492285","https://openalex.org/W2618530766","https://openalex.org/W2906043559","https://openalex.org/W6601968593","https://openalex.org/W6819060087"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W2355315220","https://openalex.org/W2518118925","https://openalex.org/W3159273459","https://openalex.org/W4319952061","https://openalex.org/W4280636456","https://openalex.org/W4388913998","https://openalex.org/W4310584535","https://openalex.org/W4295935044","https://openalex.org/W3159906349"],"abstract_inverted_index":{"Now,":[0],"Convolutional":[1],"Neural":[2],"Network":[3],"(CNN)":[4],"has":[5,195,209,216],"gained":[6],"great":[7,72,218],"popularity.":[8],"Intensive":[9],"computation":[10],"and":[11,59,149,155],"huge":[12],"external":[13],"data":[14,123,146,212],"access":[15,147,213],"amount":[16,148,214],"are":[17,106],"two":[18],"challenged":[19],"factors":[20],"for":[21,64,74,152,158],"the":[22,27,42,62,65,75,102,110,116,121,130,138,150,153,156,159,164,168,183,189,196,221],"hardware":[23,96],"acceleration.":[24],"Besides":[25,204],"these,":[26],"ability":[28],"to":[29,85,101,108,126,179,188],"deal":[30,50],"with":[31,51,87],"various":[32],"CNN":[33,45,53,67,89],"models":[34,54,90],"is":[35],"also":[36,208],"challenged.":[37],"At":[38],"present,":[39],"most":[40],"of":[41,112,167],"proposed":[43,107,120],"FPGA-based":[44],"accelerator":[46,194,207],"either":[47],"can":[48,97,132,176],"only":[49,134],"specific":[52],"or":[55],"should":[56],"be":[57,98,133,177,180],"re-coded":[58],"re-download":[60],"on":[61,220],"FPGA":[63],"different":[66,88],"models.":[68],"This":[69,141],"would":[70],"bring":[71],"trouble":[73],"developers.":[76],"In":[77],"this":[78],"paper,":[79],"we":[80,119],"designed":[81],"a":[82,217],"software-defined":[83,122,193],"architecture":[84],"cope":[86],"while":[91,199],"keeping":[92,200],"high":[93,202],"throughput.":[94],"The":[95],"programmed":[99],"according":[100],"requirement.":[103],"Several":[104],"techniques":[105],"optimize":[109],"performance":[111],"our":[113,192,206],"accelerators.":[114],"For":[115],"convolutional":[117],"layer,":[118],"reuse":[124],"technique":[125],"ensure":[127],"that":[128],"all":[129],"parameters":[131,175],"loaded":[135,181],"once":[136],"during":[137],"computing":[139],"phase.":[140],"will":[142],"reduce":[143],"large":[144],"off-chip":[145,211],"need":[151,157],"memory":[154,160],"bandwidth.":[161],"By":[162],"using":[163],"sparse":[165],"property":[166],"input":[169],"feature":[170],"map,":[171],"almost":[172],"80%":[173],"weight":[174],"skipped":[178],"in":[182],"full-connected":[184],"(FC)":[185],"layer.":[186],"Compared":[187],"previous":[190],"works,":[191],"highest":[197],"flexibility":[198],"relative":[201],"throughout.":[203],"this,":[205],"lower":[210],"which":[215],"effect":[219],"power":[222],"consumption.":[223]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}