{"id":"https://openalex.org/W2742152118","doi":"https://doi.org/10.1109/asap.2017.7995253","title":"Fast and efficient implementation of Convolutional Neural Networks on FPGA","display_name":"Fast and efficient implementation of Convolutional Neural Networks on FPGA","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2742152118","doi":"https://doi.org/10.1109/asap.2017.7995253","mag":"2742152118"},"language":"en","primary_location":{"id":"doi:10.1109/asap.2017.7995253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asap.2017.7995253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP)","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/A5028852213","display_name":"Abhinav Podili","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abhinav Podili","raw_affiliation_strings":["Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA","Ming Hsieh Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Ming Hsieh Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100458134","display_name":"Chi Zhang","orcid":"https://orcid.org/0000-0001-7374-1940"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chi Zhang","raw_affiliation_strings":["Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA","Ming Hsieh Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Ming Hsieh Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033166029","display_name":"Viktor K. Prasanna","orcid":"https://orcid.org/0000-0002-1609-8589"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Viktor Prasanna","raw_affiliation_strings":["Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA","Ming Hsieh Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Ming Hsieh Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028852213"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":3.6409,"has_fulltext":false,"cited_by_count":76,"citation_normalized_percentile":{"value":0.9599822,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"11","last_page":"18"},"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":0.998199999332428,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9941999912261963,"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/computer-science","display_name":"Computer science","score":0.7905234098434448},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7525728940963745},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6511037945747375},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.6338744759559631},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.6147913336753845},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6006171107292175},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5899558663368225},{"id":"https://openalex.org/keywords/memory-bandwidth","display_name":"Memory bandwidth","score":0.5237545967102051},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5162346363067627},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.44803664088249207},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.43289950489997864},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3770730793476105},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36632204055786133},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.33972281217575073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3004207909107208},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2865719199180603},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11811360716819763}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7905234098434448},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7525728940963745},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6511037945747375},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.6338744759559631},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.6147913336753845},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6006171107292175},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5899558663368225},{"id":"https://openalex.org/C188045654","wikidata":"https://www.wikidata.org/wiki/Q17148339","display_name":"Memory bandwidth","level":2,"score":0.5237545967102051},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5162346363067627},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.44803664088249207},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.43289950489997864},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3770730793476105},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36632204055786133},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.33972281217575073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3004207909107208},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2865719199180603},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11811360716819763},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asap.2017.7995253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asap.2017.7995253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1487564550","https://openalex.org/W1686810756","https://openalex.org/W1752712236","https://openalex.org/W1922123711","https://openalex.org/W1995562189","https://openalex.org/W2025265972","https://openalex.org/W2094756095","https://openalex.org/W2097117768","https://openalex.org/W2144172034","https://openalex.org/W2163605009","https://openalex.org/W2172654076","https://openalex.org/W2255738257","https://openalex.org/W2276486856","https://openalex.org/W2279098554","https://openalex.org/W2294282016","https://openalex.org/W2584616277","https://openalex.org/W2949245006","https://openalex.org/W2950179405","https://openalex.org/W2952309299","https://openalex.org/W2962835968","https://openalex.org/W2962987932","https://openalex.org/W4300234771","https://openalex.org/W6637373629","https://openalex.org/W6640442106","https://openalex.org/W6674914833","https://openalex.org/W6681239517","https://openalex.org/W6684191040","https://openalex.org/W6685214006","https://openalex.org/W6691901705","https://openalex.org/W6694717790","https://openalex.org/W6695314431","https://openalex.org/W6697189835","https://openalex.org/W6732622633"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W3211292372","https://openalex.org/W803346624"],"abstract_inverted_index":{"State-of-the-art":[0],"CNN":[1,43,140],"models":[2,44],"for":[3,66],"Image":[4],"recognition":[5],"use":[6],"deep":[7],"networks":[8,15],"with":[9,16,145,149,196],"small":[10,46],"filters":[11],"instead":[12],"of":[13,28,60,73,93,109,117,129],"shallow":[14],"large":[17],"filters,":[18],"because":[19],"the":[20,26,58,71,74,80,90,94,105,126,130,150,175,197],"former":[21],"requires":[22],"fewer":[23],"weights.":[24],"In":[25],"light":[27],"above":[29],"trend,":[30],"we":[31,137],"present":[32],"a":[33,99,134],"fast":[34],"and":[35,142,168,184,192],"efficient":[36],"FPGA":[37],"based":[38],"convolution":[39,49,76,95,120],"engine":[40,50,77,121],"to":[41,56,64,78,103],"accelerate":[42],"over":[45],"filters.":[47],"The":[48,178],"implements":[51],"Winograd":[52,75,119],"minimal":[53],"filtering":[54],"algorithm":[55],"reduce":[57,104],"number":[59],"multiplications":[61],"by":[62,112,163],"38%":[63],"55%":[65],"state-of-the-art":[67,151,198],"CNNs.":[68],"We":[69,83,97],"exploit":[70],"parallelism":[72],"scale":[79],"overall":[81,87],"performance.":[82],"show":[84],"that":[85,123],"our":[86,110,118,156],"design":[88,111],"sustains":[89],"peak":[91],"throughput":[92,162,181,185],"engines.":[96],"propose":[98],"novel":[100],"data":[101],"layout":[102],"required":[106],"memory":[107,172,189],"bandwidth":[108],"half.":[113],"One":[114],"noteworthy":[115],"feature":[116],"is":[122],"it":[124,144],"hides":[125],"computation":[127],"latency":[128],"pooling":[131],"layer.":[132],"As":[133],"case":[135],"study":[136],"implement":[138],"VGG16":[139,154],"model":[141],"compare":[143],"previous":[146],"approaches.":[147],"Compared":[148],"reduced":[152],"precision":[153],"implementation,":[155],"implementation":[157],"achieves":[158],"1.2\u00d7":[159],"improvement":[160],"in":[161,180],"using":[164],"3\u00d7":[165],"less":[166,170],"multipliers":[167],"2\u00d7":[169],"on-chip":[171,188],"without":[173],"impacting":[174],"classification":[176],"accuracy.":[177],"improvements":[179],"per":[182,186],"multiplier":[183],"unit":[187],"are":[190],"3.7\u00d7":[191],"2.47\u00d7":[193],"respectively,":[194],"compared":[195],"design.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}