{"id":"https://openalex.org/W3010819965","doi":"https://doi.org/10.1145/3380548","title":"FFConv","display_name":"FFConv","publication_year":2020,"publication_date":"2020-03-11","ids":{"openalex":"https://openalex.org/W3010819965","doi":"https://doi.org/10.1145/3380548","mag":"3010819965"},"language":"en","primary_location":{"id":"doi:10.1145/3380548","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3380548","pdf_url":null,"source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","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/A5060826708","display_name":"Afzal Ahmad","orcid":"https://orcid.org/0000-0003-4491-5440"},"institutions":[{"id":"https://openalex.org/I207789805","display_name":"Lahore University of Management Sciences","ror":"https://ror.org/05b5x4a35","country_code":"PK","type":"education","lineage":["https://openalex.org/I207789805"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Afzal Ahmad","raw_affiliation_strings":["Lahore University of Management Sciences (LUMS), Lahore, Pakistan"],"raw_orcid":"https://orcid.org/0000-0003-4491-5440","affiliations":[{"raw_affiliation_string":"Lahore University of Management Sciences (LUMS), Lahore, Pakistan","institution_ids":["https://openalex.org/I207789805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069432255","display_name":"Muhammad Adeel Pasha","orcid":"https://orcid.org/0000-0001-9892-5201"},"institutions":[{"id":"https://openalex.org/I207789805","display_name":"Lahore University of Management Sciences","ror":"https://ror.org/05b5x4a35","country_code":"PK","type":"education","lineage":["https://openalex.org/I207789805"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Adeel Pasha","raw_affiliation_strings":["Lahore University of Management Sciences (LUMS), Lahore, Pakistan"],"raw_orcid":"https://orcid.org/0000-0001-9892-5201","affiliations":[{"raw_affiliation_string":"Lahore University of Management Sciences (LUMS), Lahore, Pakistan","institution_ids":["https://openalex.org/I207789805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I207789805"],"apc_list":null,"apc_paid":null,"fwci":1.5663,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.85254257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"19","issue":"2","first_page":"1","last_page":"24"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9972000122070312,"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":0.8894566297531128},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.7532018423080444},{"id":"https://openalex.org/keywords/massively-parallel","display_name":"Massively parallel","score":0.7047152519226074},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6216402649879456},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5986944437026978},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.5764381289482117},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4927683174610138},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.45506852865219116},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4523705542087555},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3860846757888794},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3423570394515991},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3278385400772095},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19653072953224182},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.12114137411117554}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8894566297531128},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.7532018423080444},{"id":"https://openalex.org/C190475519","wikidata":"https://www.wikidata.org/wiki/Q544384","display_name":"Massively parallel","level":2,"score":0.7047152519226074},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6216402649879456},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5986944437026978},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.5764381289482117},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4927683174610138},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.45506852865219116},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4523705542087555},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3860846757888794},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3423570394515991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3278385400772095},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19653072953224182},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.12114137411117554},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3380548","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3380548","pdf_url":null,"source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1005811612","https://openalex.org/W1487564550","https://openalex.org/W2002555321","https://openalex.org/W2094756095","https://openalex.org/W2097117768","https://openalex.org/W2172654076","https://openalex.org/W2183182206","https://openalex.org/W2194775991","https://openalex.org/W2233116163","https://openalex.org/W2276486856","https://openalex.org/W2294282016","https://openalex.org/W2585560244","https://openalex.org/W2585774018","https://openalex.org/W2586654419","https://openalex.org/W2602816542","https://openalex.org/W2618530766","https://openalex.org/W2790167166","https://openalex.org/W2903688003","https://openalex.org/W2907579173","https://openalex.org/W2963125010","https://openalex.org/W4387007199"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W1970433854","https://openalex.org/W4200391368","https://openalex.org/W2355315220","https://openalex.org/W2210979487","https://openalex.org/W2023867642","https://openalex.org/W2074043759","https://openalex.org/W1905852083","https://openalex.org/W575709247","https://openalex.org/W2373535795"],"abstract_inverted_index":{"Image":[0],"classification":[1,228],"is":[2,20],"known":[3],"to":[4,44,87,94,125,208,245],"be":[5],"one":[6],"of":[7,15,65,98,184],"the":[8,13,63,105,170,181,205,209],"most":[9],"challenging":[10],"problems":[11,49],"in":[12],"domain":[14],"computer":[16],"vision.":[17],"Significant":[18],"research":[19],"being":[21,123],"done":[22],"on":[23,169,197],"developing":[24],"systems":[25],"and":[26,32,56,114,191,225,233,241],"algorithms":[27,178],"improving":[28,216,238],"accuracy,":[29],"performance,":[30],"area,":[31],"power":[33,112,142,242],"consumption":[34,113,143],"for":[35,48,76,159,179,230],"related":[36],"problems.":[37],"Convolutional":[38],"Neural":[39],"Networks":[40],"(CNNs)":[41],"have":[42,92],"shown":[43,93],"give":[45,95],"outstanding":[46],"accuracies":[47],"such":[50],"as":[51,129],"image":[52],"classification,":[53],"object":[54],"detection,":[55],"semantic":[57],"segmentation.":[58],"While":[59],"CNNs":[60],"are":[61,107,122],"pioneering":[62],"development":[64],"high":[66,111],"accuracy":[67,229],"systems,":[68],"their":[69,88,110],"excessive":[70],"computational":[71,206],"complexity":[72],"presents":[73],"a":[74,77,139,163,198],"barrier":[75],"more":[78],"permeated":[79],"deployment.":[80],"Although":[81],"Graphical":[82],"Processing":[83],"Units":[84],"(GPUs),":[85],"due":[86],"massively":[89,133],"parallel":[90,134],"architecture,":[91],"performance":[96],"orders":[97],"magnitude":[99],"better":[100],"than":[101,144],"general":[102],"purpose":[103],"processors,":[104],"former":[106],"limited":[108],"by":[109],"generality.":[115],"Consequently,":[116],"Field":[117],"Programmable":[118],"Gate":[119],"Arrays":[120],"(FPGAs)":[121],"explored":[124],"implement":[126,194],"CNN":[127,187],"architectures,":[128],"they":[130],"also":[131],"provide":[132],"logic":[135],"resources":[136],"but":[137],"with":[138],"relatively":[140],"lower":[141],"GPUs.":[145],"In":[146],"this":[147],"article,":[148],"we":[149,203],"present":[150],"FFConv,":[151],"an":[152],"efficient":[153],"FPGA-based":[154],"fast":[155],"convolutional":[156,182],"layer":[157],"accelerator":[158,196],"CNNs.":[160],"We":[161,193],"design":[162,220],"pipelined,":[164],"high-throughput":[165],"convolution":[166],"engine":[167],"based":[168],"Winograd":[171],"minimal":[172],"filtering":[173],"(also":[174],"called":[175],"Fast":[176],"Convolution)":[177],"computing":[180],"layers":[183],"three":[185],"popular":[186],"architectures:":[188],"VGG16,":[189,231],"Alexnet,":[190,232],"Shufflenet.":[192],"our":[195],"Virtex-7":[199],"FPGA":[200],"platform":[201],"where":[202],"exploit":[204],"parallelization":[207],"maximum":[210],"while":[211,236],"exploring":[212],"optimizations":[213],"aimed":[214],"at":[215],"performance.":[217],"The":[218],"resultant":[219],"loses":[221],"only":[222],"0.43%,":[223],"0.47%,":[224],"0.61%":[226],"Top-1":[227],"Shufflenet-v1,":[234],"respectively,":[235],"significantly":[237],"throughput,":[239],"resource,":[240],"efficiency":[243],"compared":[244],"previous":[246],"state-of-the-art":[247],"designs.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2020-03-23T00:00:00"}
