{"id":"https://openalex.org/W3174657316","doi":"https://doi.org/10.1145/3456126.3456140","title":"Efficient LUT-based FPGA Accelerator Design for Universal Quantized CNN Inference","display_name":"Efficient LUT-based FPGA Accelerator Design for Universal Quantized CNN Inference","publication_year":2021,"publication_date":"2021-02-24","ids":{"openalex":"https://openalex.org/W3174657316","doi":"https://doi.org/10.1145/3456126.3456140","mag":"3174657316"},"language":"en","primary_location":{"id":"doi:10.1145/3456126.3456140","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3456126.3456140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 2nd Asia Service Sciences and Software Engineering Conference","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/A5100627571","display_name":"Yanpeng Cao","orcid":"https://orcid.org/0000-0002-8620-480X"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanpeng Cao","raw_affiliation_strings":["Southeast University, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037540218","display_name":"Changjun Song","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changjun Song","raw_affiliation_strings":["Southeast University, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072235807","display_name":"Yongming Tang","orcid":"https://orcid.org/0000-0003-2102-2041"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongming Tang","raw_affiliation_strings":["Southeast University, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100627571"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":0.2882,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.54635621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"108","last_page":"115"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9986000061035156,"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":0.9986000061035156,"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":0.9975000023841858,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9966999888420105,"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":0.8124073147773743},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.6982072591781616},{"id":"https://openalex.org/keywords/lookup-table","display_name":"Lookup table","score":0.6104135513305664},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5900176763534546},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5869589447975159},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.570379912853241},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5675420165061951},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.5550310611724854},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5290321707725525},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5094147324562073},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.49085837602615356},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4713670015335083},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4402032196521759},{"id":"https://openalex.org/keywords/floating-point","display_name":"Floating point","score":0.4241673946380615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3770316243171692},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.36441391706466675},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33738774061203003},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3042675852775574},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20935288071632385},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09376347064971924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8124073147773743},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.6982072591781616},{"id":"https://openalex.org/C134835016","wikidata":"https://www.wikidata.org/wiki/Q690265","display_name":"Lookup table","level":2,"score":0.6104135513305664},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5900176763534546},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5869589447975159},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.570379912853241},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5675420165061951},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.5550310611724854},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5290321707725525},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5094147324562073},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.49085837602615356},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4713670015335083},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4402032196521759},{"id":"https://openalex.org/C84211073","wikidata":"https://www.wikidata.org/wiki/Q117879","display_name":"Floating point","level":2,"score":0.4241673946380615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3770316243171692},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.36441391706466675},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33738774061203003},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3042675852775574},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20935288071632385},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09376347064971924}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3456126.3456140","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3456126.3456140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 2nd Asia Service Sciences and Software Engineering Conference","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":9,"referenced_works":["https://openalex.org/W2033372705","https://openalex.org/W2110452354","https://openalex.org/W2132916570","https://openalex.org/W2160284536","https://openalex.org/W2172654076","https://openalex.org/W2531409750","https://openalex.org/W2548916103","https://openalex.org/W3140847110","https://openalex.org/W6685214006"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1001352512","https://openalex.org/W1989889224","https://openalex.org/W4382618745","https://openalex.org/W1973775000","https://openalex.org/W2748922771","https://openalex.org/W2586397364"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"has":[2,29,45],"achieved":[3],"remarkable":[4],"success":[5],"in":[6,11,37],"a":[7],"variety":[8],"of":[9,24,33,70,96],"tasks":[10],"real":[12],"life,":[13],"such":[14],"as":[15],"speech":[16],"and":[17,59,80],"vision.":[18],"However,":[19],"the":[20,31,34,53,63,67,71,94],"vast":[21],"computational":[22,68],"complexity":[23,69],"convolution":[25],"neural":[26,87],"networks":[27,88],"(CNN)":[28],"limited":[30],"speed":[32],"network":[35,42,51,72],"running":[36],"hardware.":[38],"In":[39],"recent":[40],"years,":[41],"quantization":[43],"technology":[44],"made":[46],"it":[47],"possible":[48],"to":[49,92],"quantize":[50],"into":[52],"16-bit":[54],"fixed":[55],"point,":[56],"8-bit":[57],"integer,":[58],"even":[60],"binary,":[61],"maintaining":[62],"original":[64],"performance,":[65],"while":[66],"inference":[73],"is":[74,90],"still":[75],"considerable.":[76],"Therefore,":[77],"exploring":[78],"high-performance":[79],"efficient":[81],"hardware":[82],"architecture":[83],"designed":[84],"for":[85],"quantized":[86],"(QNN)":[89],"necessary":[91],"eliminate":[93],"bottleneck":[95],"high-density":[97],"computing":[98],"requirements.":[99]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}