{"id":"https://openalex.org/W4386259200","doi":"https://doi.org/10.1109/icsse58758.2023.10227155","title":"in-Memory Processing to Accelerate Convolutional Neural Networks","display_name":"in-Memory Processing to Accelerate Convolutional Neural Networks","publication_year":2023,"publication_date":"2023-07-27","ids":{"openalex":"https://openalex.org/W4386259200","doi":"https://doi.org/10.1109/icsse58758.2023.10227155"},"language":"en","primary_location":{"id":"doi:10.1109/icsse58758.2023.10227155","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icsse58758.2023.10227155","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on System Science and Engineering (ICSSE)","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/A5101238751","display_name":"Van - Khoa Pham","orcid":null},"institutions":[{"id":"https://openalex.org/I228151691","display_name":"Ho Chi Minh City International University","ror":"https://ror.org/003szmg30","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023","https://openalex.org/I228151691"]},{"id":"https://openalex.org/I4210148201","display_name":"Ho Chi Minh City University of Technology and Education","ror":"https://ror.org/05hzn5427","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210148201"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Van - Khoa Pham","raw_affiliation_strings":["Ho Chi Minh City University of Technology and Education,Faculty of International Education,Ho Chi Minh City,Vietnam","Faculty of International Education, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Vietnam"],"affiliations":[{"raw_affiliation_string":"Ho Chi Minh City University of Technology and Education,Faculty of International Education,Ho Chi Minh City,Vietnam","institution_ids":["https://openalex.org/I4210148201","https://openalex.org/I228151691"]},{"raw_affiliation_string":"Faculty of International Education, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Vietnam","institution_ids":["https://openalex.org/I4210148201"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101238751"],"corresponding_institution_ids":["https://openalex.org/I228151691","https://openalex.org/I4210148201"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09080669,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"521","issue":null,"first_page":"28","last_page":"32"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8446889519691467},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.6780103445053101},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6768168210983276},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5463789105415344},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5403239727020264},{"id":"https://openalex.org/keywords/dram","display_name":"Dram","score":0.5145015716552734},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.5079415440559387},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.48287633061408997},{"id":"https://openalex.org/keywords/multiplier","display_name":"Multiplier (economics)","score":0.4168448746204376},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4136728346347809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3963727653026581},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.29851675033569336},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1873280107975006}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8446889519691467},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.6780103445053101},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6768168210983276},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5463789105415344},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5403239727020264},{"id":"https://openalex.org/C7366592","wikidata":"https://www.wikidata.org/wiki/Q1255620","display_name":"Dram","level":2,"score":0.5145015716552734},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.5079415440559387},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.48287633061408997},{"id":"https://openalex.org/C124584101","wikidata":"https://www.wikidata.org/wiki/Q1053266","display_name":"Multiplier (economics)","level":2,"score":0.4168448746204376},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4136728346347809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3963727653026581},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.29851675033569336},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1873280107975006},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsse58758.2023.10227155","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icsse58758.2023.10227155","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on System Science and Engineering (ICSSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1531789256","https://openalex.org/W2013305145","https://openalex.org/W2112796928","https://openalex.org/W2194775991","https://openalex.org/W2233116163","https://openalex.org/W2300242332","https://openalex.org/W2524428287","https://openalex.org/W2578887236","https://openalex.org/W2583383421","https://openalex.org/W2591922920","https://openalex.org/W2761919306","https://openalex.org/W2900162849","https://openalex.org/W2919115771","https://openalex.org/W2952797486","https://openalex.org/W3008515144","https://openalex.org/W6631772083","https://openalex.org/W6687483927","https://openalex.org/W6727208969"],"related_works":["https://openalex.org/W3120961607","https://openalex.org/W4401568740","https://openalex.org/W2098207691","https://openalex.org/W3148568549","https://openalex.org/W1648516568","https://openalex.org/W361036515","https://openalex.org/W2269474412","https://openalex.org/W2929170389","https://openalex.org/W4300097863","https://openalex.org/W2950268673"],"abstract_inverted_index":{"In":[0,29,131],"artificial":[1],"neural":[2,6,129],"network":[3],"applications,":[4],"convolutional":[5],"networks":[7],"(CNNs),":[8],"compared":[9],"to":[10,63,108,121,133],"conventional":[11,135],"fully":[12],"connected":[13],"networks,":[14],"significantly":[15,161],"reduce":[16,162],"the":[17,93,99,110,118,123,127,134,147,152,163],"number":[18,164],"of":[19,38,80,126,137,165],"trained":[20,50,128],"synaptic":[21],"weights":[22,51],"by":[23],"stacking":[24],"many":[25,54],"convolution":[26],"layers":[27,69],"sequentially.":[28],"addition,":[30],"CNNs":[31],"outperform":[32],"a":[33,46,86,157],"fully-connected":[34],"approach":[35,97],"in":[36,53,105],"terms":[37],"accuracy.":[39],"However,":[40],"these":[41,68],"advantages":[42],"only":[43],"come":[44],"for":[45],"fee":[47],"because":[48,79],"sharing":[49],"results":[52,149],"computation-intensive":[55],"operations.":[56],"With":[57],"practical":[58],"applications":[59],"using":[60,98],"resource-constraint":[61],"hardware":[62,84],"process":[64],"large-scale":[65],"input":[66],"images,":[67],"consume":[70],"much":[71],"more":[72],"computing":[73],"time":[74],"as":[75,77,168],"well":[76],"power":[78],"utilizing":[81],"massive":[82],"complexity":[83],"and":[85,160],"large":[87],"memory":[88,139],"footprint.":[89],"To":[90],"deal":[91],"with":[92,117,140],"challenge,":[94],"an":[95],"alternative":[96],"in-DRAM":[100],"processing":[101,141],"concept":[102],"is":[103],"proposed":[104,153],"this":[106],"study":[107],"avoid":[109],"multiplier":[111],"operation.":[112],"The":[113],"design":[114],"was":[115],"tested":[116],"GTSRB":[119],"dataset":[120],"verify":[122],"recognition":[124],"performance":[125,159],"network.":[130],"comparison":[132],"combination":[136],"main":[138],"chips":[142],"on":[143],"Von-Neumann":[144],"computer":[145],"architectures,":[146],"simulation":[148],"indicate":[150],"that":[151],"circuit":[154],"can":[155],"achieve":[156],"competitive":[158],"computation":[166],"cycles":[167],"well.":[169]},"counts_by_year":[],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}
