{"id":"https://openalex.org/W4388052862","doi":"https://doi.org/10.1109/jetcas.2023.3328864","title":"Benchmarking DNN Mapping Methods for the in-Memory Computing Accelerators","display_name":"Benchmarking DNN Mapping Methods for the in-Memory Computing Accelerators","publication_year":2023,"publication_date":"2023-10-31","ids":{"openalex":"https://openalex.org/W4388052862","doi":"https://doi.org/10.1109/jetcas.2023.3328864"},"language":"en","primary_location":{"id":"doi:10.1109/jetcas.2023.3328864","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jetcas.2023.3328864","pdf_url":null,"source":{"id":"https://openalex.org/S142323794","display_name":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","issn_l":"2156-3357","issn":["2156-3357","2156-3365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal on Emerging and Selected Topics in Circuits and 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/A5100384240","display_name":"Yi\u2010Min Wang","orcid":"https://orcid.org/0009-0008-7292-0670"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yimin Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore"],"raw_orcid":"https://orcid.org/0009-0008-7292-0670","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085588788","display_name":"Xuanyao Fong","orcid":"https://orcid.org/0000-0001-5939-7389"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xuanyao Fong","raw_affiliation_strings":["Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-5939-7389","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":0.8487,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.73447326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"13","issue":"4","first_page":"1040","last_page":"1051"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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":1.0,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9997000098228455,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9955000281333923,"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":0.8391274809837341},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.7783633470535278},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.6372684836387634},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6148005723953247},{"id":"https://openalex.org/keywords/memory-bandwidth","display_name":"Memory bandwidth","score":0.5925611257553101},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.5105558633804321},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.5041142702102661},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4918367862701416},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4481911063194275},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4321724474430084},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4180937707424164},{"id":"https://openalex.org/keywords/design-space-exploration","display_name":"Design space exploration","score":0.41255974769592285},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.41038933396339417},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.38979148864746094},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3674706816673279},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3606764078140259},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21716299653053284},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.11810269951820374}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8391274809837341},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7783633470535278},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.6372684836387634},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6148005723953247},{"id":"https://openalex.org/C188045654","wikidata":"https://www.wikidata.org/wiki/Q17148339","display_name":"Memory bandwidth","level":2,"score":0.5925611257553101},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.5105558633804321},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.5041142702102661},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4918367862701416},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4481911063194275},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4321724474430084},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4180937707424164},{"id":"https://openalex.org/C2776221188","wikidata":"https://www.wikidata.org/wiki/Q21072556","display_name":"Design space exploration","level":2,"score":0.41255974769592285},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.41038933396339417},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.38979148864746094},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3674706816673279},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3606764078140259},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21716299653053284},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.11810269951820374},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","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},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/jetcas.2023.3328864","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jetcas.2023.3328864","pdf_url":null,"source":{"id":"https://openalex.org/S142323794","display_name":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","issn_l":"2156-3357","issn":["2156-3357","2156-3365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","raw_type":"journal-article"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/245817","is_oa":false,"landing_page_url":"https://scholarbank.nus.edu.sg/handle/10635/245817","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Elements","raw_type":"Article"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/249160","is_oa":false,"landing_page_url":"https://scholarbank.nus.edu.sg/handle/10635/249160","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2413778509","display_name":null,"funder_award_id":"NRF-CRP24-2020-0003","funder_id":"https://openalex.org/F4320320709","funder_display_name":"National Research Foundation Singapore"},{"id":"https://openalex.org/G5155372924","display_name":null,"funder_award_id":"A18A6b0057","funder_id":"https://openalex.org/F4320320696","funder_display_name":"Agency for Science, Technology and Research"}],"funders":[{"id":"https://openalex.org/F4320320696","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09"},{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2120000030","https://openalex.org/W2782046614","https://openalex.org/W2792893539","https://openalex.org/W2913104037","https://openalex.org/W2922487710","https://openalex.org/W2925935411","https://openalex.org/W2944898315","https://openalex.org/W2945146780","https://openalex.org/W2969812992","https://openalex.org/W2980200167","https://openalex.org/W2997869757","https://openalex.org/W3003821665","https://openalex.org/W3016014942","https://openalex.org/W3049586678","https://openalex.org/W3112740243","https://openalex.org/W3128246765","https://openalex.org/W3132942233","https://openalex.org/W3133754064","https://openalex.org/W3134195144","https://openalex.org/W3135835558","https://openalex.org/W3137875211","https://openalex.org/W3157848896","https://openalex.org/W3158617745","https://openalex.org/W3188913081","https://openalex.org/W4200404159","https://openalex.org/W4220882094","https://openalex.org/W4220958508","https://openalex.org/W4220990849","https://openalex.org/W4221039638","https://openalex.org/W4221118949","https://openalex.org/W4224309960","https://openalex.org/W4285263226","https://openalex.org/W4293023013","https://openalex.org/W4293243554","https://openalex.org/W4312141825"],"related_works":["https://openalex.org/W2168940796","https://openalex.org/W4282568311","https://openalex.org/W2951473296","https://openalex.org/W2883928845","https://openalex.org/W4288420200","https://openalex.org/W3145095675","https://openalex.org/W2024329643","https://openalex.org/W4365793791","https://openalex.org/W3134072570","https://openalex.org/W2171195786"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,76,107,181],"study":[4],"of":[5,132],"methods":[6,56,134,170],"for":[7,47,110,171,192],"mapping":[8,38,55,90,133,169],"the":[9,18,22,34,53,58,64,83,97,125,154,193],"convolutional":[10],"workloads":[11],"in":[12,21,45,153],"deep":[13],"neural":[14,137],"networks":[15],"(DNNs)":[16],"onto":[17],"computing":[19,24,145],"hardware":[20,108],"in-memory":[23],"(IMC)":[25],"architecture.":[26],"Specifically,":[27],"we":[28,51,118],"focus":[29],"on":[30,67,96],"categorizing":[31],"and":[32,62,71,85,104,128,143,157,178],"benchmarking":[33,131,148],"processing":[35],"element":[36],"(PE)-level":[37],"methods,":[39],"which":[40],"have":[41],"not":[42],"been":[43],"investigated":[44],"detail":[46],"IMC-based":[48],"architectures.":[49],"First,":[50],"categorize":[52],"PE-level":[54,115],"from":[57],"loop":[59],"unrolling":[60],"perspective":[61],"discuss":[63],"corresponding":[65],"implications":[66],"input":[68,84],"data":[69,73],"reuse":[70],"output":[72,86],"reduction.":[74],"Then,":[75],"mapping-oriented":[77],"architecture":[78,93,126],"is":[79,94],"proposed":[80],"by":[81,188],"considering":[82],"datapaths":[87],"under":[88,135],"various":[89,136],"methods.":[91],"The":[92,147],"evaluated":[95],"45":[98],"nm":[99],"technology":[100],"showing":[101],"good":[102],"area-efficiency":[103],"scalability,":[105],"providing":[106],"substrate":[109],"further":[111],"performance":[112],"improvements":[113],"via":[114],"mappings.":[116],"Furthermore,":[117],"present":[119,163],"an":[120],"evaluation":[121],"framework":[122],"that":[123,180],"captures":[124],"behaviors":[127],"enables":[129],"extensive":[130],"network":[138],"workloads,":[139],"main":[140],"memory":[141],"bandwidth,":[142],"digital":[144],"throughput.":[146],"results":[149],"demonstrate":[150,179],"significant":[151],"tradeoffs":[152],"design":[155,160],"space":[156],"unlock":[158],"new":[159],"possibilities.":[161],"We":[162],"case":[164],"studies":[165],"to":[166,190],"showcase":[167],"preferred":[168],"best":[172],"energy":[173],"consumption":[174],"and/or":[175],"execution":[176,186],"time":[177,187],"hybrid-mapping":[182],"scheme":[183],"enhances":[184],"minimum":[185],"up":[189],"30%":[191],"publicly-available":[194],"DNN":[195],"benchmarks.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}