{"id":"https://openalex.org/W3017574963","doi":"https://doi.org/10.1109/aicas48895.2020.9073942","title":"Deep Neural Network Mapping and Performance Analysis on Tiled RRAM Architecture","display_name":"Deep Neural Network Mapping and Performance Analysis on Tiled RRAM Architecture","publication_year":2020,"publication_date":"2020-04-23","ids":{"openalex":"https://openalex.org/W3017574963","doi":"https://doi.org/10.1109/aicas48895.2020.9073942","mag":"3017574963"},"language":"en","primary_location":{"id":"doi:10.1109/aicas48895.2020.9073942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas48895.2020.9073942","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)","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/A5013835189","display_name":"Xinxin Wang","orcid":"https://orcid.org/0000-0002-6793-9763"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinxin Wang","raw_affiliation_strings":["Electrical Engineering and Computer Science, University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101801919","display_name":"Qiwen Wang","orcid":"https://orcid.org/0000-0002-4350-0203"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiwen Wang","raw_affiliation_strings":["Electrical Engineering and Computer Science, University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100581952","display_name":"Fan-Hsuan Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fan-Hsuan Meng","raw_affiliation_strings":["Electrical Engineering and Computer Science, University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100410180","display_name":"Seung Hwan Lee","orcid":"https://orcid.org/0000-0002-5839-6533"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seung Hwan Lee","raw_affiliation_strings":["Electrical Engineering and Computer Science, University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066881061","display_name":"Wei L\u00fc","orcid":"https://orcid.org/0000-0003-4731-1976"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei D Lu","raw_affiliation_strings":["Electrical Engineering and Computer Science, University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6244,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.67372657,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"141","last_page":"144"},"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":0.9998000264167786,"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/T10207","display_name":"Advanced biosensing and bioanalysis techniques","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/resistive-random-access-memory","display_name":"Resistive random-access memory","score":0.8198657035827637},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7881743907928467},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.6596903800964355},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.6153441071510315},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5911719799041748},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.52208012342453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5181604623794556},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4984712600708008},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.4244394898414612},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.38740330934524536},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37823793292045593},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08420327305793762},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.05709335207939148}],"concepts":[{"id":"https://openalex.org/C182019814","wikidata":"https://www.wikidata.org/wiki/Q1143830","display_name":"Resistive random-access memory","level":3,"score":0.8198657035827637},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7881743907928467},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.6596903800964355},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.6153441071510315},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5911719799041748},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.52208012342453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5181604623794556},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4984712600708008},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.4244394898414612},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.38740330934524536},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37823793292045593},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08420327305793762},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.05709335207939148},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aicas48895.2020.9073942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas48895.2020.9073942","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2612445135","https://openalex.org/W2787759178","https://openalex.org/W2830509727","https://openalex.org/W2960778947","https://openalex.org/W2962851944","https://openalex.org/W2963122961","https://openalex.org/W3005901860","https://openalex.org/W4297775537"],"related_works":["https://openalex.org/W2545245183","https://openalex.org/W4285161415","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128","https://openalex.org/W2799384463"],"abstract_inverted_index":{"Representative":[0],"deep":[1],"neural":[2],"networks":[3],"(DNNs)":[4],"have":[5,32,60],"been":[6,33,61],"successfully":[7,62],"mapped":[8],"on":[9,66],"an":[10],"RRAM-based":[11],"tiled":[12,52],"in-memory":[13],"computing":[14],"(IMC)":[15],"architecture.":[16,53],"Effects":[17],"of":[18],"finite":[19],"array":[20],"size":[21],"and":[22,42,46,58,64,69],"quantized":[23],"partial":[24],"products":[25],"(PPs)":[26],"due":[27],"to":[28,38],"ADC":[29],"precision":[30],"constraints":[31],"analyzed.":[34],"Methods":[35],"were":[36],"developed":[37],"solve":[39],"these":[40],"challenges":[41],"preserve":[43],"DNN":[44],"accuracies":[45],"IMC":[47],"performance":[48],"gains":[49],"in":[50],"the":[51],"Popular":[54],"models":[55],"VGG-16,":[56],"MobileNet,":[57],"RNN/LSTM":[59],"implemented":[63],"tested":[65],"ImageNet":[67],"dataset":[68],"text":[70],"classification":[71],"tasks,":[72],"respectively.":[73]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}