{"id":"https://openalex.org/W2973064692","doi":"https://doi.org/10.1145/3354265.3354266","title":"MLP+NeuroSimV3.0","display_name":"MLP+NeuroSimV3.0","publication_year":2019,"publication_date":"2019-07-23","ids":{"openalex":"https://openalex.org/W2973064692","doi":"https://doi.org/10.1145/3354265.3354266","mag":"2973064692"},"language":"en","primary_location":{"id":"doi:10.1145/3354265.3354266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3354265.3354266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3354265.3354266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Neuromorphic Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3354265.3354266","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021633981","display_name":"Yandong Luo","orcid":"https://orcid.org/0000-0001-8239-0492"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yandong Luo","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076031530","display_name":"Xiaochen Peng","orcid":"https://orcid.org/0000-0001-6148-7711"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaochen Peng","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054894631","display_name":"Shimeng Yu","orcid":"https://orcid.org/0000-0002-0068-3652"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shimeng Yu","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021633981"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":1.453,"has_fulltext":true,"cited_by_count":61,"citation_normalized_percentile":{"value":0.82735879,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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":0.9983999729156494,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7934902906417847},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.6259227991104126},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.5595356822013855},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.4736180007457733},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.45917773246765137},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.45252150297164917},{"id":"https://openalex.org/keywords/low-latency","display_name":"Low latency (capital markets)","score":0.4350978136062622},{"id":"https://openalex.org/keywords/synapse","display_name":"Synapse","score":0.42127907276153564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.418854296207428},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4092901945114136},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39993271231651306},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3293999433517456},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09032890200614929}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7934902906417847},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.6259227991104126},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.5595356822013855},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.4736180007457733},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.45917773246765137},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.45252150297164917},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.4350978136062622},{"id":"https://openalex.org/C127445978","wikidata":"https://www.wikidata.org/wiki/Q187181","display_name":"Synapse","level":2,"score":0.42127907276153564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.418854296207428},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4092901945114136},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39993271231651306},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3293999433517456},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09032890200614929},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3354265.3354266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3354265.3354266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3354265.3354266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Neuromorphic Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3354265.3354266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3354265.3354266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3354265.3354266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Neuromorphic Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6053735285","display_name":null,"funder_award_id":"E2CDA","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G83212158","display_name":"CAREER: Scaling-up Resistive Synaptic Arrays for Neuro-inspired Computing","funder_award_id":"1903951","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8675392359","display_name":null,"funder_award_id":"NSF-CCF-1903951","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2973064692.pdf","grobid_xml":"https://content.openalex.org/works/W2973064692.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2016922062","https://openalex.org/W2026145098","https://openalex.org/W2334364695","https://openalex.org/W2462963692","https://openalex.org/W2613989746","https://openalex.org/W2782046614","https://openalex.org/W2785141883","https://openalex.org/W2787453651","https://openalex.org/W2787513570","https://openalex.org/W2787759178","https://openalex.org/W2790669755","https://openalex.org/W2794288888","https://openalex.org/W2799229073","https://openalex.org/W2803163155","https://openalex.org/W2809579658","https://openalex.org/W2899224990","https://openalex.org/W2899516590","https://openalex.org/W2907930361","https://openalex.org/W2912270587","https://openalex.org/W2922487710"],"related_works":["https://openalex.org/W2986579802","https://openalex.org/W4389237622","https://openalex.org/W3205411230","https://openalex.org/W4286899009","https://openalex.org/W9168048","https://openalex.org/W4300849822","https://openalex.org/W4376480820","https://openalex.org/W3155891479","https://openalex.org/W3029351463","https://openalex.org/W4308600690"],"abstract_inverted_index":{"On-chip":[0],"learning":[1,11,26,53,102],"with":[2,76,88],"compute-in-memory":[3],"(CIM)":[4],"paradigm":[5],"has":[6],"become":[7],"popular":[8],"in":[9,14,33],"machine":[10],"hardware":[12],"design":[13],"the":[15,30,34,55,67,71,100,126],"recent":[16],"years.":[17],"However,":[18],"it":[19],"is":[20,133],"hard":[21],"to":[22,29,61,69,98],"achieve":[23],"high":[24,31,62],"on-chip":[25,101],"accuracy":[27],"due":[28],"nonlinearity":[32],"weight":[35],"update":[36],"curve":[37],"of":[38],"emerging":[39],"nonvolatile":[40],"memory":[41],"(eNVM)":[42],"based":[43,143],"analog":[44,82],"synapse":[45,49],"devices.":[46],"Although":[47],"digital":[48,108],"devices":[50],"offer":[51],"good":[52,89],"accuracy,":[54],"row-by-row":[56],"partial":[57,116],"sum":[58,117],"accumulation":[59],"leads":[60],"latency.":[63],"In":[64],"this":[65],"paper,":[66],"methods":[68],"solve":[70],"aforementioned":[72],"issues":[73],"are":[74,96,123],"presented":[75],"a":[77],"device-to-algorithm":[78],"level":[79],"optimization.":[80],"For":[81],"synapses,":[83],"novel":[84],"hybrid":[85],"precision":[86],"synapses":[87,109],"linearity":[90],"and":[91],"more":[92],"advanced":[93],"training":[94],"algorithms":[95],"introduced":[97],"increase":[99],"accuracy.":[103],"The":[104],"latency":[105],"issue":[106],"for":[107,140],"can":[110],"be":[111],"solved":[112],"by":[113],"using":[114],"parallel":[115],"read-out":[118],"scheme.":[119],"All":[120],"these":[121],"features":[122],"included":[124],"into":[125],"recently":[127],"released":[128],"MLP":[129],"+":[130],"NeuroSimV3.0,":[131],"which":[132],"an":[134],"in-house":[135],"developed":[136],"device-to-system":[137],"evaluation":[138],"framework":[139],"neuro-inspired":[141],"accelerators":[142],"on":[144],"CIM":[145],"paradigm.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5}],"updated_date":"2026-05-08T15:41:06.802602","created_date":"2019-09-19T00:00:00"}
