{"id":"https://openalex.org/W3112740243","doi":"https://doi.org/10.1109/tcad.2020.3043731","title":"DNN+NeuroSim V2.0: An End-to-End Benchmarking Framework for Compute-in-Memory Accelerators for On-Chip Training","display_name":"DNN+NeuroSim V2.0: An End-to-End Benchmarking Framework for Compute-in-Memory Accelerators for On-Chip Training","publication_year":2020,"publication_date":"2020-12-14","ids":{"openalex":"https://openalex.org/W3112740243","doi":"https://doi.org/10.1109/tcad.2020.3043731","mag":"3112740243"},"language":"en","primary_location":{"id":"doi:10.1109/tcad.2020.3043731","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcad.2020.3043731","pdf_url":null,"source":{"id":"https://openalex.org/S100835903","display_name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","issn_l":"0278-0070","issn":["0278-0070","1937-4151"],"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 Transactions on Computer-Aided Design of Integrated 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/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, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-6148-7711","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014877058","display_name":"Shanshi Huang","orcid":"https://orcid.org/0000-0002-1760-7656"},"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":"Shanshi Huang","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1760-7656","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013020304","display_name":"Hongwu Jiang","orcid":"https://orcid.org/0000-0002-3048-5948"},"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":"Hongwu Jiang","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3048-5948","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072117537","display_name":"Anni Lu","orcid":"https://orcid.org/0000-0002-4415-0866"},"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":"Anni Lu","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4415-0866","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","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, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-0068-3652","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":11.8633,"has_fulltext":false,"cited_by_count":286,"citation_normalized_percentile":{"value":0.99103278,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"40","issue":"11","first_page":"2306","last_page":"2319"},"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":0.9994000196456909,"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":0.9962000250816345,"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/end-to-end-principle","display_name":"End-to-end principle","score":0.7525370121002197},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.7138839364051819},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6229410171508789},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.5518114566802979},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5315555930137634},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.36678487062454224},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3430749773979187},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3321373462677002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2853422164916992},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.1747911274433136},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08550167083740234},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06723156571388245}],"concepts":[{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.7525370121002197},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7138839364051819},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6229410171508789},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.5518114566802979},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5315555930137634},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.36678487062454224},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3430749773979187},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3321373462677002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2853422164916992},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.1747911274433136},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08550167083740234},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06723156571388245},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcad.2020.3043731","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcad.2020.3043731","pdf_url":null,"source":{"id":"https://openalex.org/S100835903","display_name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","issn_l":"0278-0070","issn":["0278-0070","1937-4151"],"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 Transactions on Computer-Aided Design of Integrated Circuits and Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.9100000262260437}],"awards":[{"id":"https://openalex.org/G3290149408","display_name":null,"funder_award_id":"NSF-CCF-1903951","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1937359183","https://openalex.org/W2016922062","https://openalex.org/W2026145098","https://openalex.org/W2131763976","https://openalex.org/W2462963692","https://openalex.org/W2510331918","https://openalex.org/W2535534962","https://openalex.org/W2550153070","https://openalex.org/W2782046614","https://openalex.org/W2785141883","https://openalex.org/W2787453651","https://openalex.org/W2787513570","https://openalex.org/W2790669755","https://openalex.org/W2800050615","https://openalex.org/W2899224990","https://openalex.org/W2912495531","https://openalex.org/W2943765373","https://openalex.org/W2964164125","https://openalex.org/W2966305769","https://openalex.org/W2997869757","https://openalex.org/W3005619596","https://openalex.org/W3010932008","https://openalex.org/W3036454296","https://openalex.org/W3090816752","https://openalex.org/W3092083602","https://openalex.org/W6679951043","https://openalex.org/W6748319235","https://openalex.org/W6779548340"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2000169967","https://openalex.org/W2112883198"],"abstract_inverted_index":{"DNN+NeuroSim":[0,79,192],"is":[1,31,194],"an":[2,110],"integrated":[3],"framework":[4,49,80,193],"to":[5,20,25,33,43,88],"benchmark":[6],"compute-in-memory":[7],"(CIM)":[8],"accelerators":[9,163],"for":[10,62,131,153,171,183],"deep":[11],"neural":[12],"networks,":[13],"with":[14,36,71],"hierarchical":[15],"design":[16],"options":[17],"from":[18],"device-level,":[19],"circuit":[21],"level":[22],"and":[23,54,60,97,106,140,150,168],"up":[24],"algorithm":[26],"level.":[27],"A":[28],"python":[29,148],"wrapper":[30],"developed":[32,87],"interface":[34],"NeuroSim":[35,158],"a":[37],"popular":[38],"machine":[39],"learning":[40],"platform:":[41],"Pytorch,":[42],"support":[44],"flexible":[45],"network":[46],"structures.":[47],"The":[48,186],"provides":[50],"automatic":[51],"algorithm-to-hardware":[52],"mapping,":[53],"evaluates":[55],"chip-level":[56],"area,":[57],"energy":[58],"efficiency":[59],"throughput":[61],"training":[63,188],"or":[64],"inference,":[65],"as":[66,68],"well":[67],"training/inference":[69],"accuracy":[70,105],"hardware":[72,107],"constraints.":[73],"Our":[74],"prior":[75],"inference":[76,111],"version":[77,189],"of":[78,92,109,121,143,180,190],"available":[81,195],"at":[82,196],"<italic":[83,197],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[84,198],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><uri>https://github.com/neurosim/DNN_NeuroSim_V1.2</uri></i>":[85],"was":[86],"estimate":[89],"the":[90,104,119,122,136,147,177,191],"impact":[91,120],"reliability":[93],"in":[94,157],"synaptic":[95,181],"devices,":[96],"analog-to-digital":[98],"converter":[99],"(ADC)":[100],"quantization":[101],"loss":[102],"on":[103,165,173],"performance":[108],"engine.":[112],"In":[113],"this":[114],"work,":[115],"we":[116,160],"further":[117],"investigated":[118],"\u201canalog\u201d":[123],"emerging":[124],"nonvolatile":[125],"memory":[126],"(eNVM)\u2019s":[127],"nonideal":[128],"device":[129],"properties":[130],"on-chip":[132,184],"training.":[133,185],"By":[134],"introducing":[135],"nonlinearity,":[137],"asymmetry,":[138],"device-to-device":[139],"cycle-to-cycle":[141],"variation":[142],"weight":[144],"update":[145],"into":[146],"wrapper,":[149],"peripheral":[151],"circuits":[152],"error/weight":[154],"gradient":[155],"computation":[156],"core,":[159],"benchmarked":[161],"CIM":[162],"based":[164],"state-of-the-art":[166],"SRAM":[167],"eNVM":[169],"devices":[170,182],"VGG-8":[172],"CIFAR-10":[174],"dataset,":[175],"revealing":[176],"crucial":[178],"specs":[179],"latest":[187],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><uri>https://github.com/neurosim/DNN_NeuroSim_V2.1</uri></i>":[199],".":[200]},"counts_by_year":[{"year":2026,"cited_by_count":28},{"year":2025,"cited_by_count":82},{"year":2024,"cited_by_count":62},{"year":2023,"cited_by_count":61},{"year":2022,"cited_by_count":31},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":3}],"updated_date":"2026-06-27T08:28:00.272161","created_date":"2025-10-10T00:00:00"}