{"id":"https://openalex.org/W4321277298","doi":"https://doi.org/10.48550/arxiv.2302.08469","title":"Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators","display_name":"Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators","publication_year":2023,"publication_date":"2023-02-16","ids":{"openalex":"https://openalex.org/W4321277298","doi":"https://doi.org/10.48550/arxiv.2302.08469"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2302.08469","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.08469","pdf_url":"https://arxiv.org/pdf/2302.08469","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2302.08469","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008815965","display_name":"Malte J. Rasch","orcid":"https://orcid.org/0000-0002-7988-4624"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rasch, Malte J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015811754","display_name":"Charles Mackin","orcid":"https://orcid.org/0000-0001-8413-5583"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mackin, Charles","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027282232","display_name":"Manuel Le Gallo","orcid":"https://orcid.org/0000-0003-1600-6151"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gallo, Manuel Le","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100687053","display_name":"An Chen","orcid":"https://orcid.org/0000-0002-7903-4953"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, An","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026800272","display_name":"Andrea Fasoli","orcid":"https://orcid.org/0000-0001-6892-5139"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fasoli, Andrea","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052970037","display_name":"Fr\u00e9d\u00e9ric Odermatt","orcid":"https://orcid.org/0009-0000-3977-5020"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Odermatt, Frederic","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368998","display_name":"Ning Li","orcid":"https://orcid.org/0000-0002-0680-9666"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ning","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110692025","display_name":"S. R. Nandakumar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nandakumar, S. R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058290381","display_name":"Pritish Narayanan","orcid":"https://orcid.org/0000-0002-3176-0059"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Narayanan, Pritish","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086723230","display_name":"Hsinyu Tsai","orcid":"https://orcid.org/0000-0002-3971-097X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tsai, Hsinyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014981734","display_name":"Geoffrey W. Burr","orcid":"https://orcid.org/0000-0001-5717-2549"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Burr, Geoffrey W.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017236774","display_name":"Abu Sebastian","orcid":"https://orcid.org/0000-0001-5603-5243"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sebastian, Abu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5051232628","display_name":"Vijay Narayanan","orcid":"https://orcid.org/0009-0008-8433-963X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Narayanan, Vijay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9954000115394592,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7586100101470947},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.6604273319244385},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6403767466545105},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5087152123451233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5072178840637207},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4946694076061249},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4854789078235626},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.4815981090068817},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4782611131668091},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4780878722667694},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.4248770773410797},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3500986695289612},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.3285658359527588},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.2173650860786438}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7586100101470947},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.6604273319244385},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6403767466545105},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5087152123451233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5072178840637207},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4946694076061249},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4854789078235626},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.4815981090068817},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4782611131668091},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4780878722667694},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.4248770773410797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3500986695289612},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.3285658359527588},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.2173650860786438},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2302.08469","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.08469","pdf_url":"https://arxiv.org/pdf/2302.08469","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40770-4","is_oa":false,"landing_page_url":"https://www.nature.com/articles/s41467-023-40770-4","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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"},{"id":"doi:10.48550/arxiv.2302.08469","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2302.08469","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2302.08469","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.08469","pdf_url":"https://arxiv.org/pdf/2302.08469","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8999999761581421}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4321277298.pdf","grobid_xml":"https://content.openalex.org/works/W4321277298.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4285144618","https://openalex.org/W2518118925","https://openalex.org/W4285104150","https://openalex.org/W4389319487","https://openalex.org/W3159273459","https://openalex.org/W4319952061","https://openalex.org/W4280636456","https://openalex.org/W4388913998","https://openalex.org/W4310584535","https://openalex.org/W3154092384"],"abstract_inverted_index":{"Analog":[0],"in-memory":[1],"computing":[2],"(AIMC)":[3],"--":[4,15],"a":[5,47,67,109,116],"promising":[6],"approach":[7],"for":[8,92],"energy-efficient":[9],"acceleration":[10],"of":[11,90,112,136],"deep":[12,38],"learning":[13],"workloads":[14,98],"computes":[16],"matrix-vector":[17],"multiplications":[18],"(MVMs)":[19],"but":[20],"only":[21,66],"approximately,":[22],"due":[23],"to":[24,46,59,85,108,156,171,192],"nonidealities":[25,167],"that":[26,132,165,168,187],"often":[27],"are":[28,189],"non-deterministic":[29],"or":[30,174],"nonlinear.":[31],"This":[32],"can":[33,150],"adversely":[34],"impact":[35,182],"the":[36,88,172,177,180],"achievable":[37],"neural":[39,141,145],"network":[40],"(DNN)":[41],"inference":[42],"accuracy":[43,89],"as":[44],"compared":[45],"conventional":[48],"floating":[49],"point":[50],"(FP)":[51],"implementation.":[52],"While":[53],"retraining":[54,128],"has":[55,64],"previously":[56],"been":[57],"suggested":[58],"improve":[60,124],"robustness,":[61],"prior":[62],"work":[63],"explored":[65],"few":[68],"DNN":[69,101,184],"topologies,":[70,102,138],"using":[71],"disparate":[72],"and":[73,103,106,118,148,186],"overly":[74],"simplified":[75],"AIMC":[76,91,121,166],"hardware":[77],"models.":[78],"Here,":[79],"we":[80,123],"use":[81],"hardware-aware":[82],"(HWA)":[83],"training":[84],"systematically":[86],"examine":[87],"multiple":[93,100],"common":[94],"artificial":[95],"intelligence":[96],"(AI)":[97],"across":[99],"investigate":[104],"sensitivity":[105],"robustness":[107],"broad":[110],"set":[111],"nonidealities.":[113,194],"By":[114],"introducing":[115],"new":[117],"highly":[119],"realistic":[120],"crossbar-model,":[122],"significantly":[125],"on":[126,159,183],"earlier":[127],"approaches.":[129],"We":[130],"show":[131,157],"many":[133],"large-scale":[134],"DNNs":[135],"various":[137],"including":[139],"convolutional":[140],"networks":[142,146],"(CNNs),":[143],"recurrent":[144],"(RNNs),":[147],"transformers,":[149],"in":[151],"fact":[152],"be":[153],"successfully":[154],"retrained":[155],"iso-accuracy":[158],"AIMC.":[160],"Our":[161],"results":[162],"further":[163],"suggest":[164],"add":[169],"noise":[170],"inputs":[173],"outputs,":[175],"not":[176],"weights,":[178],"have":[179],"largest":[181],"accuracy,":[185],"RNNs":[188],"particularly":[190],"robust":[191],"all":[193]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
