{"id":"https://openalex.org/W3048152613","doi":"https://doi.org/10.1145/3370748.3406583","title":"Embedding error correction into crossbars for reliable matrix vector multiplication using emerging devices","display_name":"Embedding error correction into crossbars for reliable matrix vector multiplication using emerging devices","publication_year":2020,"publication_date":"2020-08-07","ids":{"openalex":"https://openalex.org/W3048152613","doi":"https://doi.org/10.1145/3370748.3406583","mag":"3048152613"},"language":"en","primary_location":{"id":"doi:10.1145/3370748.3406583","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3370748.3406583","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design","raw_type":"proceedings-article"},"type":"conference-paper","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/A5004724074","display_name":"Qiuwen Lou","orcid":"https://orcid.org/0000-0002-9266-8125"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiuwen Lou","raw_affiliation_strings":["University of Notre Dame"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101972406","display_name":"Tianqi Gao","orcid":"https://orcid.org/0000-0001-8938-7640"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianqi Gao","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079843766","display_name":"Patrick Faley","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Patrick Faley","raw_affiliation_strings":["University of Notre Dame"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003032564","display_name":"Michael Niemier","orcid":"https://orcid.org/0000-0001-7776-4306"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Niemier","raw_affiliation_strings":["University of Notre Dame"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100600905","display_name":"Xiaobo Sharon Hu","orcid":"https://orcid.org/0000-0002-6636-9738"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"X. Sharon Hu","raw_affiliation_strings":["University of Notre Dame"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062849115","display_name":"Siddharth Joshi","orcid":"https://orcid.org/0000-0002-9201-9678"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siddharth Joshi","raw_affiliation_strings":["University of Notre Dame"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"139","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":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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","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/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/T10472","display_name":"Semiconductor materials and devices","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6788026690483093},{"id":"https://openalex.org/keywords/low-density-parity-check-code","display_name":"Low-density parity-check code","score":0.5951968431472778},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5334892868995667},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5137375593185425},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5134730935096741},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.49075445532798767},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.45595598220825195},{"id":"https://openalex.org/keywords/matrix-multiplication","display_name":"Matrix multiplication","score":0.4555585980415344},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.45322924852371216},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4169742465019226},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.41622835397720337},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.41297030448913574},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.40268272161483765},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.37279993295669556},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19179821014404297},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08402872085571289}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6788026690483093},{"id":"https://openalex.org/C67692717","wikidata":"https://www.wikidata.org/wiki/Q187444","display_name":"Low-density parity-check code","level":3,"score":0.5951968431472778},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5334892868995667},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5137375593185425},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5134730935096741},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.49075445532798767},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.45595598220825195},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.4555585980415344},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.45322924852371216},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4169742465019226},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.41622835397720337},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.41297030448913574},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.40268272161483765},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.37279993295669556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19179821014404297},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08402872085571289},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3370748.3406583","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3370748.3406583","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design","raw_type":"proceedings-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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1971319818","https://openalex.org/W2040475153","https://openalex.org/W2047478832","https://openalex.org/W2056507634","https://openalex.org/W2143518405","https://openalex.org/W2248761152","https://openalex.org/W2289252105","https://openalex.org/W2469490737","https://openalex.org/W2497735908","https://openalex.org/W2518281301","https://openalex.org/W2604218357","https://openalex.org/W2606722458","https://openalex.org/W2612375349","https://openalex.org/W2613989746","https://openalex.org/W2725159389","https://openalex.org/W2771375250","https://openalex.org/W2787759178","https://openalex.org/W2795127895","https://openalex.org/W2909534142","https://openalex.org/W2936443718","https://openalex.org/W2963733018","https://openalex.org/W3024621361","https://openalex.org/W3182208082"],"related_works":["https://openalex.org/W2903058006","https://openalex.org/W2102374550","https://openalex.org/W2047069332","https://openalex.org/W2352157218","https://openalex.org/W4213381250","https://openalex.org/W4225319325","https://openalex.org/W2124455219","https://openalex.org/W2394408226","https://openalex.org/W4389168214","https://openalex.org/W4366457933"],"abstract_inverted_index":{"Emerging":[0],"memory":[1],"devices":[2],"are":[3,121],"an":[4,125,148],"attractive":[5],"choice":[6],"for":[7,15],"implementing":[8],"very":[9],"energy-efficient":[10],"in-situ":[11,57,81],"matrix-vector":[12],"multiplication":[13],"(MVM)":[14],"use":[16],"in":[17,113,150,167,196],"intelligent":[18],"edge":[19],"platforms.":[20],"Despite":[21],"their":[22],"great":[23],"potential,":[24],"device-level":[25],"non-idealities":[26],"have":[27],"a":[28,43,161],"large":[29],"impact":[30],"on":[31,71,199],"the":[32,62,72,78,97,111,178],"application-level":[33],"accuracy":[34,94,112,138,153],"of":[35,88,99,110,118,154],"deep":[36],"neural":[37],"network":[38],"(DNN)":[39],"inference.":[40],"We":[41,59,83],"introduce":[42],"low-density":[44],"parity-check":[45],"code":[46],"(LDPC)":[47],"based":[48],"approach":[49],"to":[50,124,160,183],"correct":[51],"non-ideality":[52],"induced":[53],"errors":[54],"encountered":[55],"during":[56],"MVM.":[58,82],"first":[60],"encode":[61],"weights":[63,89],"using":[64,133],"error":[65],"correcting":[66],"codes":[67],"(ECC),":[68],"perform":[69],"MVM":[70,114],"encoded":[73],"weights,":[74],"and":[75],"then":[76],"decode":[77],"result":[79],"after":[80],"show":[84],"that":[85,163,174],"partial":[86],"encoding":[87],"can":[90,176],"maintain":[91],"DNN":[92,197],"inference":[93,198],"while":[95],"minimizing":[96],"overhead":[98],"LDPC":[100,134],"decoding.":[101],"Within":[102],"two":[103],"iterations,":[104],"our":[105],"ECC":[106,127,182],"method":[107,128],"recovers":[108],"60%":[109],"computations":[115,120],"when":[116,158],"5%":[117],"underlying":[119],"error-prone.":[122],"Compared":[123],"alternative":[126],"which":[129],"uses":[130,164],"arithmetic":[131],"codes,":[132],"improves":[135],"AlexNet":[136],"classification":[137,152],"by":[139,181],"0.8%":[140],"at":[141,144,206],"iso-energy.":[142],"Similarly,":[143],"iso-energy,":[145],"we":[146,175],"demonstrate":[147,173],"improvement":[149,195],"CIFAR-10":[151,200],"54%":[155],"with":[156,202],"VGG-11":[157,203],"compared":[159],"strategy":[162],"2\u00d7":[165],"redundancy":[166],"weights.":[168],"Further":[169],"design":[170],"space":[171],"explorations":[172],"leverage":[177],"resilience":[179],"endowed":[180],"improve":[184],"energy":[185,193],"efficiency":[186,194],"(by":[187],"reducing":[188],"operating":[189],"voltage).":[190],"A":[191],"3.3\u00d7":[192],"dataset":[201],"is":[204],"achieved":[205],"iso-accuracy.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}