{"id":"https://openalex.org/W2806281056","doi":"https://doi.org/10.1145/3194554.3194619","title":"Design Space Exploration of Magnetic Tunnel Junction based Stochastic Computing in Deep Learning","display_name":"Design Space Exploration of Magnetic Tunnel Junction based Stochastic Computing in Deep Learning","publication_year":2018,"publication_date":"2018-05-30","ids":{"openalex":"https://openalex.org/W2806281056","doi":"https://doi.org/10.1145/3194554.3194619","mag":"2806281056"},"language":"en","primary_location":{"id":"doi:10.1145/3194554.3194619","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3194554.3194619","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Great Lakes Symposium on VLSI","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/A5100430217","display_name":"You Wang","orcid":"https://orcid.org/0000-0002-6917-2199"},"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":"You Wang","raw_affiliation_strings":["Beihang Univeristy, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang Univeristy, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333767","display_name":"Yue Zhang","orcid":"https://orcid.org/0000-0003-0017-1398"},"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":"Yue Zhang","raw_affiliation_strings":["Beihang Univeristy, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang Univeristy, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018693228","display_name":"Youguang Zhang","orcid":"https://orcid.org/0009-0008-0928-4210"},"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":"Youguang Zhang","raw_affiliation_strings":["Beihang Univeristy, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang Univeristy, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066473925","display_name":"Weisheng Zhao","orcid":"https://orcid.org/0000-0001-8088-0404"},"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":"Weisheng Zhao","raw_affiliation_strings":["Beihang Univeristy, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang Univeristy, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052490965","display_name":"Hao Cai","orcid":"https://orcid.org/0000-0001-9251-0574"},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Hao Cai","raw_affiliation_strings":["T\u00e9l\u00e9com-ParisTech, Universit\u00e9 Paris-Saclay, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"T\u00e9l\u00e9com-ParisTech, Universit\u00e9 Paris-Saclay, Paris, France","institution_ids":["https://openalex.org/I12356871","https://openalex.org/I277688954"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018022196","display_name":"L\u00edrida Naviner","orcid":"https://orcid.org/0000-0002-6320-4153"},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Lirida Naviner","raw_affiliation_strings":["T\u00e9l\u00e9com-ParisTech, Universit\u00e9 Paris-Saclay, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"T\u00e9l\u00e9com-ParisTech, Universit\u00e9 Paris-Saclay, Paris, France","institution_ids":["https://openalex.org/I12356871","https://openalex.org/I277688954"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"403","last_page":"408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9980000257492065,"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":0.9966999888420105,"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/stochastic-computing","display_name":"Stochastic computing","score":0.9477014541625977},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7546714544296265},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5408151745796204},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5318996906280518},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.48705628514289856},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4796038866043091},{"id":"https://openalex.org/keywords/design-space-exploration","display_name":"Design space exploration","score":0.4503367245197296},{"id":"https://openalex.org/keywords/tunnel-magnetoresistance","display_name":"Tunnel magnetoresistance","score":0.41836944222450256},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37665069103240967},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3320620656013489},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.2832986116409302},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.12830477952957153},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12233823537826538}],"concepts":[{"id":"https://openalex.org/C2780971903","wikidata":"https://www.wikidata.org/wiki/Q2933705","display_name":"Stochastic computing","level":3,"score":0.9477014541625977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7546714544296265},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5408151745796204},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5318996906280518},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.48705628514289856},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4796038866043091},{"id":"https://openalex.org/C2776221188","wikidata":"https://www.wikidata.org/wiki/Q21072556","display_name":"Design space exploration","level":2,"score":0.4503367245197296},{"id":"https://openalex.org/C56202322","wikidata":"https://www.wikidata.org/wiki/Q1884383","display_name":"Tunnel magnetoresistance","level":3,"score":0.41836944222450256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37665069103240967},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3320620656013489},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2832986116409302},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.12830477952957153},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12233823537826538},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C82217956","wikidata":"https://www.wikidata.org/wiki/Q184207","display_name":"Ferromagnetism","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3194554.3194619","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3194554.3194619","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Great Lakes Symposium on VLSI","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":0.8999999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1503792000","https://openalex.org/W1599534361","https://openalex.org/W1985212093","https://openalex.org/W1995771228","https://openalex.org/W2032548797","https://openalex.org/W2034870940","https://openalex.org/W2068896528","https://openalex.org/W2077344647","https://openalex.org/W2096445739","https://openalex.org/W2101765144","https://openalex.org/W2112701476","https://openalex.org/W2114644969","https://openalex.org/W2219959730","https://openalex.org/W2303314981","https://openalex.org/W2345008675","https://openalex.org/W2403784446","https://openalex.org/W2516416362","https://openalex.org/W2520217849","https://openalex.org/W2550037452","https://openalex.org/W2611984215","https://openalex.org/W2770413419","https://openalex.org/W4251378477"],"related_works":["https://openalex.org/W2402859572","https://openalex.org/W3195476257","https://openalex.org/W4226092179","https://openalex.org/W4306791972","https://openalex.org/W4400134053","https://openalex.org/W2910319223","https://openalex.org/W4390846322","https://openalex.org/W4282568311","https://openalex.org/W3212867030","https://openalex.org/W4313484792"],"abstract_inverted_index":{"Magnetic":[0],"tunnel":[1],"junction":[2],"(MTJ)":[3],"is":[4,62,105,140],"considered":[5],"as":[6,47],"a":[7,92],"promising":[8],"memory":[9,149],"candidate":[10],"in":[11,59,107,121,142],"the":[12,53,83,116,135,138],"more":[13,153],"than":[14],"Moore":[15],"era":[16],"because":[17],"of":[18,55,85,95,144],"high":[19],"power":[20],"efficiency,":[21],"fast":[22],"access":[23],"speed,":[24],"nearly":[25],"infinite":[26],"endurance":[27],"and":[28,79,119,148],"easy":[29],"3D":[30],"integration.":[31],"The":[32,109],"nondeterministic":[33],"switching":[34,57],"behavior":[35,58],"has":[36,111],"been":[37,112],"profited":[38],"to":[39,133,151],"exploit":[40],"new":[41],"directions":[42],"for":[43,64],"computing":[44,61,70],"methods,":[45],"such":[46],"stochastic":[48,56,60,96],"computing.":[49],"In":[50],"this":[51],"paper,":[52],"application":[54],"explored":[63],"deep":[65],"neural":[66],"network":[67],"(DNN).":[68],"Stochastic":[69],"method":[71],"features":[72],"low":[73,76],"logic":[74],"complexity,":[75],"energy":[77,146],"consumption":[78,147],"fine-grained":[80],"parallelism,":[81],"boosting":[82],"performance":[84,139],"DNN":[86],"system":[87],"by":[88,114,128],"combining":[89,115],"MTJ.":[90],"As":[91],"key":[93],"block":[94],"computing,":[97],"MTJ":[98],"based":[99],"true":[100],"random":[101],"number":[102],"generator":[103],"design":[104,118],"presented":[106],"details.":[108],"functionality":[110],"validated":[113],"hardware":[117],"post-processing":[120],"software.":[122],"Simulation":[123],"results":[124],"are":[125],"demonstrated":[126],"visibly":[127],"handwritten":[129],"digits":[130],"recognition":[131],"test":[132],"show":[134],"accuracy.":[136],"Furthermore,":[137],"investigated":[141],"terms":[143],"accuracy,":[145],"occupation":[150],"find":[152],"efficient":[154],"techniques.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
