{"id":"https://openalex.org/W2889081591","doi":"https://doi.org/10.1109/drc.2018.8442140","title":"Energy-Efficient, Two-Dimensional Analog Memory for Neuromorphic Computing","display_name":"Energy-Efficient, Two-Dimensional Analog Memory for Neuromorphic Computing","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2889081591","doi":"https://doi.org/10.1109/drc.2018.8442140","mag":"2889081591"},"language":"en","primary_location":{"id":"doi:10.1109/drc.2018.8442140","is_oa":false,"landing_page_url":"https://doi.org/10.1109/drc.2018.8442140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 76th Device Research Conference (DRC)","raw_type":"proceedings-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/A5016035604","display_name":"Mohammad Taghi Sharbati","orcid":"https://orcid.org/0000-0001-5120-5426"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohammad T. Sharbati","raw_affiliation_strings":["Dept. of ECE, University of Pittsburgh, 3700 O'Hara St., Pittsburgh, PA, United States of America"],"affiliations":[{"raw_affiliation_string":"Dept. of ECE, University of Pittsburgh, 3700 O'Hara St., Pittsburgh, PA, United States of America","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022134704","display_name":"Yanhao Du","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanhao Du","raw_affiliation_strings":["Dept. of ECE, University of Pittsburgh, 3700 O'Hara St., Pittsburgh, PA, United States of America"],"affiliations":[{"raw_affiliation_string":"Dept. of ECE, University of Pittsburgh, 3700 O'Hara St., Pittsburgh, PA, United States of America","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024645437","display_name":"Feng Xiong","orcid":"https://orcid.org/0000-0001-8383-5182"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Xiong","raw_affiliation_strings":["Dept. of ECE, University of Pittsburgh, 3700 O'Hara St., Pittsburgh, PA, United States of America"],"affiliations":[{"raw_affiliation_string":"Dept. of ECE, University of Pittsburgh, 3700 O'Hara St., Pittsburgh, PA, United States of America","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5016035604"],"corresponding_institution_ids":["https://openalex.org/I170201317"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08234583,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"1","last_page":"2"},"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":0.9991999864578247,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9965000152587891,"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/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.9034326076507568},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6981391310691833},{"id":"https://openalex.org/keywords/resistive-random-access-memory","display_name":"Resistive random-access memory","score":0.6966867446899414},{"id":"https://openalex.org/keywords/memristor","display_name":"Memristor","score":0.5658228993415833},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5577554106712341},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.5223314166069031},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.49329155683517456},{"id":"https://openalex.org/keywords/synaptic-weight","display_name":"Synaptic weight","score":0.4864797294139862},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.4796498417854309},{"id":"https://openalex.org/keywords/controllability","display_name":"Controllability","score":0.47761934995651245},{"id":"https://openalex.org/keywords/analog-computer","display_name":"Analog computer","score":0.4553466737270355},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.38756197690963745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3612287640571594},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.27578431367874146},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.16290578246116638},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13236185908317566}],"concepts":[{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.9034326076507568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6981391310691833},{"id":"https://openalex.org/C182019814","wikidata":"https://www.wikidata.org/wiki/Q1143830","display_name":"Resistive random-access memory","level":3,"score":0.6966867446899414},{"id":"https://openalex.org/C150072547","wikidata":"https://www.wikidata.org/wiki/Q212923","display_name":"Memristor","level":2,"score":0.5658228993415833},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5577554106712341},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.5223314166069031},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.49329155683517456},{"id":"https://openalex.org/C66949984","wikidata":"https://www.wikidata.org/wiki/Q7662043","display_name":"Synaptic weight","level":3,"score":0.4864797294139862},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.4796498417854309},{"id":"https://openalex.org/C48209547","wikidata":"https://www.wikidata.org/wiki/Q1331104","display_name":"Controllability","level":2,"score":0.47761934995651245},{"id":"https://openalex.org/C90915687","wikidata":"https://www.wikidata.org/wiki/Q63759","display_name":"Analog computer","level":2,"score":0.4553466737270355},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.38756197690963745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3612287640571594},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.27578431367874146},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.16290578246116638},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13236185908317566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/drc.2018.8442140","is_oa":false,"landing_page_url":"https://doi.org/10.1109/drc.2018.8442140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 76th Device Research Conference (DRC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1542981317","https://openalex.org/W2153041354","https://openalex.org/W2389556795","https://openalex.org/W2394732766"],"related_works":["https://openalex.org/W3173413269","https://openalex.org/W2926332116","https://openalex.org/W2995498660","https://openalex.org/W1990306796","https://openalex.org/W3139020568","https://openalex.org/W4205843713","https://openalex.org/W4205344526","https://openalex.org/W1970974872","https://openalex.org/W2971489542","https://openalex.org/W9602499"],"abstract_inverted_index":{"Unlike":[0],"modern":[1],"computers":[2,64],"that":[3],"use":[4],"digital":[5,86],"`0'":[6],"and":[7,28,101,119,154],"`1'":[8],"for":[9],"computation,":[10],"neural":[11,20,38,81],"networks":[12,82],"in":[13,19],"human":[14,45],"brains":[15,46],"exhibit":[16],"analog":[17,32,96],"changes":[18],"connections":[21,131],"(i.e.":[22],"synaptic":[23,130],"weight)":[24],"during":[25],"the":[26,37,61,75,95],"decision-making":[27],"learning":[29],"processes.":[30],"This":[31],"nature":[33],"as":[34,36,56,109,147],"well":[35],"network's":[39],"massive":[40],"parallelism":[41],"are":[42,49,83,139],"partly":[43],"why":[44],"(~20":[47],"W)":[48],"much":[50],"better":[51,69],"at":[52],"complex":[53],"tasks":[54],"such":[55,108,146],"pattern":[57],"recognition":[58],"than":[59],"even":[60],"most":[62],"powerful":[63],"(~1":[65],"MW)":[66],"with":[67,88,132],"significantly":[68],"energy":[70],"efficiency.":[71],"Currently,":[72],"majority":[73],"of":[74,98],"research":[76],"efforts":[77],"towards":[78],"developing":[79],"artificial":[80],"based":[84],"on":[85],"technology":[87],"CMOS":[89],"devices":[90,107],"[1],":[91],"which":[92],"cannot":[93],"mimic":[94,129],"behaviors":[97],"biological":[99],"synapses":[100],"thus":[102],"energy-extensive.":[103],"Recently,":[104],"emerging":[105],"memory":[106,112,117],"phase":[110],"change":[111],"(PCM),":[113],"resistive":[114],"random":[115],"access":[116],"(RRAM),":[118],"spin-torque":[120],"transfer":[121],"(STT)":[122],"RAM":[123],"[2-4]":[124],"have":[125],"been":[126],"studied":[127],"to":[128],"their":[133],"programmable":[134],"conductance.":[135],"While":[136],"these":[137],"approaches":[138],"promising,":[140],"they":[141],"still":[142],"face":[143],"various":[144],"limitations":[145],"poor":[148],"controllability,":[149],"subpar":[150],"reliability,":[151],"large":[152],"variability,":[153],"non-symmetrical":[155],"resistance":[156],"response.":[157]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
