{"id":"https://openalex.org/W4399952905","doi":"https://doi.org/10.1109/tc.2024.3404096","title":"HYDRA: A Hybrid Resistance Drift Resilient Architecture for Phase Change Memory-Based Neural Network Accelerators","display_name":"HYDRA: A Hybrid Resistance Drift Resilient Architecture for Phase Change Memory-Based Neural Network Accelerators","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4399952905","doi":"https://doi.org/10.1109/tc.2024.3404096"},"language":"en","primary_location":{"id":"doi:10.1109/tc.2024.3404096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2024.3404096","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","1557-9956","2326-3814"],"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 Computers","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/A5068146203","display_name":"Thai-Hoang Nguyen","orcid":"https://orcid.org/0000-0001-5498-0030"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Thai-Hoang Nguyen","raw_affiliation_strings":["Design Technology Team, Memory Business, Samsung Electronics, Hwaseong, Korea"],"raw_orcid":"https://orcid.org/0000-0001-5498-0030","affiliations":[{"raw_affiliation_string":"Design Technology Team, Memory Business, Samsung Electronics, Hwaseong, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057878975","display_name":"Muhammad Imran","orcid":"https://orcid.org/0000-0002-6246-6143"},"institutions":[{"id":"https://openalex.org/I929597975","display_name":"National University of Sciences and Technology","ror":"https://ror.org/03w2j5y17","country_code":"PK","type":"education","lineage":["https://openalex.org/I929597975"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Imran","raw_affiliation_strings":["Department of Electrical Engineering, School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad, Pakistan"],"raw_orcid":"https://orcid.org/0000-0002-6246-6143","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad, Pakistan","institution_ids":["https://openalex.org/I929597975"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091341639","display_name":"Jaehyuk Choi","orcid":"https://orcid.org/0000-0003-4700-1900"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaehyuk Choi","raw_affiliation_strings":["Department of Semiconductor Systems Engineering, Sungkyunkwan University, Suwon, Korea"],"raw_orcid":"https://orcid.org/0000-0003-4700-1900","affiliations":[{"raw_affiliation_string":"Department of Semiconductor Systems Engineering, Sungkyunkwan University, Suwon, Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026627679","display_name":"Joon-Sung Yang","orcid":"https://orcid.org/0000-0002-1502-5353"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Joon-Sung Yang","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Department of Systems Semiconductor Engineering and BK21 Graduate Program in Intelligent Semiconductor Technology, Yonsei University, Seoul, Korea"],"raw_orcid":"https://orcid.org/0000-0002-1502-5353","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Department of Systems Semiconductor Engineering and BK21 Graduate Program in Intelligent Semiconductor Technology, Yonsei University, Seoul, Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068146203"],"corresponding_institution_ids":["https://openalex.org/I2250650973"],"apc_list":null,"apc_paid":null,"fwci":1.2017,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78600432,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"73","issue":"9","first_page":"2123","last_page":"2135"},"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/T11315","display_name":"Phase-change materials and chalcogenides","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.5799815654754639},{"id":"https://openalex.org/keywords/phase-change-memory","display_name":"Phase-change memory","score":0.5301167964935303},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4957769811153412},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45572394132614136},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.36077117919921875},{"id":"https://openalex.org/keywords/phase-change","display_name":"Phase change","score":0.2755824327468872},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24283459782600403},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11139857769012451},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.09726035594940186}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5799815654754639},{"id":"https://openalex.org/C64142963","wikidata":"https://www.wikidata.org/wiki/Q1153902","display_name":"Phase-change memory","level":3,"score":0.5301167964935303},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4957769811153412},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45572394132614136},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.36077117919921875},{"id":"https://openalex.org/C133256868","wikidata":"https://www.wikidata.org/wiki/Q7180940","display_name":"Phase change","level":2,"score":0.2755824327468872},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24283459782600403},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11139857769012451},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.09726035594940186},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C61696701","wikidata":"https://www.wikidata.org/wiki/Q770766","display_name":"Engineering physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tc.2024.3404096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2024.3404096","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","1557-9956","2326-3814"],"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 Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1996160696","https://openalex.org/W2036934942","https://openalex.org/W2048266589","https://openalex.org/W2083343565","https://openalex.org/W2091988614","https://openalex.org/W2115500527","https://openalex.org/W2119144962","https://openalex.org/W2126370767","https://openalex.org/W2194775991","https://openalex.org/W2289252105","https://openalex.org/W2442272385","https://openalex.org/W2518281301","https://openalex.org/W2595748027","https://openalex.org/W2612375349","https://openalex.org/W2798696633","https://openalex.org/W2801197783","https://openalex.org/W2809624076","https://openalex.org/W2883451745","https://openalex.org/W2910983724","https://openalex.org/W2948661249","https://openalex.org/W2966740705","https://openalex.org/W2978384356","https://openalex.org/W2979754840","https://openalex.org/W2996801341","https://openalex.org/W3004493283","https://openalex.org/W3005874416","https://openalex.org/W3025017204","https://openalex.org/W3036979375","https://openalex.org/W3084534437","https://openalex.org/W3101272433","https://openalex.org/W3146726557","https://openalex.org/W3201969459","https://openalex.org/W3210205345","https://openalex.org/W4230982788","https://openalex.org/W4251370906","https://openalex.org/W4252174618","https://openalex.org/W6677580257","https://openalex.org/W6745889759","https://openalex.org/W6753069482"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W2038503502"],"abstract_inverted_index":{"In-memory":[0],"Computing":[1],"(IMC)":[2],"using":[3],"Phase":[4],"Change":[5],"Memory":[6],"(PCM)":[7],"has":[8,105,125],"proven":[9],"to":[10,35,112,169,182],"be":[11],"effective":[12],"for":[13,88,96,135,167],"efficient":[14,97],"processing":[15],"of":[16,25,51,54,60,117,153,165],"Deep":[17],"Neural":[18],"Networks":[19],"(DNNs).":[20],"However,":[21],"with":[22,150],"the":[23,43,52,67,74,114,136,151,162],"use":[24,94],"multi-level":[26],"cell":[27,102],"PCM":[28],"(MLC-PCM)":[29],"in":[30,38,157,187],"NVMs-based":[31],"accelerators,":[32],"errors":[33,57,69,156],"due":[34],"resistance":[36,55,84,108,154],"drift":[37,56,68,85,109,155,173,178],"MLC-PCM":[39,61,89,121],"can":[40,71,160],"severely":[41],"degrade":[42],"DNNs":[44,118,166],"accuracy.":[45,75],"In":[46],"this":[47],"paper,":[48],"an":[49],"analysis":[50],"impact":[53,73],"on":[58,141],"accuracy":[59,164,185],"based":[62,90],"DNN":[63,91,143],"accelerator":[64],"shows":[65],"that":[66],"alone":[70],"significantly":[72],"This":[76],"paper":[77],"proposes":[78],"Hydra,":[79],"which":[80,93,104,124],"is":[81,174],"a":[82,106,126,183,189],"hybrid":[83],"resilient":[86],"architecture":[87],"accelerators":[92],"IMC":[95],"computations.":[98],"Hydra":[99,159],"utilizes":[100],"Tri-level":[101],"PCM,":[103,158],"negligible":[107],"error":[110,128],"rate,":[111],"store":[113],"critical":[115],"bits":[116],"parameters":[119],"and":[120,146],"(4-level":[122],"cell),":[123],"higher":[127],"rate":[129],"(but":[130],"offers":[131],"more":[132],"storage":[133],"density),":[134],"non-critical":[137],"bits.":[138],"Experimental":[139],"results":[140],"various":[142],"architectures,":[144],"configurations":[145],"datasets":[147],"show":[148],"that,":[149],"presence":[152],"maintain":[161],"baseline":[163],"up":[168],"1":[170],"year":[171],"(resistance":[172],"time-dependent),":[175],"whereas":[176],"conventional":[177],"tolerance":[179],"techniques":[180],"lead":[181],"significant":[184],"drop":[186],"just":[188],"few":[190],"seconds.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}
