{"id":"https://openalex.org/W4293499136","doi":"https://doi.org/10.1109/tvlsi.2022.3199396","title":"In-Memory Computation With Improved Linearity Using Adaptive Sparsity-Based Compact Thermometric Code","display_name":"In-Memory Computation With Improved Linearity Using Adaptive Sparsity-Based Compact Thermometric Code","publication_year":2022,"publication_date":"2022-08-29","ids":{"openalex":"https://openalex.org/W4293499136","doi":"https://doi.org/10.1109/tvlsi.2022.3199396"},"language":"en","primary_location":{"id":"doi:10.1109/tvlsi.2022.3199396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvlsi.2022.3199396","pdf_url":null,"source":{"id":"https://openalex.org/S37538908","display_name":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","issn_l":"1063-8210","issn":["1063-8210","1557-9999"],"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 Very Large Scale Integration (VLSI) Systems","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/A5000710204","display_name":"Prasanna Kumar Saragada","orcid":"https://orcid.org/0000-0002-4877-3067"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Prasanna Kumar Saragada","raw_affiliation_strings":["Department of Electronics and Communication Engineering, IIT Roorkee, Roorkee, Uttarakhand, India"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, IIT Roorkee, Roorkee, Uttarakhand, India","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009032005","display_name":"Bishnu Prasad Das","orcid":"https://orcid.org/0000-0001-6993-2744"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Bishnu Prasad Das","raw_affiliation_strings":["Department of Electronics and Communication Engineering, IIT Roorkee, Roorkee, Uttarakhand, India"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, IIT Roorkee, Roorkee, Uttarakhand, India","institution_ids":["https://openalex.org/I154851008"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000710204"],"corresponding_institution_ids":["https://openalex.org/I154851008"],"apc_list":null,"apc_paid":null,"fwci":0.549,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.63621068,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"30","issue":"10","first_page":"1473","last_page":"1483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9934999942779541,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/linearity","display_name":"Linearity","score":0.8097318410873413},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.7807436585426331},{"id":"https://openalex.org/keywords/static-random-access-memory","display_name":"Static random-access memory","score":0.7356585264205933},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5332934856414795},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5067713856697083},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4808693528175354},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46812382340431213},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.46629801392555237},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4065936803817749},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.3840712308883667},{"id":"https://openalex.org/keywords/computational-science","display_name":"Computational science","score":0.3219430446624756},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.31607872247695923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17762327194213867},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16374552249908447},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13760584592819214},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08431535959243774}],"concepts":[{"id":"https://openalex.org/C77170095","wikidata":"https://www.wikidata.org/wiki/Q1753188","display_name":"Linearity","level":2,"score":0.8097318410873413},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.7807436585426331},{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.7356585264205933},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5332934856414795},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5067713856697083},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4808693528175354},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46812382340431213},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.46629801392555237},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4065936803817749},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3840712308883667},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.3219430446624756},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.31607872247695923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17762327194213867},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16374552249908447},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13760584592819214},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08431535959243774}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvlsi.2022.3199396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvlsi.2022.3199396","pdf_url":null,"source":{"id":"https://openalex.org/S37538908","display_name":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","issn_l":"1063-8210","issn":["1063-8210","1557-9999"],"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 Very Large Scale Integration (VLSI) Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G3817276654","display_name":null,"funder_award_id":"CRG/2021/007437","funder_id":"https://openalex.org/F4320334771","funder_display_name":"Science and Engineering Research Board"}],"funders":[{"id":"https://openalex.org/F4320334771","display_name":"Science and Engineering Research Board","ror":"https://ror.org/03ffdsr55"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2124434523","https://openalex.org/W2591601611","https://openalex.org/W2775637085","https://openalex.org/W2782511028","https://openalex.org/W2787573408","https://openalex.org/W2790511620","https://openalex.org/W2790556218","https://openalex.org/W2792893539","https://openalex.org/W2904299207","https://openalex.org/W2966524683","https://openalex.org/W2966878541","https://openalex.org/W2981240739","https://openalex.org/W3008325842","https://openalex.org/W3015432327","https://openalex.org/W3016014942","https://openalex.org/W3017968097","https://openalex.org/W3047393108","https://openalex.org/W3097655915","https://openalex.org/W3104353813","https://openalex.org/W3138084750","https://openalex.org/W3139521791","https://openalex.org/W3180627186","https://openalex.org/W3208173795","https://openalex.org/W4220990849"],"related_works":["https://openalex.org/W2950475743","https://openalex.org/W4386603768","https://openalex.org/W2886711096","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W2590796488","https://openalex.org/W4389249638","https://openalex.org/W2733410219","https://openalex.org/W2734358244","https://openalex.org/W4388700941"],"abstract_inverted_index":{"The":[0,104,126,186],"article":[1],"presents":[2],"an":[3,75,144,202],"efficient":[4],"static":[5],"random":[6],"access":[7],"memory":[8],"(SRAM)-based":[9],"in-memory":[10],"computation":[11],"(IMC)":[12],"architecture":[13,156],"which":[14],"is":[15,50],"capable":[16],"of":[17,56,67,83,99,134,146,161,178,183,189,204],"performing":[18],"image":[19],"classification":[20],"with":[21,40,88],"improved":[22,41],"linearity.":[23,42],"In":[24,151],"this":[25],"work,":[26],"we":[27],"proposed":[28,51,74,116,154],"a":[29],"thermometric":[30,47,62],"code-based":[31,63],"IMC":[32],"(TC-IMC)":[33],"to":[34,52,60,79,166],"perform":[35],"multibit":[36],"multiply-and-accumulate":[37],"(MAC)":[38],"operations":[39],"An":[43],"input":[44],"sparsity-aware":[45],"compact":[46],"code":[48],"approach":[49],"reduce":[53],"the":[54,61,70,81,84,95,115,123,153,190],"number":[55],"SRAM":[57],"bitcells":[58],"compared":[59],"encoding":[64],"without":[65],"loss":[66],"accuracy":[68,145,203],"in":[69,109],"MAC":[71,86,158],"operation.":[72],"We":[73],"optimal":[76],"sampling":[77],"time":[78],"improve":[80],"linearity":[82,121],"TC-IMC":[85,102,117,155],"operation":[87],"maximum":[89],"signal":[90],"margin":[91],"(SM)":[92],"based":[93],"on":[94,129],"detailed":[96],"nonlinearity":[97],"analysis":[98],"8T":[100],"SRAM-based":[101],"architecture.":[103],"test":[105,141],"chip":[106],"measurement":[107],"results":[108,128],"180":[110],"nm":[111],"process":[112,198],"show":[113,143],"that":[114],"has":[118],"72%":[119],"better":[120],"than":[122],"traditional":[124],"IMC.":[125],"measured":[127],"100":[130],"Modified":[131],"National":[132],"Institute":[133],"Standards":[135],"and":[136,139,148,180,194,206],"Technology":[137],"(MNIST)":[138],"CIFAR-10":[140,195],"images":[142,196],"97%":[147],"87%,":[149],"respectively.":[150,208],"addition,":[152],"achieves":[157],"compute":[159],"latency":[160],"25":[162],"ns,":[163],"GOPS/kb":[164],"(normalized":[165],"1":[167,176],"b":[168],"<inline-formula":[169],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[170],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[171],"<tex-math":[172],"notation=\"LaTeX\">$\\times":[173],"$":[174],"</tex-math></inline-formula>":[175],"b)":[177],"29.8,":[179],"energy":[181],"efficiency":[182],"2.3":[184],"TOPS/W.":[185],"simulation":[187],"result":[188],"entire":[191],"10000":[192],"MNIST":[193],"considering":[197],"variation":[199],"effects":[200],"shows":[201],"98.7%":[205],"90.4%,":[207]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}