{"id":"https://openalex.org/W4378800932","doi":"https://doi.org/10.1145/3583781.3590306","title":"SRAM-Based Processing-In-Memory Design with Kullback-Leibler Divergence-Based Dynamic Precision Quantization","display_name":"SRAM-Based Processing-In-Memory Design with Kullback-Leibler Divergence-Based Dynamic Precision Quantization","publication_year":2023,"publication_date":"2023-05-31","ids":{"openalex":"https://openalex.org/W4378800932","doi":"https://doi.org/10.1145/3583781.3590306"},"language":"en","primary_location":{"id":"doi:10.1145/3583781.3590306","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583781.3590306","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2023","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/A5101551160","display_name":"Yanjun Li","orcid":"https://orcid.org/0009-0008-5903-1465"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yanjun Li","raw_affiliation_strings":["Pimchip Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0008-5903-1465","affiliations":[{"raw_affiliation_string":"Pimchip Technology, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044556337","display_name":"Chunshan Zu","orcid":"https://orcid.org/0009-0002-9569-9522"},"institutions":[{"id":"https://openalex.org/I4210100976","display_name":"BOE Technology Group (China)","ror":"https://ror.org/01cwwvj38","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210100976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunshan Zu","raw_affiliation_strings":["BOE Technology Group Co., LTD., Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-9569-9522","affiliations":[{"raw_affiliation_string":"BOE Technology Group Co., LTD., Beijing, China","institution_ids":["https://openalex.org/I4210100976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103009945","display_name":"Bingqian Wang","orcid":"https://orcid.org/0009-0004-3217-781X"},"institutions":[{"id":"https://openalex.org/I4210100976","display_name":"BOE Technology Group (China)","ror":"https://ror.org/01cwwvj38","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210100976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingqian Wang","raw_affiliation_strings":["BOE Technology Group Co., LTD., Beijing, China"],"raw_orcid":"https://orcid.org/0009-0004-3217-781X","affiliations":[{"raw_affiliation_string":"BOE Technology Group Co., LTD., Beijing, China","institution_ids":["https://openalex.org/I4210100976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103138440","display_name":"Zhenhua Zhu","orcid":"https://orcid.org/0009-0007-9259-7180"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Zhu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-9259-7180","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101538623","display_name":"Yaojun Zhang","orcid":"https://orcid.org/0000-0002-0125-2221"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yaojun Zhang","raw_affiliation_strings":["Pimchip Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0125-2221","affiliations":[{"raw_affiliation_string":"Pimchip Technology, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101496096","display_name":"Ran Duan","orcid":"https://orcid.org/0009-0003-9986-0229"},"institutions":[{"id":"https://openalex.org/I4210100976","display_name":"BOE Technology Group (China)","ror":"https://ror.org/01cwwvj38","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210100976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Duan","raw_affiliation_strings":["BOE Technology Group Co., LTD., Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-9986-0229","affiliations":[{"raw_affiliation_string":"BOE Technology Group Co., LTD., Beijing, China","institution_ids":["https://openalex.org/I4210100976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451305","display_name":"Bing Li","orcid":"https://orcid.org/0000-0003-0732-2267"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Li","raw_affiliation_strings":["Capital Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0732-2267","affiliations":[{"raw_affiliation_string":"Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043075091","display_name":"Bonan Yan","orcid":"https://orcid.org/0000-0002-3052-9330"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bonan Yan","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3052-9330","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5101551160"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1278,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.41146869,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"189","last_page":"192"},"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":0.9994000196456909,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9986000061035156,"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/static-random-access-memory","display_name":"Static random-access memory","score":0.8905936479568481},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.7946339249610901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7223526239395142},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5454027652740479},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5077279806137085},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4244588017463684},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.41296544671058655},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3578212559223175},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35541674494743347},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2981255054473877},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.22214332222938538}],"concepts":[{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.8905936479568481},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.7946339249610901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7223526239395142},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5454027652740479},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5077279806137085},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4244588017463684},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.41296544671058655},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3578212559223175},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35541674494743347},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2981255054473877},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.22214332222938538},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583781.3590306","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583781.3590306","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2023","raw_type":"proceedings-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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2600072075","https://openalex.org/W2966524683","https://openalex.org/W3004127905","https://openalex.org/W3091895175","https://openalex.org/W3131573445","https://openalex.org/W3197618653","https://openalex.org/W4302391768"],"related_works":["https://openalex.org/W4386245174","https://openalex.org/W4200132709","https://openalex.org/W3204400881","https://openalex.org/W3214410901","https://openalex.org/W3204296682","https://openalex.org/W3183118997","https://openalex.org/W2917767146","https://openalex.org/W3176282186","https://openalex.org/W2973622361","https://openalex.org/W4387489555"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2],"networks":[3],"(CNNs)":[4],"are":[5,23],"widely":[6],"used":[7],"in":[8,98,112],"Artificial":[9],"Intelligence":[10],"of":[11,29,34,49,61,86],"Things":[12],"(AIoT)":[13],"systems.":[14],"Limited":[15],"by":[16],"power":[17,54],"and":[18,53,92,133],"area,":[19],"conventional":[20],"edge":[21,46,64,117],"devices":[22,47],"insufficient":[24],"to":[25,42,128,166],"handle":[26],"the":[27,59,84,94,123,157,168],"cost":[28],"CNN":[30,44,88],"computation.":[31],"The":[32,79,105],"idea":[33],"SRAM":[35],"based":[36],"Processing-In-Memory":[37],"(SRAM-PIM)":[38],"has":[39,109],"been":[40,110],"advocated":[41],"implement":[43],"on":[45,63,90,116],"because":[48],"its":[50],"high":[51],"area":[52],"efficiency.":[55],"To":[56],"further":[57],"excavate":[58],"potential":[60],"SRAM-PIM":[62,70,95,107],"inferences,":[65],"this":[66],"paper":[67],"proposes":[68],"an":[69],"design":[71,108,125],"with":[72,138,145],"Kullback-Leibler":[73],"(KL)":[74],"divergence-based":[75],"dynamic":[76,140,148,159],"precision":[77,103,141,160],"quantization.":[78],"proposed":[80,106,158],"quantization":[81,149,155,161,170],"method":[82,150,162],"decouples":[83],"effect":[85],"different":[87],"layers":[89],"accuracy":[91,135],"introduces":[93],"hardware":[96],"performance":[97],"quantization,":[99],"realizing":[100],"SRAM-PIM-aware":[101],"layer-wise":[102],"adjustment.":[104],"applied":[111],"image":[113],"classification":[114],"tasks":[115],"devices.":[118],"Our":[119],"evaluation":[120],"shows":[121],"that":[122,151],"implemented":[124],"achieves":[126],"up":[127],"2.03x":[129],"energy":[130],"efficiency":[131],"improvement":[132,136],"2.54%":[134],"compared":[137],"existing":[139,146],"PIM":[142],"design.":[143],"Compared":[144],"reinforcement-learning-based":[147],"requires":[152],"several":[153],"hours":[154],"time,":[156],"takes":[163],"only":[164],"26.28us":[165],"get":[167],"optimal":[169],"results.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}