{"id":"https://openalex.org/W4377969868","doi":"https://doi.org/10.1109/isqed57927.2023.10129301","title":"AGNI: In-Situ, Iso-Latency Stochastic-to-Binary Number Conversion for In-DRAM Deep Learning","display_name":"AGNI: In-Situ, Iso-Latency Stochastic-to-Binary Number Conversion for In-DRAM Deep Learning","publication_year":2023,"publication_date":"2023-04-05","ids":{"openalex":"https://openalex.org/W4377969868","doi":"https://doi.org/10.1109/isqed57927.2023.10129301"},"language":"en","primary_location":{"id":"doi:10.1109/isqed57927.2023.10129301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed57927.2023.10129301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 24th International Symposium on Quality Electronic Design (ISQED)","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/A5041592711","display_name":"Supreeth Mysore Shivanandamurthy","orcid":null},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Supreeth Mysore Shivanandamurthy","raw_affiliation_strings":["University of Kentucky,Department of Electrical and Computer Engineering,Lexington,KY,USA,40506"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kentucky,Department of Electrical and Computer Engineering,Lexington,KY,USA,40506","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073706633","display_name":"Sairam Sri Vatsavai","orcid":"https://orcid.org/0000-0003-1847-3976"},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sairam Sri Vatsavai","raw_affiliation_strings":["University of Kentucky,Department of Electrical and Computer Engineering,Lexington,KY,USA,40506"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kentucky,Department of Electrical and Computer Engineering,Lexington,KY,USA,40506","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083056788","display_name":"Ishan Thakkar","orcid":"https://orcid.org/0000-0002-7289-1530"},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ishan Thakkar","raw_affiliation_strings":["University of Kentucky,Department of Electrical and Computer Engineering,Lexington,KY,USA,40506"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kentucky,Department of Electrical and Computer Engineering,Lexington,KY,USA,40506","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022120826","display_name":"Sayed Ahmad Salehi","orcid":null},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sayed Ahmad Salehi","raw_affiliation_strings":["University of Kentucky,Department of Electrical and Computer Engineering,Lexington,KY,USA,40506"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kentucky,Department of Electrical and Computer Engineering,Lexington,KY,USA,40506","institution_ids":["https://openalex.org/I143302722"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I143302722"],"apc_list":null,"apc_paid":null,"fwci":1.5411,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78589268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","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"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9951000213623047,"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/dram","display_name":"Dram","score":0.8614641427993774},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7331103086471558},{"id":"https://openalex.org/keywords/cas-latency","display_name":"CAS latency","score":0.5644398927688599},{"id":"https://openalex.org/keywords/stochastic-computing","display_name":"Stochastic computing","score":0.5558491945266724},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.5074593424797058},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.46415719389915466},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.44323021173477173},{"id":"https://openalex.org/keywords/sense-amplifier","display_name":"Sense amplifier","score":0.42126721143722534},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.39874112606048584},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.38275930285453796},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.328784704208374},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3282572627067566},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22495704889297485},{"id":"https://openalex.org/keywords/memory-controller","display_name":"Memory controller","score":0.17825615406036377},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12154731154441833},{"id":"https://openalex.org/keywords/semiconductor-memory","display_name":"Semiconductor memory","score":0.10532668232917786},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08766719698905945}],"concepts":[{"id":"https://openalex.org/C7366592","wikidata":"https://www.wikidata.org/wiki/Q1255620","display_name":"Dram","level":2,"score":0.8614641427993774},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7331103086471558},{"id":"https://openalex.org/C189930140","wikidata":"https://www.wikidata.org/wiki/Q1112878","display_name":"CAS latency","level":4,"score":0.5644398927688599},{"id":"https://openalex.org/C2780971903","wikidata":"https://www.wikidata.org/wiki/Q2933705","display_name":"Stochastic computing","level":3,"score":0.5558491945266724},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.5074593424797058},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.46415719389915466},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.44323021173477173},{"id":"https://openalex.org/C32666082","wikidata":"https://www.wikidata.org/wiki/Q7450979","display_name":"Sense amplifier","level":3,"score":0.42126721143722534},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.39874112606048584},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.38275930285453796},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.328784704208374},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3282572627067566},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22495704889297485},{"id":"https://openalex.org/C100800780","wikidata":"https://www.wikidata.org/wiki/Q1175867","display_name":"Memory controller","level":3,"score":0.17825615406036377},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12154731154441833},{"id":"https://openalex.org/C98986596","wikidata":"https://www.wikidata.org/wiki/Q1143031","display_name":"Semiconductor memory","level":2,"score":0.10532668232917786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08766719698905945},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isqed57927.2023.10129301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed57927.2023.10129301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 24th International Symposium on Quality Electronic Design (ISQED)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2048266589","https://openalex.org/W2097117768","https://openalex.org/W2158620667","https://openalex.org/W2285660444","https://openalex.org/W2290548492","https://openalex.org/W2508602506","https://openalex.org/W2518281301","https://openalex.org/W2624299682","https://openalex.org/W2798554798","https://openalex.org/W2809205380","https://openalex.org/W2904200161","https://openalex.org/W2904299207","https://openalex.org/W2920866490","https://openalex.org/W3000301330","https://openalex.org/W3016903199","https://openalex.org/W3043216033","https://openalex.org/W3118013838","https://openalex.org/W3188529796","https://openalex.org/W3191222816","https://openalex.org/W3193414970","https://openalex.org/W3209151516","https://openalex.org/W4205117993","https://openalex.org/W4253877280","https://openalex.org/W6662587704","https://openalex.org/W6674914833","https://openalex.org/W6683227110","https://openalex.org/W6756601136","https://openalex.org/W6756864557"],"related_works":["https://openalex.org/W2154176871","https://openalex.org/W2740703383","https://openalex.org/W4293430534","https://openalex.org/W2342813629","https://openalex.org/W1607126780","https://openalex.org/W3150934690","https://openalex.org/W2335743642","https://openalex.org/W4297812927","https://openalex.org/W2800412005","https://openalex.org/W2900372418"],"abstract_inverted_index":{"Recent":[0],"years":[1],"have":[2,50,62],"seen":[3],"a":[4,154],"rapid":[5],"increase":[6],"in":[7,10,66,132,144,168,220,232,262],"research":[8],"activity":[9],"the":[11,19,30,56,73,88,138,181,254],"field":[12],"of":[13,23,33,75,90,140,192,196,216],"DRAM-based":[14,42],"Processing-In-Memory":[15],"(PIM)":[16],"accelerators,":[17],"where":[18],"analog":[20],"computing":[21],"capability":[22],"DRAM":[24,34,133,169],"is":[25],"employed":[26],"by":[27],"minimally":[28],"changing":[29],"inherent":[31],"structure":[32],"peripherals":[35,170],"to":[36,72,78,100,187,237,251,256],"accelerate":[37],"various":[38],"data-centric":[39],"applications.":[40],"Several":[41],"PIM":[43],"accelerators":[44,57],"for":[45,94,157],"Convolutional":[46],"Neural":[47],"Networks":[48],"(CNNs)":[49],"also":[51,128],"been":[52],"reported.":[53],"Among":[54],"these,":[55],"leveraging":[58],"in-DRAM":[59,91,114,126,158,239],"stochastic":[60,76,92,99,142],"arithmetic":[61,77,93,143],"shown":[63],"manifold":[64],"improvements":[65],"processing":[67],"latency":[68],"and":[69,121,176,179,228],"throughput,":[70],"due":[71],"ability":[74],"convert":[79],"multiplications":[80],"into":[81],"simple":[82],"bit-wise":[83],"logical":[84],"AND":[85],"operations.":[86],"However,":[87],"use":[89],"CNN":[95,267],"acceleration":[96],"requires":[97],"frequent":[98],"binary":[101,190],"number":[102,160],"conversions.":[103],"For":[104],"that,":[105],"prior":[106,244],"works":[107],"employ":[108],"full":[109],"adder-based":[110],"or":[111],"serial":[112],"counter-based":[113],"circuits.":[115],"These":[116,246],"circuits":[117,242],"consume":[118],"large":[119],"area":[120,233],"incur":[122],"long":[123],"latency.":[124,201],"Their":[125],"implementations":[127],"require":[129],"heavy":[130],"modifications":[131,167],"peripherals,":[134],"which":[135],"significantly":[136],"diminishes":[137],"benefits":[139,248],"using":[141,171],"these":[145,149],"accelerators.":[146],"To":[147],"address":[148],"shortcomings,":[150],"this":[151],"paper":[152],"presents":[153],"new":[155],"substrate":[156],"stochastic-to-binary":[159,240],"conversion":[161,191,241],"called":[162],"AGNI.":[163],"AGNI":[164,212],"makes":[165],"minor":[166],"pass":[172],"transistors,":[173],"capacitors,":[174],"encoders,":[175],"charge":[177],"pumps,":[178],"re-purposes":[180],"sense":[182],"amplifiers":[183],"as":[184],"voltage":[185],"comparators,":[186],"enable":[188],"in-situ":[189],"input":[193],"statistic":[194],"operands":[195],"different":[197],"sizes":[198],"with":[199],"iso":[200],"Our":[202],"evaluations,":[203],"based":[204],"on":[205],"detailed":[206],"SPICE":[207],"simulations":[208],"(https://github.com/uky-UCAT/AGNI_SPICE.git),":[209],"show":[210],"that":[211],"can":[213],"achieve":[214,257],"savings":[215],"at":[217,222,229,253,258],"least":[218,223,230,259],"8\u00d7":[219],"area,":[221],"28\u00d7":[224],"energy-delay":[225],"product":[226],"(EDP),":[227],"21":[231],"\u00d7":[234],"latency,":[235],"compared":[236],"two":[238],"from":[243],"works.":[245],"circuit-level":[247],"are":[249],"demonstrated":[250],"propagate":[252],"system-level":[255],"3.9\u00d7":[260],"gain":[261],"performance":[263],"across":[264],"four":[265],"deep":[266],"models.":[268]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-30T07:30:35.949966","created_date":"2025-10-10T00:00:00"}
