{"id":"https://openalex.org/W4387411256","doi":"https://doi.org/10.1109/esscirc59616.2023.10268726","title":"Compute-MLROM: Compute-in-Multi Level Read Only Memory for Energy Efficient Edge AI Inference Engines","display_name":"Compute-MLROM: Compute-in-Multi Level Read Only Memory for Energy Efficient Edge AI Inference Engines","publication_year":2023,"publication_date":"2023-09-11","ids":{"openalex":"https://openalex.org/W4387411256","doi":"https://doi.org/10.1109/esscirc59616.2023.10268726"},"language":"en","primary_location":{"id":"doi:10.1109/esscirc59616.2023.10268726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/esscirc59616.2023.10268726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESSCIRC 2023- IEEE 49th European Solid State Circuits Conference (ESSCIRC)","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/A5061327392","display_name":"Rishabh Sehgal","orcid":"https://orcid.org/0000-0003-3327-0595"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rishabh Sehgal","raw_affiliation_strings":["University of Texas at Austin,Chandra Family School of Electrical and Computer Engineering,Austin,TX","Chandra Family School of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX"],"affiliations":[{"raw_affiliation_string":"University of Texas at Austin,Chandra Family School of Electrical and Computer Engineering,Austin,TX","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Chandra Family School of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087818397","display_name":"Rishab Mehra","orcid":"https://orcid.org/0000-0001-5194-0279"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rishab Mehra","raw_affiliation_strings":["University of Texas at Austin,Chandra Family School of Electrical and Computer Engineering,Austin,TX","Chandra Family School of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX"],"affiliations":[{"raw_affiliation_string":"University of Texas at Austin,Chandra Family School of Electrical and Computer Engineering,Austin,TX","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Chandra Family School of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078795733","display_name":"Can Ni","orcid":"https://orcid.org/0009-0008-5118-8601"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Can Ni","raw_affiliation_strings":["University of Texas at Austin,Chandra Family School of Electrical and Computer Engineering,Austin,TX","Chandra Family School of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX"],"affiliations":[{"raw_affiliation_string":"University of Texas at Austin,Chandra Family School of Electrical and Computer Engineering,Austin,TX","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Chandra Family School of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003048953","display_name":"Jaydeep P. Kulkarni","orcid":"https://orcid.org/0000-0002-0258-6776"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jaydeep P. Kulkarni","raw_affiliation_strings":["University of Texas at Austin,Chandra Family School of Electrical and Computer Engineering,Austin,TX","Chandra Family School of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX"],"affiliations":[{"raw_affiliation_string":"University of Texas at Austin,Chandra Family School of Electrical and Computer Engineering,Austin,TX","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Chandra Family School of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061327392"],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":1.6892,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.84446351,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"37","last_page":"40"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9990000128746033,"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/computer-science","display_name":"Computer science","score":0.692889392375946},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.5804131031036377},{"id":"https://openalex.org/keywords/pmos-logic","display_name":"PMOS logic","score":0.5488682985305786},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.531629204750061},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.45932623744010925},{"id":"https://openalex.org/keywords/static-random-access-memory","display_name":"Static random-access memory","score":0.4529028832912445},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.45112648606300354},{"id":"https://openalex.org/keywords/resistive-random-access-memory","display_name":"Resistive random-access memory","score":0.4268611669540405},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.42183905839920044},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.4068244695663452},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.36774247884750366},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.28347116708755493},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19322070479393005},{"id":"https://openalex.org/keywords/transistor","display_name":"Transistor","score":0.18483158946037292},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14882495999336243},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13896960020065308}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.692889392375946},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.5804131031036377},{"id":"https://openalex.org/C27050352","wikidata":"https://www.wikidata.org/wiki/Q173605","display_name":"PMOS logic","level":4,"score":0.5488682985305786},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.531629204750061},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.45932623744010925},{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.4529028832912445},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.45112648606300354},{"id":"https://openalex.org/C182019814","wikidata":"https://www.wikidata.org/wiki/Q1143830","display_name":"Resistive random-access memory","level":3,"score":0.4268611669540405},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.42183905839920044},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.4068244695663452},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.36774247884750366},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.28347116708755493},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19322070479393005},{"id":"https://openalex.org/C172385210","wikidata":"https://www.wikidata.org/wiki/Q5339","display_name":"Transistor","level":3,"score":0.18483158946037292},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14882495999336243},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13896960020065308}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/esscirc59616.2023.10268726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/esscirc59616.2023.10268726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESSCIRC 2023- IEEE 49th European Solid State Circuits Conference (ESSCIRC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W3133754064","https://openalex.org/W3134304371","https://openalex.org/W3159353913","https://openalex.org/W4221118949","https://openalex.org/W4294310671","https://openalex.org/W6809622522"],"related_works":["https://openalex.org/W2095795001","https://openalex.org/W2465290883","https://openalex.org/W2003063789","https://openalex.org/W2035078432","https://openalex.org/W1970620885","https://openalex.org/W2545245183","https://openalex.org/W4398784231","https://openalex.org/W4388836178","https://openalex.org/W2031972468","https://openalex.org/W1510452813"],"abstract_inverted_index":{"An":[0],"energy-efficient":[1],"and":[2,69],"high-density":[3],"first-ever":[4],"Read":[5],"Only":[6],"Memory":[7],"(ROM)":[8],"based":[9],"compute-in-memory":[10],"(CIM)":[11],"design":[12],"for":[13,52,78],"edge":[14],"AI":[15],"inference":[16],"is":[17],"demonstrated":[18],"featuring":[19],"1)":[20],"MultiLevel-Cell":[21],"(MLC)":[22],"using":[23],"standard":[24],"via-programed":[25],"ROM":[26],"bitcell;":[27],"2)":[28],"Source-Line":[29],"PMOS":[30],"current":[31],"driving;":[32],"3)":[33],"Auto-scaling":[34],"diode-connected":[35],"current-to-voltage":[36],"(I2V)":[37],"converters;":[38],"4)":[39],"3-b":[40],"ADC":[41],"with":[42,82],"ROM-based":[43],"VREF":[44],"generation;":[45],"5)":[46],"Early":[47],"termination":[48],"of":[49,64,73],"convolution":[50],"operation":[51],"power":[53],"savings.":[54],"A":[55],"65nm":[56],"CMOS":[57],"prototype":[58],"achieves":[59],"a":[60],"state-of-the-art":[61],"energy":[62],"efficiency":[63,72],"~66.21":[65],"to":[66,75,92],"1324.26":[67],"TOPS/W":[68],"an":[70],"area":[71],"~230.2":[74],"4604.":[76],"SGOPS/mm2":[77],"the":[79,83,88,95],"CIFAR-10":[80],"dataset":[81],"ResNet-20":[84],"model.":[85],"It":[86],"advances":[87],"defined":[89],"FoM":[90],"by~2.7X":[91],"3.2X":[93],"over":[94],"prior":[96],"CIM":[97],"designs.":[98]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
