{"id":"https://openalex.org/W4200161924","doi":"https://doi.org/10.1109/a-sscc53895.2021.9634800","title":"Realizing Direct Convolution in Memory with Systolic-RAM","display_name":"Realizing Direct Convolution in Memory with Systolic-RAM","publication_year":2021,"publication_date":"2021-11-07","ids":{"openalex":"https://openalex.org/W4200161924","doi":"https://doi.org/10.1109/a-sscc53895.2021.9634800"},"language":"en","primary_location":{"id":"doi:10.1109/a-sscc53895.2021.9634800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/a-sscc53895.2021.9634800","pdf_url":null,"source":{"id":"https://openalex.org/S4363608516","display_name":"2021 IEEE Asian Solid-State Circuits Conference (A-SSCC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Asian Solid-State Circuits Conference (A-SSCC)","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/A5005624193","display_name":"Jacob N. Rohan","orcid":"https://orcid.org/0000-0002-2916-1663"},"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":"Jacob N. Rohan","raw_affiliation_strings":["The University of Texas at Austin, Austin, TX"],"affiliations":[{"raw_affiliation_string":"The 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":["The University of Texas at Austin, Austin, TX"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Austin, Austin, TX","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005624193"],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":0.4327,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46119276,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"3"},"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":0.9994999766349792,"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/T12676","display_name":"Machine Learning and ELM","score":0.9977999925613403,"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/static-random-access-memory","display_name":"Static random-access memory","score":0.7505339980125427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7325596809387207},{"id":"https://openalex.org/keywords/memory-refresh","display_name":"Memory refresh","score":0.597287654876709},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5814284086227417},{"id":"https://openalex.org/keywords/multiplication","display_name":"Multiplication (music)","score":0.5744404792785645},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5439456105232239},{"id":"https://openalex.org/keywords/matrix-multiplication","display_name":"Matrix multiplication","score":0.5110751390457153},{"id":"https://openalex.org/keywords/systolic-array","display_name":"Systolic array","score":0.49991440773010254},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.48740819096565247},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.4836336374282837},{"id":"https://openalex.org/keywords/semiconductor-memory","display_name":"Semiconductor memory","score":0.30404454469680786},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.286318302154541},{"id":"https://openalex.org/keywords/very-large-scale-integration","display_name":"Very-large-scale integration","score":0.282274067401886},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.27945464849472046},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.2783086895942688},{"id":"https://openalex.org/keywords/computer-memory","display_name":"Computer memory","score":0.1947954297065735},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14934736490249634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12076431512832642},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09116384387016296}],"concepts":[{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.7505339980125427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7325596809387207},{"id":"https://openalex.org/C87907426","wikidata":"https://www.wikidata.org/wiki/Q6815755","display_name":"Memory refresh","level":4,"score":0.597287654876709},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5814284086227417},{"id":"https://openalex.org/C2780595030","wikidata":"https://www.wikidata.org/wiki/Q3860309","display_name":"Multiplication (music)","level":2,"score":0.5744404792785645},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5439456105232239},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.5110751390457153},{"id":"https://openalex.org/C150741067","wikidata":"https://www.wikidata.org/wiki/Q2377218","display_name":"Systolic array","level":3,"score":0.49991440773010254},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.48740819096565247},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.4836336374282837},{"id":"https://openalex.org/C98986596","wikidata":"https://www.wikidata.org/wiki/Q1143031","display_name":"Semiconductor memory","level":2,"score":0.30404454469680786},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.286318302154541},{"id":"https://openalex.org/C14580979","wikidata":"https://www.wikidata.org/wiki/Q876049","display_name":"Very-large-scale integration","level":2,"score":0.282274067401886},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.27945464849472046},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.2783086895942688},{"id":"https://openalex.org/C92855701","wikidata":"https://www.wikidata.org/wiki/Q5830907","display_name":"Computer memory","level":3,"score":0.1947954297065735},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14934736490249634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12076431512832642},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09116384387016296},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/a-sscc53895.2021.9634800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/a-sscc53895.2021.9634800","pdf_url":null,"source":{"id":"https://openalex.org/S4363608516","display_name":"2021 IEEE Asian Solid-State Circuits Conference (A-SSCC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Asian Solid-State Circuits Conference (A-SSCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2899771611","https://openalex.org/W2954580493","https://openalex.org/W6756040250","https://openalex.org/W6765129128","https://openalex.org/W6931634728"],"related_works":["https://openalex.org/W2022229285","https://openalex.org/W46448156","https://openalex.org/W2283084692","https://openalex.org/W2130878144","https://openalex.org/W4232117715","https://openalex.org/W2150609674","https://openalex.org/W3172158163","https://openalex.org/W2138404091","https://openalex.org/W2189053673","https://openalex.org/W3200702775"],"abstract_inverted_index":{"A":[0],"12.8Kbit":[1,104],"Static":[2],"Random":[3],"Access":[4],"Memory":[5],"(SRAM)":[6],"array":[7,77],"is":[8],"demonstrated":[9],"in":[10],"40nm":[11],"CMOS":[12],"for":[13,42,70,109],"charge-domain":[14],"vector-matrix":[15],"multiplication":[16,74],"(VMM).":[17],"While":[18],"conventional":[19],"compute-in-memory":[20],"(CIM)":[21],"approaches":[22],"rely":[23],"on":[24],"the":[25,29,40,66,76],"indirect":[26],"convolution":[27,37,112],"algorithm,":[28],"proposed":[30],"Systolic-RAM":[31],"performs":[32],"a":[33,100],"form":[34],"of":[35,99],"direct":[36],"which":[38],"eliminates":[39],"need":[41],"data":[43,59],"duplication":[44],"and":[45,93,122],"near-memory":[46],"registers.":[47],"For":[48],"this":[49],"purpose,":[50],"bitcells":[51],"feature":[52],"additional":[53],"read/write":[54],"ports":[55],"configured":[56,108],"to":[57,65,87],"move":[58],"directly":[60],"from":[61],"one":[62],"neighboring":[63],"bitcell":[64],"next.":[67],"Circuit":[68],"details":[69],"implementing":[71],"signed":[72],"analog":[73,91],"within":[75],"are":[78,85],"discussed.":[79],"Quantized":[80],"neural":[81],"network":[82],"training":[83],"methods":[84],"used":[86],"effectively":[88],"mitigate":[89],"non-ideal":[90],"effects":[92],"achieve":[94],"test":[95,106],"accuracy":[96],"near":[97],"that":[98],"floating-point":[101],"network.":[102],"The":[103],"VMM":[105],"chip":[107],"8-bit":[110],"5x5":[111],"achieves":[113],"175(113)":[114],"peak(continuous)":[115],"multiply-accumulate":[116],"(MAC)":[117],"operations":[118],"per":[119],"clock":[120],"cycle":[121],"consumes":[123],"3.0mW":[124],"at":[125],"100MHz.":[126]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}