{"id":"https://openalex.org/W4377969808","doi":"https://doi.org/10.1109/isqed57927.2023.10129338","title":"Heterogeneous Multi-Functional Look-Up-Table-based Processing-in-Memory Architecture for Deep Learning Acceleration","display_name":"Heterogeneous Multi-Functional Look-Up-Table-based Processing-in-Memory Architecture for Deep Learning Acceleration","publication_year":2023,"publication_date":"2023-04-05","ids":{"openalex":"https://openalex.org/W4377969808","doi":"https://doi.org/10.1109/isqed57927.2023.10129338"},"language":"en","primary_location":{"id":"doi:10.1109/isqed57927.2023.10129338","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed57927.2023.10129338","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/A5073660180","display_name":"Sathwika Bavikadi","orcid":"https://orcid.org/0000-0002-1430-5070"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sathwika Bavikadi","raw_affiliation_strings":["George Mason University,Department of Electrical and Computer Engineering,Fairfax,VA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University,Department of Electrical and Computer Engineering,Fairfax,VA,USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021789107","display_name":"Purab Ranjan Sutradhar","orcid":"https://orcid.org/0000-0003-3155-1115"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Purab Ranjan Sutradhar","raw_affiliation_strings":["Rochester Institute of Technology,Department of Computer Engineering,Rochester,NY,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology,Department of Computer Engineering,Rochester,NY,USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004368293","display_name":"Amlan Ganguly","orcid":"https://orcid.org/0000-0001-7354-7873"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amlan Ganguly","raw_affiliation_strings":["Rochester Institute of Technology,Department of Computer Engineering,Rochester,NY,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology,Department of Computer Engineering,Rochester,NY,USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047725314","display_name":"Sai Manoj Pudukotai Dinakarrao","orcid":"https://orcid.org/0000-0002-4417-2387"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sai Manoj Pudukotai Dinakarrao","raw_affiliation_strings":["George Mason University,Department of Electrical and Computer Engineering,Fairfax,VA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University,Department of Electrical and Computer Engineering,Fairfax,VA,USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7043,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.89850111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9991000294685364,"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"}},{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.8380071520805359},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.6399478912353516},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5699729919433594},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5668801665306091},{"id":"https://openalex.org/keywords/memory-bandwidth","display_name":"Memory bandwidth","score":0.46561312675476074},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.4654653072357178},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.45587271451950073},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4230548143386841},{"id":"https://openalex.org/keywords/lookup-table","display_name":"Lookup table","score":0.421800434589386},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.4107925295829773},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.36983925104141235},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.342621386051178},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20458713173866272},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10779473185539246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8380071520805359},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.6399478912353516},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5699729919433594},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5668801665306091},{"id":"https://openalex.org/C188045654","wikidata":"https://www.wikidata.org/wiki/Q17148339","display_name":"Memory bandwidth","level":2,"score":0.46561312675476074},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4654653072357178},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.45587271451950073},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4230548143386841},{"id":"https://openalex.org/C134835016","wikidata":"https://www.wikidata.org/wiki/Q690265","display_name":"Lookup table","level":2,"score":0.421800434589386},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.4107925295829773},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.36983925104141235},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.342621386051178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20458713173866272},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10779473185539246},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isqed57927.2023.10129338","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed57927.2023.10129338","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":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8899999856948853}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2007339694","https://openalex.org/W2014555481","https://openalex.org/W2048266589","https://openalex.org/W2112796928","https://openalex.org/W2154991996","https://openalex.org/W2194775991","https://openalex.org/W2332254524","https://openalex.org/W2545376626","https://openalex.org/W2606722458","https://openalex.org/W2613989746","https://openalex.org/W2765234579","https://openalex.org/W2801000640","https://openalex.org/W2809205380","https://openalex.org/W2933452742","https://openalex.org/W2942478991","https://openalex.org/W2946829484","https://openalex.org/W2995188280","https://openalex.org/W3045328293","https://openalex.org/W3083505238","https://openalex.org/W3118608800","https://openalex.org/W3173995779","https://openalex.org/W3185946996","https://openalex.org/W4285140031","https://openalex.org/W4293254947","https://openalex.org/W4298168912","https://openalex.org/W4313496376"],"related_works":["https://openalex.org/W2792080776","https://openalex.org/W2788663687","https://openalex.org/W1997955449","https://openalex.org/W2031026393","https://openalex.org/W2904665340","https://openalex.org/W2292897598","https://openalex.org/W4310814620","https://openalex.org/W2493588167","https://openalex.org/W2891552639","https://openalex.org/W4285189103"],"abstract_inverted_index":{"Emerging":[0],"applications":[1,24],"including":[2,133],"deep":[3],"neural":[4,9],"networks":[5,10],"(DNNs)":[6],"and":[7,20,30,39,55,75,82,136,174,190,201,212,236],"convolutional":[8],"(CNNs)":[11],"employ":[12],"massive":[13],"amounts":[14],"of":[15,57,150,231],"data":[16,21,35],"to":[17,27,50,155,162,171],"perform":[18,130],"computations":[19],"analysis.":[22],"Such":[23],"often":[25],"lead":[26],"resource":[28],"constraints":[29],"impose":[31],"large":[32],"overheads":[33],"in":[34,86,98],"movement":[36],"between":[37,69],"memory":[38],"compute":[40],"units.":[41],"Several":[42],"architectures":[43,65],"such":[44,198,208],"as":[45,192,194,199,209],"Processing-in-Memory":[46],"(PIM)":[47],"are":[48,139,148],"introduced":[49],"alleviate":[51],"the":[52,62,80,145,160,225],"bandwidth":[53],"bottlenecks":[54],"inefficiency":[56],"traditional":[58],"computing":[59],"architectures.":[60],"However,":[61],"existing":[63],"PIM":[64,96,244],"represent":[66],"a":[67,91,105,114,229,241],"trade-off":[68],"power,":[70],"performance,":[71],"area,":[72],"energy":[73,234],"efficiency,":[74],"programmability.":[76],"To":[77],"better":[78],"achieve":[79],"energy-efficiency":[81],"flexibility":[83],"criteria":[84],"simultaneously":[85,158],"hardware":[87],"accelerators,":[88],"we":[89,178],"introduce":[90],"multi-functional":[92],"look-up-table":[93],"(LUT)-based":[94],"reconfigurable":[95,124],"architecture":[97,103,227],"this":[99],"work.":[100],"The":[101,126],"proposed":[102,127,146,226],"is":[104,222],"many-core":[106],"architecture,":[107],"each":[108],"core":[109],"comprises":[110],"processing":[111],"elements":[112],"(PEs),":[113],"stand-alone":[115],"processor":[116],"with":[117],"programmable":[118],"functional":[119],"units":[120],"built":[121],"using":[122],"high-speed":[123],"LUTs.":[125],"LUTs":[128,147,165],"can":[129,184],"various":[131,206],"operations,":[132],"convolutional,":[134],"pooling,":[135],"activation":[137,196],"that":[138,219],"required":[140],"for":[141,166,188],"CNN":[142],"acceleration.":[143],"Additionally,":[144],"capable":[149],"providing":[151],"multiple":[152],"outputs":[153,187],"relating":[154],"different":[156,164,167],"functionalities":[157],"without":[159],"need":[161],"design":[163,180],"functionalities.":[168],"This":[169],"leads":[170],"optimized":[172],"area":[173],"power":[175],"overheads.":[176],"Furthermore,":[177],"also":[179],"special-function":[181],"LUTs,":[182],"which":[183],"provide":[185],"simultaneous":[186],"multiplication":[189],"accumulation":[191],"well":[193],"special":[195],"functions":[197],"hyperbolics":[200],"sigmoids.":[202],"We":[203],"have":[204,217],"evaluated":[205],"CNNs":[207],"LeNet,":[210],"AlexNet,":[211],"ResNet18,34,50.":[213],"Our":[214],"experimental":[215],"results":[216],"demonstrated":[218],"when":[220],"AlexNet":[221],"implemented":[223],"on":[224],"shows":[228],"maximum":[230],"200\u00d7":[232],"higher":[233,238],"efficiency":[235],"1.5\u00d7":[237],"throughput":[239],"than":[240],"DRAM-based":[242],"LUT-based":[243],"architecture.":[245]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}