{"id":"https://openalex.org/W3020759376","doi":"https://doi.org/10.1109/aicas48895.2020.9073848","title":"XNORAM: An Efficient Computing-in-Memory Architecture for Binary Convolutional Neural Networks with Flexible Dataflow Mapping","display_name":"XNORAM: An Efficient Computing-in-Memory Architecture for Binary Convolutional Neural Networks with Flexible Dataflow Mapping","publication_year":2020,"publication_date":"2020-04-24","ids":{"openalex":"https://openalex.org/W3020759376","doi":"https://doi.org/10.1109/aicas48895.2020.9073848","mag":"3020759376"},"language":"en","primary_location":{"id":"doi:10.1109/aicas48895.2020.9073848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas48895.2020.9073848","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)","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/A5047073566","display_name":"Shiwei Liu","orcid":"https://orcid.org/0000-0002-0564-4900"},"institutions":[{"id":"https://openalex.org/I4391767673","display_name":"State Key Laboratory of ASIC and System","ror":"https://ror.org/01mamgv83","country_code":null,"type":"facility","lineage":["https://openalex.org/I24943067","https://openalex.org/I4391767673"]}],"countries":[],"is_corresponding":true,"raw_author_name":"Shiwei Liu","raw_affiliation_strings":["State Key Laboratory of ASIC and System"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC and System","institution_ids":["https://openalex.org/I4391767673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037971089","display_name":"Haozhe Zhu","orcid":"https://orcid.org/0000-0002-6412-3996"},"institutions":[{"id":"https://openalex.org/I4391767673","display_name":"State Key Laboratory of ASIC and System","ror":"https://ror.org/01mamgv83","country_code":null,"type":"facility","lineage":["https://openalex.org/I24943067","https://openalex.org/I4391767673"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Haozhe Zhu","raw_affiliation_strings":["State Key Laboratory of ASIC and System"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC and System","institution_ids":["https://openalex.org/I4391767673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051205321","display_name":"Chixiao Chen","orcid":"https://orcid.org/0000-0002-5980-4236"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chixiao Chen","raw_affiliation_strings":["Shanghai Engineering Research Center for AI & Robotics, Fudan University, Shanghai"],"affiliations":[{"raw_affiliation_string":"Shanghai Engineering Research Center for AI & Robotics, Fudan University, Shanghai","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100414906","display_name":"Lihua Zhang","orcid":"https://orcid.org/0000-0003-0467-4347"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lihua Zhang","raw_affiliation_strings":["Shanghai Engineering Research Center for AI & Robotics, Fudan University, Shanghai"],"affiliations":[{"raw_affiliation_string":"Shanghai Engineering Research Center for AI & Robotics, Fudan University, Shanghai","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069699411","display_name":"Cong Shi","orcid":"https://orcid.org/0000-0003-0040-4411"},"institutions":[{"id":"https://openalex.org/I4391767673","display_name":"State Key Laboratory of ASIC and System","ror":"https://ror.org/01mamgv83","country_code":null,"type":"facility","lineage":["https://openalex.org/I24943067","https://openalex.org/I4391767673"]}],"countries":[],"is_corresponding":false,"raw_author_name":"C.-J. Richard Shi","raw_affiliation_strings":["State Key Laboratory of ASIC and System"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC and System","institution_ids":["https://openalex.org/I4391767673"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5047073566"],"corresponding_institution_ids":["https://openalex.org/I4391767673"],"apc_list":null,"apc_paid":null,"fwci":0.2931,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.54802716,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"21","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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/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/T12676","display_name":"Machine Learning and ELM","score":0.9987000226974487,"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/dataflow","display_name":"Dataflow","score":0.8923291563987732},{"id":"https://openalex.org/keywords/xnor-gate","display_name":"XNOR gate","score":0.829775869846344},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7706902027130127},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7340971231460571},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.42232197523117065},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41195663809776306},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.40364813804626465},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.38151904940605164},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3556298017501831},{"id":"https://openalex.org/keywords/logic-gate","display_name":"Logic gate","score":0.25966280698776245},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23168176412582397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.14483079314231873}],"concepts":[{"id":"https://openalex.org/C96324660","wikidata":"https://www.wikidata.org/wiki/Q205446","display_name":"Dataflow","level":2,"score":0.8923291563987732},{"id":"https://openalex.org/C57684291","wikidata":"https://www.wikidata.org/wiki/Q1336142","display_name":"XNOR gate","level":4,"score":0.829775869846344},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7706902027130127},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7340971231460571},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.42232197523117065},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41195663809776306},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.40364813804626465},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.38151904940605164},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3556298017501831},{"id":"https://openalex.org/C131017901","wikidata":"https://www.wikidata.org/wiki/Q170451","display_name":"Logic gate","level":2,"score":0.25966280698776245},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23168176412582397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.14483079314231873},{"id":"https://openalex.org/C124296912","wikidata":"https://www.wikidata.org/wiki/Q575178","display_name":"NAND gate","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aicas48895.2020.9073848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas48895.2020.9073848","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8899999856948853}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1999085092","https://openalex.org/W2062143991","https://openalex.org/W2194775991","https://openalex.org/W2300242332","https://openalex.org/W2405920868","https://openalex.org/W2745228312","https://openalex.org/W2792893539","https://openalex.org/W2793168176","https://openalex.org/W2894696827","https://openalex.org/W2920866490","https://openalex.org/W2921013323","https://openalex.org/W2965129158","https://openalex.org/W6687483927","https://openalex.org/W6698200048","https://openalex.org/W6714058667","https://openalex.org/W6760218904"],"related_works":["https://openalex.org/W2108719777","https://openalex.org/W2910771446","https://openalex.org/W2966758645","https://openalex.org/W2559054477","https://openalex.org/W2122693377","https://openalex.org/W2293118914","https://openalex.org/W2998381397","https://openalex.org/W4236419692","https://openalex.org/W1998888015","https://openalex.org/W2896822060"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"an":[3],"energy-efficient":[4],"computing-inmemory":[5],"architecture":[6],"for":[7],"binary":[8],"convolutional":[9,45],"neural":[10,46],"networks,":[11,47],"called":[12],"XNORAM,":[13],"is":[14,51,91],"proposed.":[15],"The":[16],"XNORAM":[17,29,54,69],"employs":[18],"6T":[19],"feature":[20],"cells":[21,25],"and":[22,86,99],"10T":[23],"weight":[24],"to":[26,55,109],"form":[27],"one":[28],"column.":[30,38],"Multiplexed":[31],"XNOR":[32],"operations":[33],"are":[34],"embedded":[35],"in":[36,44,71],"each":[37],"To":[39,61],"address":[40],"the":[41,57,63,94,110],"data":[42,59],"reuse":[43],"flexible":[48],"dataflow":[49],"mapping":[50],"supported":[52],"on":[53,93,114],"minimize":[56],"external":[58],"access.":[60],"verify":[62],"architecture,":[64],"we":[65],"design":[66,95],"a":[67,77],"4-KB":[68],"prototype":[70],"65nm":[72],"CMOS":[73],"technology.":[74],"It":[75],"achieves":[76],"throughput":[78],"of":[79],"18.":[80],"5GOPs":[81],"at":[82],"100-MHz":[83],"clock":[84],"rate":[85],"1.0-V":[87],"power":[88],"supply.":[89],"XNOR-AlexNet":[90],"performed":[92],"achieving":[96],"39.86":[97],"TOPS/W":[98],"4.63":[100],"GOPS/KB":[101],"utilization":[102],"with":[103],"only":[104],"1.3%":[105],"accuracy":[106],"loss":[107],"comparing":[108],"original":[111],"XNOR-Net":[112],"result":[113],"GPUs.":[115]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
