{"id":"https://openalex.org/W2810978387","doi":"https://doi.org/10.1145/3167132.3167174","title":"Low power driven loop tiling for RRAM crossbar-based CNN","display_name":"Low power driven loop tiling for RRAM crossbar-based CNN","publication_year":2018,"publication_date":"2018-04-09","ids":{"openalex":"https://openalex.org/W2810978387","doi":"https://doi.org/10.1145/3167132.3167174","mag":"2810978387"},"language":"en","primary_location":{"id":"doi:10.1145/3167132.3167174","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3167132.3167174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd Annual ACM Symposium on Applied Computing","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/A5066640277","display_name":"Yuanhui Ni","orcid":"https://orcid.org/0000-0002-1286-8128"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanhui Ni","raw_affiliation_strings":["Capital Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026823951","display_name":"Keni Qiu","orcid":"https://orcid.org/0000-0002-5851-777X"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keni Qiu","raw_affiliation_strings":["Capital Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100739110","display_name":"Weiwen Chen","orcid":"https://orcid.org/0000-0002-5275-7975"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwen Chen","raw_affiliation_strings":["Capital Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008190519","display_name":"Lixue Xia","orcid":"https://orcid.org/0000-0002-7731-7028"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixue Xia","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445061","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0001-6108-5157"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3896,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46742307,"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":"375","last_page":"380"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"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":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9945999979972839,"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/crossbar-switch","display_name":"Crossbar switch","score":0.8052289485931396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7999995350837708},{"id":"https://openalex.org/keywords/resistive-random-access-memory","display_name":"Resistive random-access memory","score":0.7779756188392639},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.687309741973877},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6526734828948975},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.5697469711303711},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.5419297218322754},{"id":"https://openalex.org/keywords/electronic-circuit","display_name":"Electronic circuit","score":0.48025253415107727},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.468313068151474},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4539295732975006},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4394243061542511},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.41437017917633057},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.35491329431533813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1408369243144989},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.1318768560886383},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.10454362630844116},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09708809852600098}],"concepts":[{"id":"https://openalex.org/C29984679","wikidata":"https://www.wikidata.org/wiki/Q1929149","display_name":"Crossbar switch","level":2,"score":0.8052289485931396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7999995350837708},{"id":"https://openalex.org/C182019814","wikidata":"https://www.wikidata.org/wiki/Q1143830","display_name":"Resistive random-access memory","level":3,"score":0.7779756188392639},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.687309741973877},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6526734828948975},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.5697469711303711},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.5419297218322754},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.48025253415107727},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.468313068151474},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4539295732975006},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4394243061542511},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.41437017917633057},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.35491329431533813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1408369243144989},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.1318768560886383},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.10454362630844116},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09708809852600098},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3167132.3167174","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3167132.3167174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd Annual ACM Symposium on Applied Computing","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":0.9100000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1993163906","https://openalex.org/W2094756095","https://openalex.org/W2117696986","https://openalex.org/W2152839228","https://openalex.org/W2395491504","https://openalex.org/W2408724663","https://openalex.org/W2466675884","https://openalex.org/W2546299555","https://openalex.org/W2562493617","https://openalex.org/W2605487586","https://openalex.org/W2798808759","https://openalex.org/W2799063839","https://openalex.org/W4254672563"],"related_works":["https://openalex.org/W2145932742","https://openalex.org/W3005999147","https://openalex.org/W3176428941","https://openalex.org/W3089883684","https://openalex.org/W4232634182","https://openalex.org/W4301187613","https://openalex.org/W2923038022","https://openalex.org/W3008646524","https://openalex.org/W4385624997","https://openalex.org/W2593506445"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4],"been":[5],"proposed":[6],"to":[7,11,39],"be":[8],"widely":[9],"adopted":[10],"make":[12],"predictions":[13],"on":[14,78],"a":[15,74],"large":[16],"amount":[17],"of":[18,42,63,87],"data":[19],"in":[20,36,46,52],"modern":[21],"embedded":[22],"systems.":[23],"Multiply":[24],"and":[25,48,66,81],"accumulate":[26],"(MAC)":[27],"operations":[28,45],"serve":[29],"as":[30],"the":[31,40,53,60,70,85],"most":[32],"computationally":[33],"expensive":[34],"portion":[35],"CNN.":[37],"Compared":[38],"manner":[41],"executing":[43],"MAC":[44],"GPU":[47],"FPGA,":[49],"CNN":[50],"implementation":[51],"RRAM":[54],"crossbar-based":[55],"computing":[56],"system":[57],"(RCS)":[58],"demonstrates":[59],"outstanding":[61],"advantages":[62],"high":[64,76],"performance":[65],"low":[67],"power.":[68],"However,":[69],"current":[71],"design":[72],"presents":[73],"very":[75],"overhead":[77],"peripheral":[79],"circuits":[80],"memory":[82],"accesses,":[83],"limiting":[84],"gains":[86],"RCS.":[88]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
