{"id":"https://openalex.org/W4387092396","doi":"https://doi.org/10.1109/access.2023.3319727","title":"Optimization of Microarchitecture and Dataflow for Sparse Tensor CNN Acceleration","display_name":"Optimization of Microarchitecture and Dataflow for Sparse Tensor CNN Acceleration","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387092396","doi":"https://doi.org/10.1109/access.2023.3319727"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3319727","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3319727","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10265240.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10265240.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032761908","display_name":"Ngoc-Son Pham","orcid":"https://orcid.org/0000-0003-1867-1219"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Ngoc-Son Pham","raw_affiliation_strings":["Department of Computer Science and Engineering, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018071173","display_name":"Taeweon Suh","orcid":"https://orcid.org/0000-0002-6377-5482"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Taeweon Suh","raw_affiliation_strings":["Department of Computer Science and Engineering, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032761908"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7379,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7313601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"11","issue":null,"first_page":"108818","last_page":"108832"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9957000017166138,"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":0.9957000017166138,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9787999987602234,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9757999777793884,"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":0.9386563897132874},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8182366490364075},{"id":"https://openalex.org/keywords/microarchitecture","display_name":"Microarchitecture","score":0.7796928882598877},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.6261440515518188},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5875597596168518},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5049734711647034},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0901603102684021}],"concepts":[{"id":"https://openalex.org/C96324660","wikidata":"https://www.wikidata.org/wiki/Q205446","display_name":"Dataflow","level":2,"score":0.9386563897132874},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8182366490364075},{"id":"https://openalex.org/C107598950","wikidata":"https://www.wikidata.org/wiki/Q259864","display_name":"Microarchitecture","level":2,"score":0.7796928882598877},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.6261440515518188},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5875597596168518},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5049734711647034},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0901603102684021},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3319727","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3319727","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10265240.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:84a63b2e7a1a4594bacce365defd682e","is_oa":true,"landing_page_url":"https://doaj.org/article/84a63b2e7a1a4594bacce365defd682e","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 108818-108832 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3319727","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3319727","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10265240.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G4560152605","display_name":null,"funder_award_id":"IO210204-08384-01","funder_id":"https://openalex.org/F4320332195","funder_display_name":"Samsung"},{"id":"https://openalex.org/G5932296353","display_name":null,"funder_award_id":"2022-0-01198","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387092396.pdf","grobid_xml":"https://content.openalex.org/works/W4387092396.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1999085092","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2118884301","https://openalex.org/W2194775991","https://openalex.org/W2289252105","https://openalex.org/W2537959404","https://openalex.org/W2604319603","https://openalex.org/W2613119772","https://openalex.org/W2623629680","https://openalex.org/W2625457103","https://openalex.org/W2794952988","https://openalex.org/W2931118404","https://openalex.org/W2945146780","https://openalex.org/W2950656546","https://openalex.org/W2963363373","https://openalex.org/W2963674932","https://openalex.org/W2964988320","https://openalex.org/W2979310060","https://openalex.org/W2979439447","https://openalex.org/W2996874060","https://openalex.org/W3016542674","https://openalex.org/W3016735325","https://openalex.org/W3016832937","https://openalex.org/W3094014938","https://openalex.org/W3103168911","https://openalex.org/W3104849992","https://openalex.org/W3128633047","https://openalex.org/W3133635270","https://openalex.org/W3160499679","https://openalex.org/W3167210698","https://openalex.org/W3176231905","https://openalex.org/W3185702163","https://openalex.org/W3187481008","https://openalex.org/W3190761184","https://openalex.org/W3205734594","https://openalex.org/W3213578211","https://openalex.org/W4240168186","https://openalex.org/W4244461127","https://openalex.org/W4251575795","https://openalex.org/W4360831992","https://openalex.org/W6637373629","https://openalex.org/W6638632666","https://openalex.org/W6684191040","https://openalex.org/W6726275242","https://openalex.org/W6790428460"],"related_works":["https://openalex.org/W2293118914","https://openalex.org/W2998381397","https://openalex.org/W4236419692","https://openalex.org/W2171015181","https://openalex.org/W3167919718","https://openalex.org/W4251718783","https://openalex.org/W4239447582","https://openalex.org/W1484403103","https://openalex.org/W2521947294","https://openalex.org/W2907307640"],"abstract_inverted_index":{"The":[0],"inherent":[1],"sparsity":[2,24],"present":[3],"in":[4,111,136,144],"convolutional":[5],"neural":[6],"networks":[7],"(CNNs)":[8],"offers":[9],"a":[10,66,104,108,132,141],"valuable":[11],"opportunity":[12],"to":[13,85,95,122,148],"significantly":[14,93],"decrease":[15],"the":[16,28,56,62,118,123,128],"computational":[17],"workload":[18],"during":[19],"inference.":[20],"Nevertheless,":[21],"leveraging":[22],"unstructured":[23],"typically":[25],"comes":[26],"with":[27],"trade-off":[29],"of":[30,61,74],"increased":[31],"complexity":[32],"or":[33],"substantial":[34],"hardware":[35,137],"overheads":[36],"for":[37],"accelerators.":[38],"To":[39],"address":[40],"these":[41],"challenges,":[42],"this":[43],"research":[44],"introduces":[45],"an":[46,90],"innovative":[47],"<italic":[48,70],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[49,71],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">inner":[50],"join</i>":[51],"aimed":[52],"at":[53],"effectively":[54],"reducing":[55],"size":[57],"and":[58,107,140],"power":[59,97],"consumption":[60],"sparsity-handling":[63],"circuit.":[64],"Additionally,":[65],"novel":[67],"dataflow":[68],"named":[69],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Channel":[72],"Stacking":[73],"Sparse":[75],"Tensors":[76],"(CSSpa)</i>":[77],"is":[78],"presented,":[79],"focusing":[80],"on":[81,117],"maximizing":[82],"data":[83],"reuse":[84],"minimize":[86],"memory":[87],"accesses":[88,113],"-":[89],"aspect":[91],"that":[92],"contributes":[94],"overall":[96],"consumption.":[98],"Through":[99],"comprehensive":[100],"simulations,":[101],"CSSpa":[102],"demonstrates":[103],"1.6\u00d7":[105],"speedup":[106],"5.6\u00d7":[109],"reduction":[110],"SRAM":[112],"when":[114],"executing":[115],"inference":[116],"ResNet50":[119],"model,":[120],"compared":[121,147],"existing":[124],"Sparten":[125],"architecture.":[126],"Furthermore,":[127],"implementation":[129],"results":[130],"reveal":[131],"notable":[133],"2.32\u00d7":[134],"enhancement":[135],"resource":[138],"efficiency":[139,146],"3.3\u00d7":[142],"improvement":[143],"energy":[145],"Sparten.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
