{"id":"https://openalex.org/W4292263344","doi":"https://doi.org/10.1109/access.2022.3197206","title":"Energy-Efficient Dataflow Scheduling of CNN Applications for Vector-SIMD DSP","display_name":"Energy-Efficient Dataflow Scheduling of CNN Applications for Vector-SIMD DSP","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4292263344","doi":"https://doi.org/10.1109/access.2022.3197206"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3197206","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3197206","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09858336.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/ielx7/6287639/6514899/09858336.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101577510","display_name":"Wontae Kim","orcid":"https://orcid.org/0000-0001-5118-0839"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Wontae Kim","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100611399","display_name":"Sangheon Lee","orcid":"https://orcid.org/0000-0001-8620-8213"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sangheon Lee","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069169167","display_name":"Ilwi Yun","orcid":"https://orcid.org/0000-0003-0415-7091"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ilwi Yun","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100719566","display_name":"Chulhee Lee","orcid":"https://orcid.org/0000-0002-2509-167X"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chulhee Lee","raw_affiliation_strings":["System LSI Division, Samsung Electronics Corporation, Hwaseong, South Korea"],"affiliations":[{"raw_affiliation_string":"System LSI Division, Samsung Electronics Corporation, Hwaseong, South Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039863333","display_name":"Kyujoong Lee","orcid":"https://orcid.org/0000-0002-3080-3010"},"institutions":[{"id":"https://openalex.org/I165677929","display_name":"Sungshin Women's University","ror":"https://ror.org/0500xzf72","country_code":"KR","type":"education","lineage":["https://openalex.org/I165677929"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyujoong Lee","raw_affiliation_strings":["School of AI Convergence, Sungshin Women’s University, Seoul, South Korea","s University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"School of AI Convergence, Sungshin Women’s University, Seoul, South Korea","institution_ids":["https://openalex.org/I165677929"]},{"raw_affiliation_string":"s University, Seoul, Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102861073","display_name":"Hyuk-Jae Lee","orcid":"https://orcid.org/0000-0001-8895-9117"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyuk-Jae Lee","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101577510"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2013,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.4695764,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"10","issue":null,"first_page":"86234","last_page":"86247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9944999814033508,"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"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9922000169754028,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8475885391235352},{"id":"https://openalex.org/keywords/dataflow","display_name":"Dataflow","score":0.7289840579032898},{"id":"https://openalex.org/keywords/simd","display_name":"SIMD","score":0.7285436987876892},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.7284484505653381},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5339267253875732},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.518467366695404},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.4614732265472412},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.40190809965133667},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3629189133644104}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8475885391235352},{"id":"https://openalex.org/C96324660","wikidata":"https://www.wikidata.org/wiki/Q205446","display_name":"Dataflow","level":2,"score":0.7289840579032898},{"id":"https://openalex.org/C150552126","wikidata":"https://www.wikidata.org/wiki/Q339387","display_name":"SIMD","level":2,"score":0.7285436987876892},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.7284484505653381},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5339267253875732},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.518467366695404},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.4614732265472412},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.40190809965133667},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3629189133644104},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3197206","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3197206","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09858336.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6463e8b619c144e59367b2ebbcbaf2c8","is_oa":true,"landing_page_url":"https://doaj.org/article/6463e8b619c144e59367b2ebbcbaf2c8","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 10, Pp 86234-86247 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3197206","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3197206","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09858336.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"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/W4292263344.pdf","grobid_xml":"https://content.openalex.org/works/W4292263344.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2088079057","https://openalex.org/W2094756095","https://openalex.org/W2096645269","https://openalex.org/W2102605133","https://openalex.org/W2110158442","https://openalex.org/W2117696986","https://openalex.org/W2162639668","https://openalex.org/W2194775991","https://openalex.org/W2242218935","https://openalex.org/W2570343428","https://openalex.org/W2620620689","https://openalex.org/W2798317693","https://openalex.org/W2909683753","https://openalex.org/W2914286461","https://openalex.org/W2963542991","https://openalex.org/W2963881378","https://openalex.org/W2980200167","https://openalex.org/W3004171485","https://openalex.org/W4212788319","https://openalex.org/W4240168186","https://openalex.org/W4247470470","https://openalex.org/W4249932213","https://openalex.org/W4288601955","https://openalex.org/W4297775537","https://openalex.org/W4302296459","https://openalex.org/W6629368666","https://openalex.org/W6637151318","https://openalex.org/W6637373629","https://openalex.org/W6682126434","https://openalex.org/W6684191040","https://openalex.org/W6737664043","https://openalex.org/W6751349269","https://openalex.org/W6757914146","https://openalex.org/W6758143911","https://openalex.org/W6765023724"],"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/W2150836909"],"abstract_inverted_index":{"Dataflow-scheduling":[0],"techniques":[1,23],"for":[2,48,56,151,157,258],"convolutional":[3],"neural":[4],"networks":[5],"(CNNs)":[6],"are":[7,24,83],"extensively":[8],"studied":[9],"to":[10,51,66,112,171,212],"minimize":[11,52,142],"the":[12,17,20,31,53,57,62,76,78,88,93,96,100,105,113,116,124,129,134,138,148,153,163,166,173,176,183,186,190,197,201,214,218,223,240,246,250],"off-chip":[13,58,89,120,130,202,219,231],"memory":[14,59,90,121,220],"access.":[15,60],"However,":[16,132],"efficiencies":[18],"of":[19,104,115,119,128,175,185,217,256],"previously":[21],"proposed":[22,63,125,247],"limited":[25],"because":[26],"their":[27],"optimizations":[28],"only":[29],"consider":[30],"general":[32],"hardware":[33],"such":[34,261],"as":[35,68,72,262],"FPGA":[36],"and":[37,95,229,243],"GPU.":[38],"To":[39,141],"overcome":[40],"this":[41,43,143,145],"limitation,":[42],"paper":[44,146],"proposes":[45],"dataflow":[46],"scheduling":[47,244],"vector-SIMD":[49,227],"DSP":[50,228],"energy":[54,117,126,198,215,251],"consumption":[55,118,199,216,252],"First,":[61],"technique":[64,248],"attempts":[65],"group":[67],"many":[69],"given":[70],"layers":[71,82,98,107,135,158],"possible.":[73],"For":[74,204],"grouping":[75,133],"layers,":[77],"tiles":[79],"in":[80,85,99,137,152,179,189],"different":[81],"executed":[84],"sequence":[86],"without":[87],"access":[91],"except":[92],"first":[94],"last":[97],"group.":[101],"The":[102,233],"length":[103],"grouped":[106,154],"is":[108,168,193,210],"determined":[109],"with":[110,239],"regard":[111],"minimization":[114],"by":[122,200,221,253],"estimating":[123],"model":[127],"memory.":[131,203,232],"results":[136,235],"additional":[139],"computation.":[140],"overhead,":[144],"solves":[147],"optimization":[149],"problem":[150],"layers.":[155],"Second,":[156],"that":[159,237],"cannot":[160],"be":[161],"grouped,":[162],"tiling":[164,242],"along":[165],"W-axis":[167],"not":[169],"considered,":[170],"maximize":[172],"size":[174],"overlapped":[177,187],"data":[178,188,224],"consecutive":[180],"tiles.":[181],"Consequently,":[182],"reuse":[184],"on-chip":[191],"buffer":[192],"maximized,":[194],"thereby":[195],"reducing":[196],"evaluation,":[205],"a":[206,226],"cycle-accurate":[207],"simulation":[208],"environment":[209],"established":[211],"measure":[213],"tracing":[222],"between":[225],"an":[230,254],"experimental":[234],"show":[236],"compared":[238],"baseline":[241],"techniques,":[245],"reduces":[249],"average":[255],"51%":[257],"CNN":[259],"applications":[260],"Tiny":[263],"YOLOv2,":[264],"MobileNetv1,":[265],"VDSR.":[266]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}