{"id":"https://openalex.org/W4406894608","doi":"https://doi.org/10.1109/a-sscc60305.2024.10849097","title":"An 8.1-to-353 TOPS/W Energy-Aware Deep-Learning Accelerator Supporting Dynamic Neural Networks","display_name":"An 8.1-to-353 TOPS/W Energy-Aware Deep-Learning Accelerator Supporting Dynamic Neural Networks","publication_year":2024,"publication_date":"2024-11-18","ids":{"openalex":"https://openalex.org/W4406894608","doi":"https://doi.org/10.1109/a-sscc60305.2024.10849097"},"language":"en","primary_location":{"id":"doi:10.1109/a-sscc60305.2024.10849097","is_oa":false,"landing_page_url":"https://doi.org/10.1109/a-sscc60305.2024.10849097","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Asian Solid-State Circuits Conference (A-SSCC)","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/A5027269111","display_name":"Tingyang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ting-Yang Chen","raw_affiliation_strings":["National Taiwan University,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University,Taipei,Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060377604","display_name":"Yi-Lin Lo","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yi-Lin Lo","raw_affiliation_strings":["National Taiwan University,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University,Taipei,Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032532506","display_name":"Tun-Yu Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tun-Yu Chang","raw_affiliation_strings":["National Taiwan University,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University,Taipei,Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101750729","display_name":"Chia\u2010Hsiang Yang","orcid":"https://orcid.org/0000-0003-1163-321X"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chia-Hsiang Yang","raw_affiliation_strings":["National Taiwan University,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University,Taipei,Taiwan","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22719999,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.7967000007629395,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.7967000007629395,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.7034000158309937,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10320","display_name":"Neural Networks and Applications","score":0.6391000151634216,"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/tops","display_name":"TOPS","score":0.7556829452514648},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.645104169845581},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5788718461990356},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5482485890388489},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4473164677619934},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40141990780830383},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15673017501831055},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12776023149490356},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.09532690048217773}],"concepts":[{"id":"https://openalex.org/C2777675136","wikidata":"https://www.wikidata.org/wiki/Q835642","display_name":"TOPS","level":3,"score":0.7556829452514648},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.645104169845581},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5788718461990356},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5482485890388489},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4473164677619934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40141990780830383},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15673017501831055},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12776023149490356},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.09532690048217773},{"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/C154815118","wikidata":"https://www.wikidata.org/wiki/Q453762","display_name":"Spinning","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/a-sscc60305.2024.10849097","is_oa":false,"landing_page_url":"https://doi.org/10.1109/a-sscc60305.2024.10849097","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Asian Solid-State Circuits Conference (A-SSCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8500000238418579,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322410","display_name":"MediaTek","ror":"https://ror.org/05g9jck81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W3086377361"],"abstract_inverted_index":{"The":[0],"demand":[1],"for":[2,26],"edge":[3],"Al":[4],"is":[5,54,63,75],"rapidly":[6],"increasing":[7],"in":[8],"various":[9],"applications,":[10],"including":[11],"image":[12,16],"classification,":[13],"object":[14],"detection,":[15],"segmentation,":[17],"and":[18,43,58],"key-point":[19],"detection.":[20],"Conventionally,":[21],"deep-learning":[22],"accelerators":[23],"are":[24,49],"designed":[25],"a":[27,32,59,70],"fixed":[28],"operating":[29,41,73],"scenario,":[30],"targeting":[31],"high":[33],"accuracy":[34,61],"with":[35],"affordable":[36],"energy":[37],"consumption.":[38],"However,":[39],"the":[40,55],"scenarios":[42,74],"performance":[44],"requirements":[45],"may":[46],"vary.":[47],"There":[48],"cases":[50],"where":[51],"low-energy":[52],"operation":[53],"first":[56],"priority":[57],"slight":[60],"loss":[62],"tolerated.":[64],"Therefore,":[65],"an":[66],"energy-aware":[67],"solution":[68],"supporting":[69],"variety":[71],"of":[72],"required.":[76]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}