{"id":"https://openalex.org/W4200410165","doi":"https://doi.org/10.1109/iccd53106.2021.00014","title":"Special Session: When Dataflows Converge: Reconfigurable and Approximate Computing for Emerging Neural Networks","display_name":"Special Session: When Dataflows Converge: Reconfigurable and Approximate Computing for Emerging Neural Networks","publication_year":2021,"publication_date":"2021-10-01","ids":{"openalex":"https://openalex.org/W4200410165","doi":"https://doi.org/10.1109/iccd53106.2021.00014"},"language":"en","primary_location":{"id":"doi:10.1109/iccd53106.2021.00014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccd53106.2021.00014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 39th International Conference on Computer Design (ICCD)","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/A5037740394","display_name":"Di Wu","orcid":"https://orcid.org/0000-0001-9775-8026"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Di Wu","raw_affiliation_strings":["University of Wisconsin-Madison,Department of Electrical and Computer Engineering,Madison,Wisconsin,USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison,Department of Electrical and Computer Engineering,Madison,Wisconsin,USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034301665","display_name":"Joshua San Miguel","orcid":"https://orcid.org/0000-0002-6886-7183"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joshua San Miguel","raw_affiliation_strings":["University of Wisconsin-Madison,Department of Electrical and Computer Engineering,Madison,Wisconsin,USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison,Department of Electrical and Computer Engineering,Madison,Wisconsin,USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5037740394"],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":null,"apc_paid":null,"fwci":0.9211,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.74234774,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"9","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9983000159263611,"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":0.781338095664978},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.6982231140136719},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6370248198509216},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5830206871032715},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5449714064598083},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.42991477251052856},{"id":"https://openalex.org/keywords/stack","display_name":"Stack (abstract data type)","score":0.41509032249450684},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.41414502263069153},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4115408658981323},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.40678489208221436},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3647778034210205},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.35021281242370605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24961945414543152}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.781338095664978},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.6982231140136719},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6370248198509216},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5830206871032715},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5449714064598083},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.42991477251052856},{"id":"https://openalex.org/C9395851","wikidata":"https://www.wikidata.org/wiki/Q177929","display_name":"Stack (abstract data type)","level":2,"score":0.41509032249450684},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.41414502263069153},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4115408658981323},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.40678489208221436},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3647778034210205},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.35021281242370605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24961945414543152},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccd53106.2021.00014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccd53106.2021.00014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 39th International Conference on Computer Design (ICCD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1665214252","https://openalex.org/W2163605009","https://openalex.org/W2570467259","https://openalex.org/W2606722458","https://openalex.org/W2613817144","https://openalex.org/W2908842219","https://openalex.org/W2911491685","https://openalex.org/W2971601850","https://openalex.org/W3126552944","https://openalex.org/W3128386784","https://openalex.org/W3189138869","https://openalex.org/W6637242042","https://openalex.org/W6684191040","https://openalex.org/W6731608545"],"related_works":["https://openalex.org/W2380576232","https://openalex.org/W2937054111","https://openalex.org/W2066223521","https://openalex.org/W373327546","https://openalex.org/W2321534397","https://openalex.org/W2058958858","https://openalex.org/W1835805572","https://openalex.org/W2148243540","https://openalex.org/W3042419602","https://openalex.org/W2966649771"],"abstract_inverted_index":{"Deep":[0],"Neural":[1],"Networks":[2],"(DNNs)":[3],"have":[4],"gained":[5],"significant":[6],"attention":[7],"in":[8,54],"both":[9,81],"academia":[10],"and":[11,83],"industry":[12],"due":[13],"to":[14,41,79],"the":[15,38,43,100],"superior":[16],"application-level":[17],"accuracy.":[18],"As":[19],"DNNs":[20,48],"rely":[21],"on":[22],"compute-":[23],"or":[24],"memory-intensive":[25],"general":[26],"matrix":[27],"multiply":[28],"(GEMM)":[29],"operations,":[30,59],"approximate":[31],"computing":[32,39],"has":[33],"been":[34],"widely":[35],"explored":[36],"across":[37],"stack":[40],"mitigate":[42],"hardware":[44,64,101],"overheads.":[45],"However,":[46],"better-performing":[47],"are":[49],"emerging":[50,104],"with":[51,88],"growing":[52],"complexity":[53],"their":[55],"use":[56],"of":[57,96,103],"nonlinear":[58,84],"which":[60],"incurs":[61],"even":[62],"more":[63],"cost.":[65],"In":[66],"this":[67,71],"work,":[68],"we":[69],"address":[70],"challenge":[72],"by":[73],"proposing":[74],"a":[75],"reconfigurable":[76],"systolic":[77],"array":[78],"execute":[80],"GEMM":[82],"operations":[85],"via":[86],"approximation":[87],"distinguished":[89],"dataflows.":[90],"Experiments":[91],"demonstrate":[92],"that":[93],"such":[94],"converging":[95],"dataflows":[97],"significantly":[98],"saves":[99],"cost":[102],"DNN":[105],"inference.":[106]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
