{"id":"https://openalex.org/W2997362251","doi":"https://doi.org/10.1109/iccad45719.2019.8942095","title":"A Uniform Modeling Methodology for Benchmarking DNN Accelerators","display_name":"A Uniform Modeling Methodology for Benchmarking DNN Accelerators","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W2997362251","doi":"https://doi.org/10.1109/iccad45719.2019.8942095","mag":"2997362251"},"language":"en","primary_location":{"id":"doi:10.1109/iccad45719.2019.8942095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad45719.2019.8942095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","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/A5021416915","display_name":"Indranil Palit","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101781","display_name":"Valeo Physical Therapy (United States)","ror":"https://ror.org/01bgvrv25","country_code":"US","type":"company","lineage":["https://openalex.org/I4210101781"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Indranil Palit","raw_affiliation_strings":["Valeo NA Inc., Troy, Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Valeo NA Inc., Troy, Michigan","institution_ids":["https://openalex.org/I4210101781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004724074","display_name":"Qiuwen Lou","orcid":"https://orcid.org/0000-0002-9266-8125"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiuwen Lou","raw_affiliation_strings":["University of Notre Dame"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067589457","display_name":"Robert Perricone","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert Perricone","raw_affiliation_strings":["University of Notre Dame"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003032564","display_name":"Michael Niemier","orcid":"https://orcid.org/0000-0001-7776-4306"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Niemier","raw_affiliation_strings":["University of Notre Dame"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100600905","display_name":"Xiaobo Sharon Hu","orcid":"https://orcid.org/0000-0002-6636-9738"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"X. Sharon Hu","raw_affiliation_strings":["University of Notre Dame"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7265,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.72997023,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2019","issue":null,"first_page":"1","last_page":"7"},"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":0.9995999932289124,"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":0.9987000226974487,"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/benchmarking","display_name":"Benchmarking","score":0.8625022172927856},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7748016119003296},{"id":"https://openalex.org/keywords/design-space-exploration","display_name":"Design space exploration","score":0.5728837847709656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5516484975814819},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5281474590301514},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.46810221672058105},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.43752917647361755},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43117856979370117},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.42956656217575073},{"id":"https://openalex.org/keywords/electronic-circuit","display_name":"Electronic circuit","score":0.42614316940307617},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.34689122438430786},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3435724973678589},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2863101065158844},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.12943428754806519},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.11546558141708374}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8625022172927856},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7748016119003296},{"id":"https://openalex.org/C2776221188","wikidata":"https://www.wikidata.org/wiki/Q21072556","display_name":"Design space exploration","level":2,"score":0.5728837847709656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5516484975814819},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5281474590301514},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.46810221672058105},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.43752917647361755},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43117856979370117},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.42956656217575073},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.42614316940307617},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.34689122438430786},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3435724973678589},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2863101065158844},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.12943428754806519},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.11546558141708374},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccad45719.2019.8942095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad45719.2019.8942095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","raw_type":"proceedings-article"},{"id":"mag:3163186498","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002287248235171","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1604973310","https://openalex.org/W1984541135","https://openalex.org/W2040475153","https://openalex.org/W2067523571","https://openalex.org/W2138913040","https://openalex.org/W2163605009","https://openalex.org/W2170382128","https://openalex.org/W2285660444","https://openalex.org/W2289252105","https://openalex.org/W2345813002","https://openalex.org/W2442974303","https://openalex.org/W2513554817","https://openalex.org/W2606722458","https://openalex.org/W2618530766","https://openalex.org/W2787453651","https://openalex.org/W2883928845","https://openalex.org/W2890947558","https://openalex.org/W2940862705","https://openalex.org/W2963029056","https://openalex.org/W6761458982"],"related_works":["https://openalex.org/W4282568311","https://openalex.org/W4313484792","https://openalex.org/W3013241373","https://openalex.org/W2951473296","https://openalex.org/W2883928845","https://openalex.org/W4288420200","https://openalex.org/W4285346947","https://openalex.org/W4365793791","https://openalex.org/W3145095675","https://openalex.org/W3134072570"],"abstract_inverted_index":{"Deep":[0],"Neural":[1],"Networks":[2],"(DNNs)":[3],"have":[4,18],"achieved":[5],"tremendous":[6],"success":[7],"in":[8,29],"many":[9],"application":[10],"domains.":[11],"Inspired":[12],"by":[13,98,142],"its":[14],"success,":[15],"specialized":[16],"accelerators":[17,38],"been":[19],"and":[20,53,109,118,145,182,198],"continue":[21],"to":[22,25,68,86,215],"be":[23,40],"developed":[24],"process":[26],"DNN":[27,37,63,100,228],"workloads":[28],"an":[30,76,157],"energy-efficient":[31],"manner.":[32],"The":[33],"design":[34,59],"space":[35,60],"for":[36,61,226],"can":[39,45,169,204],"extremely":[41],"large":[42],"since":[43],"they":[44],"employ":[46,163],"different":[47,114,210,227],"datapaths,":[48],"data":[49,143,179],"mapping":[50,180],"strategies,":[51],"circuits,":[52,177],"device":[54,175],"technologies.":[55],"To":[56,151],"explore":[57],"the":[58,71,88,105,128,136,153,193],"developing":[62],"accelerators,":[64],"it":[65],"is":[66],"important":[67],"quickly":[69],"estimate":[70,87,206],"energy":[72,90,111,154,172,207,220],"cost":[73,112,155],"associated":[74,110],"with":[75],"accelerator.":[77,101],"This":[78],"paper":[79],"introduces":[80],"a":[81,99,123,133,164],"uniform":[82,124],"modeling":[83],"framework,":[84],"Eva-DNN,":[85],"dynamic":[89],"(a":[91],"major":[92],"component":[93],"of":[94,107,116,130,135,138,148,156,217],"total":[95],"energy)":[96],"consumed":[97],"Specifically,":[102],"we":[103,162],"model":[104,152,171,187],"number":[106,129,137],"accesses":[108,131],"at":[113],"levels":[115],"memory":[117],"functional":[119,159],"units.":[120,150],"We":[121,184],"derive":[122],"expression":[125],"that":[126,202],"estimates":[127],"as":[132],"function":[134],"basic":[139],"operations":[140],"normalized":[141],"reuse":[144],"activity":[146],"factor":[147],"corresponding":[149],"individual":[158],"unit":[160],"operation,":[161],"device-level":[165],"benchmarking":[166],"approach.":[167],"Eva-DNN":[168,203],"accurately":[170,205],"contributions":[173,208],"from":[174,192,209,219,223],"technology,":[176],"architecture,":[178],"strategy,":[181],"network.":[183],"applied":[185],"our":[186],"on":[188],"three":[189],"accelerator":[190],"architectures":[191],"literature,":[194],"namely:":[195],"Eyeriss,":[196],"ShiDianNao,":[197],"TrueNorth.":[199],"Results":[200],"suggest":[201],"architectural":[211],"units,":[212],"achieving":[213],"4.5%":[214],"8.0%":[216],"deviation":[218],"costs":[221],"obtained":[222],"hardware":[224],"measurements":[225],"workloads.":[229]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}