{"id":"https://openalex.org/W3120250747","doi":"https://doi.org/10.23919/date51398.2021.9474031","title":"Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks","display_name":"Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks","publication_year":2021,"publication_date":"2021-02-01","ids":{"openalex":"https://openalex.org/W3120250747","doi":"https://doi.org/10.23919/date51398.2021.9474031","mag":"3120250747"},"language":"en","primary_location":{"id":"doi:10.23919/date51398.2021.9474031","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date51398.2021.9474031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2101.04354","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083672437","display_name":"Karina Vasquez","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144718","display_name":"Universidad de Ingenier\u00eda y Tecnolog\u00eda","ror":"https://ror.org/040gykh71","country_code":"PE","type":"education","lineage":["https://openalex.org/I4210144718"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"Karina Vasquez","raw_affiliation_strings":["Department of Electrical Engineering, UTEC, Peru","UTEC,Department of Electrical Engineering,Peru"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, UTEC, Peru","institution_ids":["https://openalex.org/I4210144718"]},{"raw_affiliation_string":"UTEC,Department of Electrical Engineering,Peru","institution_ids":["https://openalex.org/I4210144718"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079036687","display_name":"Yeshwanth Venkatesha","orcid":null},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yeshwanth Venkatesha","raw_affiliation_strings":["Department of Electrical Engineering, Yale University, USA","Yale University Department of Electrical Engineering USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Yale University, USA","institution_ids":["https://openalex.org/I32971472"]},{"raw_affiliation_string":"Yale University Department of Electrical Engineering USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004629816","display_name":"Abhiroop Bhattacharjee","orcid":"https://orcid.org/0000-0002-7721-271X"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhiroop Bhattacharjee","raw_affiliation_strings":["Department of Electrical Engineering, Yale University, USA","Yale University Department of Electrical Engineering USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Yale University, USA","institution_ids":["https://openalex.org/I32971472"]},{"raw_affiliation_string":"Yale University Department of Electrical Engineering USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050796355","display_name":"Abhishek Moitra","orcid":"https://orcid.org/0000-0002-0534-5206"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhishek Moitra","raw_affiliation_strings":["Department of Electrical Engineering, Yale University, USA","Yale University Department of Electrical Engineering USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Yale University, USA","institution_ids":["https://openalex.org/I32971472"]},{"raw_affiliation_string":"Yale University Department of Electrical Engineering USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050310538","display_name":"Priyadarshini Panda","orcid":"https://orcid.org/0000-0002-4167-6782"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Priyadarshini Panda","raw_affiliation_strings":["Department of Electrical Engineering, Yale University, USA","Yale University Department of Electrical Engineering USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Yale University, USA","institution_ids":["https://openalex.org/I32971472"]},{"raw_affiliation_string":"Yale University Department of Electrical Engineering USA","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1941,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.45620232,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1360","last_page":"1365"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9958000183105469,"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/quantization","display_name":"Quantization (signal processing)","score":0.7761883735656738},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7455308437347412},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.61012864112854},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5890306234359741},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.5549411177635193},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5429385304450989},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.49139848351478577},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.43919339776039124},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4345180094242096},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42992573976516724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.309052437543869},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10849308967590332},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08059823513031006}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.7761883735656738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7455308437347412},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.61012864112854},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5890306234359741},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.5549411177635193},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5429385304450989},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.49139848351478577},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.43919339776039124},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4345180094242096},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42992573976516724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.309052437543869},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10849308967590332},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08059823513031006},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.23919/date51398.2021.9474031","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date51398.2021.9474031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2101.04354","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.04354","pdf_url":"https://arxiv.org/pdf/2101.04354","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3120250747","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2101.04354","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2101.04354","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2101.04354","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2101.04354","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.04354","pdf_url":"https://arxiv.org/pdf/2101.04354","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6499999761581421}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3120250747.pdf"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W2007329174","https://openalex.org/W2046542508","https://openalex.org/W2114766824","https://openalex.org/W2119144962","https://openalex.org/W2145085734","https://openalex.org/W2283463896","https://openalex.org/W2300242332","https://openalex.org/W2524428287","https://openalex.org/W2554302513","https://openalex.org/W2625457103","https://openalex.org/W2739601332","https://openalex.org/W2751477244","https://openalex.org/W2764043458","https://openalex.org/W2766839578","https://openalex.org/W2769644379","https://openalex.org/W2805003733","https://openalex.org/W2886014761","https://openalex.org/W2898755250","https://openalex.org/W2952344559","https://openalex.org/W2952682304","https://openalex.org/W2963114950","https://openalex.org/W2963674932","https://openalex.org/W2964299589","https://openalex.org/W2999241864","https://openalex.org/W3005165565","https://openalex.org/W3048300167","https://openalex.org/W3092032880","https://openalex.org/W6638632666","https://openalex.org/W6639703010","https://openalex.org/W6677103964","https://openalex.org/W6695838908","https://openalex.org/W6727208969","https://openalex.org/W6745499037","https://openalex.org/W6753645039"],"related_works":["https://openalex.org/W3185946996","https://openalex.org/W3123666279","https://openalex.org/W2962761403","https://openalex.org/W2964472257","https://openalex.org/W3176324119","https://openalex.org/W3175730059","https://openalex.org/W2795578121","https://openalex.org/W2946955515","https://openalex.org/W2890770683","https://openalex.org/W2612264667","https://openalex.org/W3135784973","https://openalex.org/W2971667683","https://openalex.org/W3129181244","https://openalex.org/W2892799969","https://openalex.org/W2610592929","https://openalex.org/W2994782216","https://openalex.org/W3089938037","https://openalex.org/W2963735024","https://openalex.org/W3181793056","https://openalex.org/W2963769126"],"abstract_inverted_index":{"As":[0],"neural":[1,211],"networks":[2],"gain":[3],"widespread":[4],"adoption":[5],"in":[6,22,68,78,162,176],"embedded":[7],"devices,":[8],"there":[9],"is":[10,26],"a":[11,40,79,82,191],"growing":[12],"need":[13,130],"for":[14,53,92,131,153,207,264],"model":[15,34,102,121],"compression":[16],"techniques":[17],"to":[18,48,64,159,233,257,274],"facilitate":[19],"seamless":[20],"deployment":[21],"resource-constrained":[23],"environments.":[24],"Quantization":[25],"one":[27],"of":[28,56,75,164,185],"the":[29,50,57,62,118,129,148,154,171,182,215,224],"go-to":[30],"methods":[31],"yielding":[32,97],"state-of-the-art":[33],"compression.":[35],"Most":[36],"quantization":[37,85,245],"approaches":[38],"take":[39],"fully":[41],"trained":[42],"model,":[43],"then":[44],"apply":[45],"different":[46,54],"heuristics":[47],"determine":[49],"optimal":[51,90],"bit-precision":[52],"layers":[55],"network,":[58],"and":[59,126,146,150,260,266],"finally":[60],"retrain":[61],"network":[63,212],"regain":[65],"any":[66],"drop":[67],"accuracy.":[69,105],"Based":[70],"on":[71,136,143,223,270],"Activation":[72],"Density-the":[73],"proportion":[74],"non-zero":[76],"activations":[77],"layer-we":[80],"propose":[81],"novel":[83],"in-training":[84],"method.":[86],"Our":[87],"method":[88,222],"calculates":[89],"bit-width/precision":[91],"each":[93],"layer":[94],"during":[95,113,253],"training":[96,124,172],"an":[98],"energy-efficient":[99],"mixed":[100],"precision":[101,110,210],"with":[103,219,246],"competitive":[104],"Since":[106],"we":[107,189,238],"train":[108],"lower":[109,123],"models":[111,217],"progressively":[112],"training,":[114],"our":[115,177,186,220],"approach":[116],"yields":[117,227,255],"final":[119],"quantized":[120,216],"at":[122],"complexity":[125,173],"also":[127],"eliminates":[128],"re-training.":[132],"We":[133,156],"run":[134],"experiments":[135],"benchmark":[137],"datasets":[138],"like":[139],"CIFAR-10,":[140],"CIFAR-100,":[141],"TinyImagenet":[142],"VGG19/ResNet18":[144],"architectures":[145,268],"report":[147],"accuracy":[149],"energy":[151,183,230,262],"estimates":[152],"same.":[155],"achieve":[157],"up":[158,256],"4.5\u00d7":[160],"benefit":[161],"terms":[163],"estimated":[165],"multiply-and-accumulate":[166],"(MAC)":[167],"reduction":[168,231],"while":[169],"reducing":[170],"by":[174],"50%":[175],"experiments.":[178],"To":[179],"further":[180],"evaluate":[181],"benefits":[184],"proposed":[187,221],"method,":[188],"develop":[190],"mixed-precision":[192],"scalable":[193],"Process":[194],"In":[195],"Memory":[196],"(PIM)":[197],"hardware":[198,202],"accelerator":[199],"platform.":[200],"The":[201],"platform":[203,226,272],"incorporates":[204],"shift-add":[205],"functionality":[206],"handling":[208],"multibit":[209],"models.":[213,236,279],"Evaluating":[214],"obtained":[218],"PIM":[225,271],"about":[228],"5\u00d7":[229],"compared":[232,273],"baseline":[234,275],"16-bit":[235,276],"Additionally,":[237],"find":[239],"that":[240],"integrating":[241],"activation":[242,247],"density":[243,248],"based":[244,249],"pruning":[250],"(both":[251],"conducted":[252],"training)":[254],"~":[258],"198\u00d7":[259],"~44\u00d7":[261],"reductions":[263],"VGG19":[265],"ResNet18":[267],"respectively":[269],"precision,":[277],"unpruned":[278]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2022-07-25T00:00:00"}