{"id":"https://openalex.org/W4399486709","doi":"https://doi.org/10.1145/3649476.3658736","title":"NeuroBlend: Towards Low-Power yet Accurate Neural Network-Based Inference Engine Blending Binary and Fixed-Point Convolutions","display_name":"NeuroBlend: Towards Low-Power yet Accurate Neural Network-Based Inference Engine Blending Binary and Fixed-Point Convolutions","publication_year":2024,"publication_date":"2024-06-10","ids":{"openalex":"https://openalex.org/W4399486709","doi":"https://doi.org/10.1145/3649476.3658736"},"language":"en","primary_location":{"id":"doi:10.1145/3649476.3658736","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3649476.3658736","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2024","raw_type":"proceedings-article"},"type":"conference-paper","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/A5018508596","display_name":"Arash Fayyazi","orcid":"https://orcid.org/0000-0002-8088-5800"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arash Fayyazi","raw_affiliation_strings":["Electrical and Computer Engineering, University of Southern California, USA","University of Southern California, USA"],"raw_orcid":"https://orcid.org/0000-0002-8088-5800","affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065028689","display_name":"Mahdi Nazemi","orcid":"https://orcid.org/0000-0003-4731-3568"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahdi Nazemi","raw_affiliation_strings":["University of Southern California, USA"],"raw_orcid":"https://orcid.org/0000-0003-4731-3568","affiliations":[{"raw_affiliation_string":"University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099073584","display_name":"Arya Fayyazi","orcid":"https://orcid.org/0009-0001-9656-2627"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arya Fayyazi","raw_affiliation_strings":["Electrical and Computer Engineering, University of Southern California, USA","University of Southern California, USA"],"raw_orcid":"https://orcid.org/0009-0001-9656-2627","affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044650311","display_name":"Massoud Pedram","orcid":"https://orcid.org/0000-0002-2677-7307"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Massoud Pedram","raw_affiliation_strings":["University of Southern California, USA"],"raw_orcid":"https://orcid.org/0000-0002-2677-7307","affiliations":[{"raw_affiliation_string":"University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":0.2629,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49143867,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"730","last_page":"735"},"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":0.9973999857902527,"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/T10320","display_name":"Neural Networks and Applications","score":0.9922000169754028,"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/inference","display_name":"Inference","score":0.7116824388504028},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.6954441070556641},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6025906205177307},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.5571922063827515},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.538239061832428},{"id":"https://openalex.org/keywords/fixed-point","display_name":"Fixed point","score":0.5308144092559814},{"id":"https://openalex.org/keywords/inference-engine","display_name":"Inference engine","score":0.49274328351020813},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4755273163318634},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3209909200668335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2745790481567383},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22050601243972778},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14628928899765015},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.12642157077789307},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.07608658075332642},{"id":"https://openalex.org/keywords/thermodynamics","display_name":"Thermodynamics","score":0.07539379596710205}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7116824388504028},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.6954441070556641},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6025906205177307},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.5571922063827515},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.538239061832428},{"id":"https://openalex.org/C61445026","wikidata":"https://www.wikidata.org/wiki/Q217608","display_name":"Fixed point","level":2,"score":0.5308144092559814},{"id":"https://openalex.org/C46743427","wikidata":"https://www.wikidata.org/wiki/Q1341685","display_name":"Inference engine","level":3,"score":0.49274328351020813},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4755273163318634},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3209909200668335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2745790481567383},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22050601243972778},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14628928899765015},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.12642157077789307},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.07608658075332642},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.07539379596710205},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3649476.3658736","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3649476.3658736","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2024","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2300242332","https://openalex.org/W2565125333","https://openalex.org/W2747329762","https://openalex.org/W2887447938","https://openalex.org/W2963163009","https://openalex.org/W3130641740","https://openalex.org/W3138516171","https://openalex.org/W3150757912","https://openalex.org/W3157506437","https://openalex.org/W3202230044","https://openalex.org/W4205554189"],"related_works":["https://openalex.org/W2057057690","https://openalex.org/W2368184788","https://openalex.org/W2358964818","https://openalex.org/W2359535128","https://openalex.org/W2381332051","https://openalex.org/W2321443665","https://openalex.org/W2375699995","https://openalex.org/W2043719711","https://openalex.org/W2140069467","https://openalex.org/W2364072231"],"abstract_inverted_index":{"This":[0,19],"paper":[1],"introduces":[2],"NeuroBlend,":[3],"a":[4,10,35,60,138,163],"novel":[5],"neural":[6,102],"network":[7],"architecture":[8,64],"featuring":[9],"unique":[11],"building":[12],"block":[13],"known":[14],"as":[15],"the":[16,48],"Blend":[17,49,55],"module.":[18],"module":[20,50],"incorporates":[21],"binary":[22,101],"and":[23,29,44,51,62],"fixed-point":[24],"convolutions":[25],"in":[26,52,141,166],"its":[27],"main":[28,43],"skip":[30,45],"paths,":[31],"respectively.":[32],"There":[33],"is":[34],"judicious":[36],"deployment":[37],"of":[38,111],"batch":[39],"normalizations":[40],"on":[41,91],"both":[42],"paths":[46],"inside":[47],"between":[53],"consecutive":[54],"modules.":[56],"Additionally,":[57],"we":[58],"present":[59],"compiler":[61],"hardware":[63],"designed":[65],"to":[66,74,145],"map":[67],"NeuroBlend":[68],"models":[69],"onto":[70],"FPGA":[71,119,160],"devices,":[72],"aiming":[73],"minimize":[75],"inference":[76,109],"latency":[77],"while":[78],"maintaining":[79],"high":[80],"accuracy.":[81],"Our":[82],"NeuroBlend-20":[83],"(NeuroBlend-18)":[84],"model,":[85],"derived":[86],"from":[87],"ResNet-20":[88],"(ResNet-18)":[89],"trained":[90],"CIFAR-10":[92,128],"(CIFAR-100),":[93],"achieves":[94],"88.0%":[95],"(73.73%)":[96],"classification":[97],"accuracy,":[98],"outperforming":[99],"state-of-the-art":[100],"networks":[103],"by":[104],"0.8%":[105],"(1.33%),":[106],"with":[107,137],"an":[108],"time":[110],"0.38ms":[112],"per":[113],"image,":[114],"1.4x":[115],"faster":[116],"than":[117,133],"previous":[118],"implementation":[120],"for":[121,127,153],"BNNs.":[122],"Similarly,":[123],"our":[124],"BlendMixer":[125],"model":[126,142],"attains":[129],"90.6%":[130],"accuracy(1.59%":[131],"less":[132],"full":[134,146],"precision":[135,147],"MLPMixer),":[136],"3.5x":[139],"reduction":[140,165],"size":[143],"compared":[144],"MLPMixer.":[148],"Furthermore,":[149],"leveraging":[150],"DSP":[151],"blocks":[152],"48-bit":[154],"bitwise":[155],"logic":[156],"operations":[157],"enables":[158],"low-power":[159],"implementation,":[161],"yielding":[162],"2.5x":[164],"power":[167],"consumption.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}