{"id":"https://openalex.org/W4388902227","doi":"https://doi.org/10.1109/vlsi-soc57769.2023.10321889","title":"ADaMaT: Towards an Adaptive Dataflow for Maximising Throughput in Neural Network Inference","display_name":"ADaMaT: Towards an Adaptive Dataflow for Maximising Throughput in Neural Network Inference","publication_year":2023,"publication_date":"2023-10-16","ids":{"openalex":"https://openalex.org/W4388902227","doi":"https://doi.org/10.1109/vlsi-soc57769.2023.10321889"},"language":"en","primary_location":{"id":"doi:10.1109/vlsi-soc57769.2023.10321889","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/vlsi-soc57769.2023.10321889","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IFIP/IEEE 31st International Conference on Very Large Scale Integration (VLSI-SoC)","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/A5086454875","display_name":"Imlijungla Longchar","orcid":null},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Imlijungla Longchar","raw_affiliation_strings":["IIT Guwahati,Department of Computer Science and Engineering,Guwahati,India","Department of Computer Science and Engineering, IIT Guwahati, Guwahati, India"],"affiliations":[{"raw_affiliation_string":"IIT Guwahati,Department of Computer Science and Engineering,Guwahati,India","institution_ids":["https://openalex.org/I1317621060"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, IIT Guwahati, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070605948","display_name":"Hemangee K. Kapoor","orcid":"https://orcid.org/0000-0002-9376-7686"},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hemangee K. Kapoor","raw_affiliation_strings":["IIT Guwahati,Department of Computer Science and Engineering,Guwahati,India","Department of Computer Science and Engineering, IIT Guwahati, Guwahati, India"],"affiliations":[{"raw_affiliation_string":"IIT Guwahati,Department of Computer Science and Engineering,Guwahati,India","institution_ids":["https://openalex.org/I1317621060"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, IIT Guwahati, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5086454875"],"corresponding_institution_ids":["https://openalex.org/I1317621060"],"apc_list":null,"apc_paid":null,"fwci":0.131,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46470044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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":0.9965000152587891,"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/dataflow","display_name":"Dataflow","score":0.989871621131897},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8491798639297485},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.7689664363861084},{"id":"https://openalex.org/keywords/dataflow-architecture","display_name":"Dataflow architecture","score":0.7050610780715942},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6661040782928467},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5858080387115479},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5280478596687317},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.5150951743125916},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4780326783657074},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4613296091556549},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4349002242088318},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3382376432418823},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.33778077363967896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25742459297180176},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10374867916107178}],"concepts":[{"id":"https://openalex.org/C96324660","wikidata":"https://www.wikidata.org/wiki/Q205446","display_name":"Dataflow","level":2,"score":0.989871621131897},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8491798639297485},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.7689664363861084},{"id":"https://openalex.org/C176727019","wikidata":"https://www.wikidata.org/wiki/Q1172415","display_name":"Dataflow architecture","level":3,"score":0.7050610780715942},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6661040782928467},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5858080387115479},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5280478596687317},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.5150951743125916},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4780326783657074},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4613296091556549},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4349002242088318},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3382376432418823},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.33778077363967896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25742459297180176},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10374867916107178},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vlsi-soc57769.2023.10321889","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/vlsi-soc57769.2023.10321889","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IFIP/IEEE 31st International Conference on Very Large Scale Integration (VLSI-SoC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2048266589","https://openalex.org/W2285660444","https://openalex.org/W2289252105","https://openalex.org/W2626712922","https://openalex.org/W2750173518","https://openalex.org/W2979644612","https://openalex.org/W2980104813","https://openalex.org/W2980200167","https://openalex.org/W3114479342","https://openalex.org/W3118608800","https://openalex.org/W4236868170","https://openalex.org/W4244024631","https://openalex.org/W4280557024","https://openalex.org/W4288083528","https://openalex.org/W4308659641","https://openalex.org/W6637373629","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2564598376","https://openalex.org/W1484403103","https://openalex.org/W2584408851","https://openalex.org/W2115158825","https://openalex.org/W2101960124","https://openalex.org/W4377693460","https://openalex.org/W2783505431","https://openalex.org/W2521947294","https://openalex.org/W4236419692","https://openalex.org/W2807127337"],"abstract_inverted_index":{"With":[0],"the":[1,17,44,55,70,96,102,106,109,119,125,129,142,151,156,159,172,177],"development":[2],"of":[3,20,46,98,101,105,113,158,162],"research":[4],"in":[5,27,50,69,81,95,108,133],"hardware":[6,21,36,47,71],"for":[7,38,90,121,124],"Convolutional":[8],"Neural":[9],"Network(CNNs)":[10],"Algorithms,":[11],"it":[12],"becomes":[13],"crucial":[14],"to":[15,42,65,127,150,170],"examine":[16],"different":[18,103,186],"aspects":[19],"design.":[22],"CNNs":[23],"are":[24],"mainly":[25],"used":[26],"computer":[28],"vision":[29],"applications,":[30],"and":[31,73,175,189],"translating":[32],"these":[33],"algorithms":[34],"into":[35],"calls":[37],"adopting":[39,86],"appropriate":[40],"dataflow":[41,89,123,143],"improve":[43,128,176],"utilisation":[45,132,174],"resources":[48,99],"resulting":[49],"higher":[51],"throughput.":[52,178],"In":[53],"particular,":[54],"inference":[56],"task":[57],"at":[58,144],"each":[59],"neuron":[60,76],"position":[61],"can":[62,78,93],"be":[63,79],"assigned":[64],"a":[66,87,137,163,182],"compute":[67],"unit":[68],"accelerator,":[72],"several":[74],"such":[75],"positions":[77],"completed":[80],"parallel.":[82],"We":[83,135,179],"observe":[84],"that":[85],"static":[88,187],"an":[91],"architecture":[92],"result":[94],"under-utilisation":[97],"because":[100],"dimensions":[104,157],"data":[107],"network.":[110],"The":[111,166],"motivation":[112],"this":[114],"paper":[115],"is":[116],"built":[117],"upon":[118],"need":[120],"adaptive":[122,167],"design":[126],"multiply-and-accumulate":[130],"(MAC)":[131],"CNNs.":[134],"propose":[136],"method,":[138],"ADaMaT,":[139],"which":[140],"adapts":[141],"runtime":[145],"by":[146],"appropriately":[147],"assigning":[148],"tasks":[149],"MAC":[152,173],"units":[153],"depending":[154],"on":[155],"layers":[160],"instead":[161],"pre-determined":[164],"assignment.":[165],"assignment":[168],"tries":[169],"maximise":[171],"have":[180],"performed":[181],"comparative":[183],"analysis":[184],"among":[185],"dataflows":[188],"our":[190],"proposed":[191],"ADaMaT":[192],"dataflow.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}
