{"id":"https://openalex.org/W3202755419","doi":"https://doi.org/10.1145/3479876.3481591","title":"NEWROMAP","display_name":"NEWROMAP","publication_year":2021,"publication_date":"2021-10-05","ids":{"openalex":"https://openalex.org/W3202755419","doi":"https://doi.org/10.1145/3479876.3481591","mag":"3202755419"},"language":"en","primary_location":{"id":"doi:10.1145/3479876.3481591","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3479876.3481591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th IEEE/ACM International Symposium on Networks-on-Chip","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/A5043596492","display_name":"Jan Moritz Joseph","orcid":"https://orcid.org/0000-0001-8669-1225"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jan Moritz Joseph","raw_affiliation_strings":["RWTH Aachen University, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011744270","display_name":"Murat Sezgin Baloglu","orcid":null},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Murat Sezgin Baloglu","raw_affiliation_strings":["RWTH Aachen University, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108053345","display_name":"Yue Pan","orcid":"https://orcid.org/0000-0003-4572-8882"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Pan","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023470562","display_name":"Rainer Leupers","orcid":"https://orcid.org/0000-0002-6735-3033"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Rainer Leupers","raw_affiliation_strings":["RWTH Aachen University, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031777933","display_name":"Lennart Bamberg","orcid":"https://orcid.org/0000-0003-4673-8310"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lennart Bamberg","raw_affiliation_strings":["GrAI Matter Labs, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GrAI Matter Labs, The Netherlands","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"15","last_page":"20"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9979000091552734,"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":0.8409467339515686},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6379586458206177},{"id":"https://openalex.org/keywords/multi-core-processor","display_name":"Multi-core processor","score":0.5518362522125244},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5474458932876587},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.53514564037323},{"id":"https://openalex.org/keywords/memory-bandwidth","display_name":"Memory bandwidth","score":0.4872340261936188},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4397548735141754},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.4314485192298889},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4151831865310669},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3937692642211914},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3670739531517029},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24871128797531128},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2243439257144928}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8409467339515686},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6379586458206177},{"id":"https://openalex.org/C78766204","wikidata":"https://www.wikidata.org/wiki/Q555032","display_name":"Multi-core processor","level":2,"score":0.5518362522125244},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5474458932876587},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.53514564037323},{"id":"https://openalex.org/C188045654","wikidata":"https://www.wikidata.org/wiki/Q17148339","display_name":"Memory bandwidth","level":2,"score":0.4872340261936188},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4397548735141754},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.4314485192298889},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4151831865310669},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3937692642211914},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3670739531517029},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24871128797531128},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2243439257144928},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3479876.3481591","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3479876.3481591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th IEEE/ACM International Symposium on Networks-on-Chip","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1604973310","https://openalex.org/W2146981302","https://openalex.org/W2161380643","https://openalex.org/W2442974303","https://openalex.org/W2534302924","https://openalex.org/W2964299589","https://openalex.org/W2976973312","https://openalex.org/W2985813553","https://openalex.org/W3018923871","https://openalex.org/W3035770626","https://openalex.org/W3201876660","https://openalex.org/W4244024631","https://openalex.org/W6601968593","https://openalex.org/W7007706698"],"related_works":["https://openalex.org/W2986579802","https://openalex.org/W3108691306","https://openalex.org/W4389237622","https://openalex.org/W2166309310","https://openalex.org/W4385753159","https://openalex.org/W4200152843","https://openalex.org/W4387251107","https://openalex.org/W4214914769","https://openalex.org/W2031026393","https://openalex.org/W2063611263"],"abstract_inverted_index":{"Conventional":[0],"AI":[1],"accelerators":[2,12],"are":[3],"limited":[4],"by":[5,17,71],"von-Neumann":[6],"bottlenecks":[7],"for":[8,57,89],"edge":[9],"workloads.":[10],"Domain-specific":[11],"(often":[13],"neuromorphic)":[14],"solve":[15],"this":[16],"applying":[18],"near/in-memory":[19],"computing,":[20],"NoC-interconnected":[21],"massive-multicore":[22],"setups,":[23],"and":[24,47,91,115],"data-flow":[25],"computation.":[26],"This":[27],"requires":[28],"an":[29,36],"effective":[30],"mapping":[31,54,105,135],"of":[32,38,69,85],"neural":[33,61],"networks":[34,62],"(i.e,":[35],"assignment":[37],"network":[39],"layers":[40,73],"to":[41,43,74,87,102,128],"cores)":[42],"balance":[44],"resources/memory,":[45],"computation,":[46],"NoC":[48,82,113],"traffic.":[49],"Here,":[50],"we":[51],"introduce":[52],"a":[53,80,107],"called":[55],"Snake":[56,104],"the":[58,66,112],"predominant":[59],"convolutional":[60],"(CNNs).":[63],"It":[64],"utilizes":[65],"feed-forward":[67],"nature":[68],"CNNs":[70],"folding":[72],"spatially":[75],"adjacent":[76],"cores.":[77],"We":[78],"achieve":[79],"total":[81],"bandwidth":[83],"improvement":[84,131],"up":[86,127],"3.8X":[88],"MobileNet":[90],"ResNet":[92],"vs.":[93,132],"random":[94],"mappings.":[95],"Furthermore,":[96],"NEWROMAP":[97],"is":[98,123],"proposed":[99],"that":[100],"continues":[101],"optimize":[103],"through":[106],"meta-heuristic;":[108],"it":[109],"also":[110],"simulates":[111],"traffic":[114],"can":[116],"work":[117],"with":[118,126],"TensorFlow":[119],"models.":[120],"The":[121],"communication":[122],"further":[124],"optimized":[125],"22.52%":[129],"latency":[130],"pure":[133],"snake":[134],"shown":[136],"in":[137],"simulations.":[138]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2021-10-11T00:00:00"}
