{"id":"https://openalex.org/W4410552832","doi":"https://doi.org/10.23919/date64628.2025.10993228","title":"Performance Implications of Multi-Chiplet Neural Processing Units on Autonomous Driving Perception","display_name":"Performance Implications of Multi-Chiplet Neural Processing Units on Autonomous Driving Perception","publication_year":2025,"publication_date":"2025-03-31","ids":{"openalex":"https://openalex.org/W4410552832","doi":"https://doi.org/10.23919/date64628.2025.10993228"},"language":"en","primary_location":{"id":"doi:10.23919/date64628.2025.10993228","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date64628.2025.10993228","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Design, Automation &amp;amp; Test in Europe Conference (DATE)","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/A5045322212","display_name":"Mohanad Odema","orcid":"https://orcid.org/0000-0002-0828-949X"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohanad Odema","raw_affiliation_strings":["University of California,Irvine,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Irvine,USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100443520","display_name":"Luke Chen","orcid":"https://orcid.org/0000-0001-8027-6047"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Luke Chen","raw_affiliation_strings":["University of California,Irvine,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Irvine,USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074768327","display_name":"Hyoukjun Kwon","orcid":"https://orcid.org/0000-0001-9824-1352"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hyoukjun Kwon","raw_affiliation_strings":["University of California,Irvine,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Irvine,USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055814180","display_name":"Mohammad Abdullah Al Faruque","orcid":"https://orcid.org/0000-0002-5390-0497"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Abdullah Al Faruque","raw_affiliation_strings":["University of California,Irvine,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Irvine,USA","institution_ids":["https://openalex.org/I204250578"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5045322212"],"corresponding_institution_ids":["https://openalex.org/I204250578"],"apc_list":null,"apc_paid":null,"fwci":2.8414,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.90850732,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9693999886512756,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9693999886512756,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9142000079154968,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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":0.6423192024230957},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5236240029335022},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4405701160430908},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3781984746456146},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.12519964575767517},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.10408830642700195}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6423192024230957},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5236240029335022},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4405701160430908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3781984746456146},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.12519964575767517},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.10408830642700195}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/date64628.2025.10993228","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date64628.2025.10993228","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Design, Automation &amp;amp; Test in Europe Conference (DATE)","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":28,"referenced_works":["https://openalex.org/W2067523571","https://openalex.org/W2741014559","https://openalex.org/W2791175987","https://openalex.org/W2798722023","https://openalex.org/W2953901595","https://openalex.org/W2980104813","https://openalex.org/W2980200167","https://openalex.org/W2999356938","https://openalex.org/W3007788310","https://openalex.org/W3017521908","https://openalex.org/W3034971973","https://openalex.org/W3042495273","https://openalex.org/W3091953123","https://openalex.org/W3158233068","https://openalex.org/W3184369898","https://openalex.org/W3187788856","https://openalex.org/W4245911027","https://openalex.org/W4283395662","https://openalex.org/W4293025058","https://openalex.org/W4313152057","https://openalex.org/W4317793317","https://openalex.org/W4385245566","https://openalex.org/W4386764053","https://openalex.org/W4391623921","https://openalex.org/W4398238712","https://openalex.org/W4404955773","https://openalex.org/W6860057043","https://openalex.org/W6929505642"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"We":[0],"study":[1],"the":[2,48,59,83],"application":[3],"of":[4],"emerging":[5,31],"chiplet-based":[6],"Neural":[7],"Processing":[8],"Units":[9],"to":[10,30,91,125],"accelerate":[11],"vehicular":[12,32],"AI":[13,98],"perception":[14,45,62,94],"workloads":[15,52,95],"in":[16,53,118],"constrained":[17],"automotive":[18],"settings.":[19],"The":[20],"motivation":[21],"stems":[22],"from":[23,44],"how":[24],"chiplets":[25],"technology":[26],"is":[27],"becoming":[28],"integral":[29],"architectures,":[33],"providing":[34],"a":[35,54,65,87,103],"cost-effective":[36],"tradeoff":[37],"between":[38],"performance,":[39],"modularity,":[40],"and":[41,43,74,114,120],"customization;":[42],"models":[46,73],"being":[47],"most":[49],"computationally":[50],"demanding":[51],"autonomous":[55],"driving":[56],"system.":[57],"Using":[58],"Tesla":[60],"Autopilot":[61],"pipeline":[63],"as":[64],"case":[66],"study,":[67],"we":[68,85],"first":[69],"breakdown":[70],"its":[71],"constituent":[72],"profile":[75],"their":[76],"performance":[77,106],"on":[78,96],"different":[79],"chiplet":[80],"accelerators.":[81,99],"From":[82],"insights,":[84],"propose":[86],"novel":[88],"scheduling":[89],"strategy":[90],"efficiently":[92],"deploy":[93],"multi-chip":[97],"Our":[100],"experiments":[101],"using":[102],"standard":[104],"DNN":[105],"simulator,":[107],"MAESTRO,":[108],"show":[109],"our":[110],"approach":[111],"realizes":[112],"82%":[113],"2.8":[115],"\u00d7":[116],"increase":[117],"throughput":[119],"processing":[121],"engines":[122],"utilization":[123],"compared":[124],"monolithic":[126],"accelerator":[127],"designs.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
