{"id":"https://openalex.org/W4416429570","doi":"https://doi.org/10.1109/iccad66269.2025.11241006","title":"Energy-Efficient Accelerator for Scalable Point Transformer Networks with Reduced Data Access","display_name":"Energy-Efficient Accelerator for Scalable Point Transformer Networks with Reduced Data Access","publication_year":2025,"publication_date":"2025-10-26","ids":{"openalex":"https://openalex.org/W4416429570","doi":"https://doi.org/10.1109/iccad66269.2025.11241006"},"language":null,"primary_location":{"id":"doi:10.1109/iccad66269.2025.11241006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad66269.2025.11241006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/ACM International Conference On Computer Aided Design (ICCAD)","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/A5102585590","display_name":"Hyunsung Yoon","orcid":"https://orcid.org/0000-0003-2451-6370"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyunsung Yoon","raw_affiliation_strings":["Pohang University of Science and Technology,Pohang,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Pohang University of Science and Technology,Pohang,Republic of Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110045339","display_name":"Je\u2010Hun Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jehun Lee","raw_affiliation_strings":["Seoul National University,Seoul,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003219699","display_name":"Jae\u2010Joon Kim","orcid":"https://orcid.org/0000-0001-5175-8258"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae-Joon Kim","raw_affiliation_strings":["Seoul National University,Seoul,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102585590"],"corresponding_institution_ids":["https://openalex.org/I123900574"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.35917578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.7315000295639038,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.7315000295639038,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.04089999943971634,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.039000000804662704,"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/scalability","display_name":"Scalability","score":0.6026999950408936},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5414999723434448},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.4693000018596649},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.46059998869895935},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.4480000138282776},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.43799999356269836},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4300000071525574},{"id":"https://openalex.org/keywords/data-access","display_name":"Data access","score":0.42899999022483826},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.4251999855041504}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8158000111579895},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6026999950408936},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5414999723434448},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.4693000018596649},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.4480000138282776},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.43799999356269836},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4300000071525574},{"id":"https://openalex.org/C47487241","wikidata":"https://www.wikidata.org/wiki/Q5227230","display_name":"Data access","level":2,"score":0.42899999022483826},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4251999855041504},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.40639999508857727},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4002000093460083},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.37529999017715454},{"id":"https://openalex.org/C151300846","wikidata":"https://www.wikidata.org/wiki/Q125539","display_name":"Submanifold","level":2,"score":0.3709999918937683},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C2781357197","wikidata":"https://www.wikidata.org/wiki/Q5757597","display_name":"High memory","level":2,"score":0.35420000553131104},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.34470000863075256},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.31369999051094055},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.29330000281333923},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29319998621940613},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2890999913215637},{"id":"https://openalex.org/C176649486","wikidata":"https://www.wikidata.org/wiki/Q2308807","display_name":"Memory management","level":3,"score":0.27129998803138733},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.2639999985694885},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26190000772476196},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C82687282","wikidata":"https://www.wikidata.org/wiki/Q66221","display_name":"Auxiliary memory","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccad66269.2025.11241006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad66269.2025.11241006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/ACM International Conference On Computer Aided Design (ICCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321292","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2460657278","https://openalex.org/W2594519801","https://openalex.org/W2963125977","https://openalex.org/W2963182550","https://openalex.org/W3015248322","https://openalex.org/W3035574168","https://openalex.org/W3111535274","https://openalex.org/W3205343065","https://openalex.org/W3206429150","https://openalex.org/W4214755140","https://openalex.org/W4286571907","https://openalex.org/W4360606209","https://openalex.org/W4372283849","https://openalex.org/W4380874731","https://openalex.org/W4386113258","https://openalex.org/W4386763681","https://openalex.org/W4386763864","https://openalex.org/W4389162383","https://openalex.org/W4389162753","https://openalex.org/W4401635361","https://openalex.org/W4402667891","https://openalex.org/W4404133621"],"related_works":[],"abstract_inverted_index":{"Transformer-based":[0],"architectures":[1],"have":[2],"recently":[3],"emerged":[4],"as":[5],"the":[6,21,115,124],"backbone":[7],"for":[8,85,102,132],"neural":[9],"networks":[10],"handling":[11],"3D":[12,133,135],"point":[13,136],"cloud":[14],"applications,":[15],"achieving":[16],"state-of-the-art":[17],"accuracy":[18,156],"by":[19],"avoiding":[20],"computational":[22,60],"overhead":[23],"of":[24,117],"traditional":[25],"k-nearest":[26],"neighbor":[27],"(k-NN)":[28],"algorithms":[29],"widely":[30],"used":[31],"in":[32],"previous":[33],"models.":[34],"Despite":[35],"their":[36],"success,":[37],"these":[38,73],"transformer-based":[39,134],"models":[40],"often":[41],"rely":[42],"on":[43,123],"submanifold":[44,93],"convolution":[45],"and":[46,58,82,105,119,148],"attention":[47,103,151],"layers,":[48],"which":[49,88],"introduce":[50,77],"performance":[51],"bottlenecks":[52],"due":[53],"to":[54,71,113],"substantial":[55],"weight":[56],"parameters":[57],"high":[59],"demands.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65,76,96,126],"propose":[66,97],"two":[67],"key":[68],"hardware-friendly":[69],"optimizations":[70],"address":[72],"challenges.":[74],"First,":[75],"a":[78,98,128],"panel-level":[79],"kernel":[80],"mapping":[81],"weight-fetching":[83],"strategy":[84],"weight-stationary":[86],"computation,":[87],"minimizes":[89],"data":[90],"movement":[91],"during":[92],"convolution.":[94],"Second,":[95],"locality-based":[99],"compression":[100],"technique":[101],"queries":[104],"keys,":[106],"allowing":[107],"feature":[108],"reuse":[109],"from":[110],"neighboring":[111],"points":[112],"reduce":[114],"number":[116],"operations":[118],"memory":[120,146],"requirements.":[121],"Based":[122],"optimizations,":[125],"develop":[127],"dedicated":[129],"hardware":[130],"tailored":[131],"clouds.":[137],"Experimental":[138],"results":[139],"show":[140],"that":[141],"our":[142],"approach":[143],"significantly":[144],"reduces":[145],"accesses":[147],"enables":[149],"efficient":[150],"score":[152],"computation":[153],"with":[154],"negligible":[155],"loss.":[157]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-20T00:00:00"}