{"id":"https://openalex.org/W4395680528","doi":"https://doi.org/10.1109/jssc.2024.3386878","title":"A 28-nm Energy-Efficient Sparse Neural Network Processor for Point Cloud Applications Using Block-Wise Online Neighbor Searching","display_name":"A 28-nm Energy-Efficient Sparse Neural Network Processor for Point Cloud Applications Using Block-Wise Online Neighbor Searching","publication_year":2024,"publication_date":"2024-04-26","ids":{"openalex":"https://openalex.org/W4395680528","doi":"https://doi.org/10.1109/jssc.2024.3386878"},"language":"en","primary_location":{"id":"doi:10.1109/jssc.2024.3386878","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jssc.2024.3386878","pdf_url":null,"source":{"id":"https://openalex.org/S83637746","display_name":"IEEE Journal of Solid-State Circuits","issn_l":"0018-9200","issn":["0018-9200","1558-173X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Solid-State Circuits","raw_type":"journal-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/A5059135535","display_name":"Xiaoyu Feng","orcid":"https://orcid.org/0000-0002-3203-8682"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Feng","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3203-8682","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085072777","display_name":"Wenyu Sun","orcid":"https://orcid.org/0000-0002-4793-0972"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyu Sun","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4793-0972","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114430047","display_name":"Chen Tang","orcid":"https://orcid.org/0000-0002-3411-0078"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Tang","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3411-0078","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039208284","display_name":"Xinyuan Lin","orcid":"https://orcid.org/0009-0002-6881-5348"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyuan Lin","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-6881-5348","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053627404","display_name":"Jinshan Yue","orcid":"https://orcid.org/0000-0001-8234-7400"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinshan Yue","raw_affiliation_strings":["Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8234-7400","affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023755254","display_name":"Huazhong Yang","orcid":"https://orcid.org/0000-0003-2421-353X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huazhong Yang","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2421-353X","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045721867","display_name":"Yongpan Liu","orcid":"https://orcid.org/0000-0002-4892-2309"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongpan Liu","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4892-2309","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1514,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.76741833,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"59","issue":"9","first_page":"3070","last_page":"3081"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9984999895095825,"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":0.9984999895095825,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9950000047683716,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7475453615188599},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.7153230309486389},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6274921298027039},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5695784091949463},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5254356265068054},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4692178964614868},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.43969377875328064},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4358515739440918},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35958266258239746},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34728091955184937},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3423112630844116},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10348138213157654},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09734949469566345},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0537356436252594}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7475453615188599},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.7153230309486389},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6274921298027039},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5695784091949463},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5254356265068054},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4692178964614868},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.43969377875328064},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4358515739440918},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35958266258239746},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34728091955184937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3423112630844116},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10348138213157654},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09734949469566345},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0537356436252594},{"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:10.1109/jssc.2024.3386878","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jssc.2024.3386878","pdf_url":null,"source":{"id":"https://openalex.org/S83637746","display_name":"IEEE Journal of Solid-State Circuits","issn_l":"0018-9200","issn":["0018-9200","1558-173X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Solid-State Circuits","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G1411627799","display_name":null,"funder_award_id":"XDB44000000","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G760277085","display_name":null,"funder_award_id":"2021ZD0114402","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2048266589","https://openalex.org/W2115579991","https://openalex.org/W2289252105","https://openalex.org/W2624273542","https://openalex.org/W2761132374","https://openalex.org/W2895531329","https://openalex.org/W2897529137","https://openalex.org/W2899481200","https://openalex.org/W2949708697","https://openalex.org/W2988715931","https://openalex.org/W3035172746","https://openalex.org/W3035574168","https://openalex.org/W3037569159","https://openalex.org/W3127173651","https://openalex.org/W3167732492","https://openalex.org/W3168718178","https://openalex.org/W3184856857","https://openalex.org/W3206429150","https://openalex.org/W3207145355","https://openalex.org/W4206699317","https://openalex.org/W4286571907","https://openalex.org/W4308083737","https://openalex.org/W4310035885","https://openalex.org/W4310078553","https://openalex.org/W4312307873","https://openalex.org/W4313136902","https://openalex.org/W4352976885","https://openalex.org/W4362710863","https://openalex.org/W4380874731","https://openalex.org/W4382465451","https://openalex.org/W4383066393","https://openalex.org/W4389491903","https://openalex.org/W4389491921","https://openalex.org/W6739663239","https://openalex.org/W6739778489","https://openalex.org/W6763422710","https://openalex.org/W6789930856","https://openalex.org/W6809366383"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W1997222214","https://openalex.org/W2560439919","https://openalex.org/W4389340727","https://openalex.org/W3150465815","https://openalex.org/W2802581102","https://openalex.org/W4205786897"],"abstract_inverted_index":{"Voxel-based":[0],"point":[1,45,177],"cloud":[2,178],"networks":[3],"composed":[4],"of":[5,8,50,60,110],"multiple":[6,68,108,120],"kinds":[7,109],"sparse":[9,30,86,111],"convolutions":[10],"(SCONVs)":[11],"play":[12],"an":[13,113],"essential":[14],"role":[15],"in":[16,43,138],"emerging":[17],"applications":[18],"such":[19],"as":[20],"autonomous":[21],"driving":[22],"and":[23,57,64,94,100,115,131,142,171],"visual":[24],"navigation.":[25],"Many":[26],"researchers":[27],"have":[28],"proposed":[29,79],"processors":[31],"for":[32,107,119,175],"image":[33],"applications.":[34],"However,":[35],"they":[36],"cannot":[37],"properly":[38],"deal":[39],"with":[40,80,122],"three":[41,81],"problems":[42],"the":[44,157,163],"cloud,":[46],"including":[47],"low":[48],"efficiency":[49],"random":[51],"memory":[52,92,96,125],"access,":[53],"non-parallel":[54],"neighbor":[55],"search":[56],"area":[58],"overhead":[59],"supporting":[61,90],"hybrid":[62,117],"operators,":[63],"unbalanced":[65],"workload":[66],"among":[67],"cores.":[69],"In":[70],"this":[71],"work,":[72],"a":[73,84,98],"2-D/3-D":[74,169],"unified":[75,105,168],"SCONV":[76,102],"accelerator":[77,165],"is":[78,136,161],"key":[82],"features:":[83],"block-wise":[85],"data":[87,129],"storage":[88],"format":[89],"out-of-order":[91],"allocation":[93],"continuous":[95],"access;":[97],"high-throughput":[99],"reconfigurable":[101],"core":[103,132],"providing":[104],"support":[106,170],"CNNs;":[112],"asynchronous":[114],"synchronous":[116],"scheduler":[118],"cores":[121],"dynamic":[123],"on-chip":[124],"router":[126],"to":[127,166],"maximize":[128],"reusing":[130],"utilization.":[133],"This":[134],"chip":[135],"fabricated":[137],"28-nm":[139],"CMOS":[140],"technology":[141],"achieves":[143],"4.68-TOPS/W":[144],"peak":[145],"energy":[146],"efficiency,":[147],"2":[148],"<inline-formula":[149],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[150],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[151],"<tex-math":[152],"notation=\"LaTeX\">$\\times$</tex-math>":[153],"</inline-formula>":[154],"higher":[155],"than":[156],"previous":[158],"accelerator.":[159],"It":[160],"also":[162],"first":[164],"provide":[167],"end-to-end":[172],"inference":[173],"ability":[174],"voxel-based":[176],"networks.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}