{"id":"https://openalex.org/W7140200960","doi":"https://doi.org/10.48550/arxiv.2603.21167","title":"PC2IM: An Efficient In-Memory Computing Accelerator for 3D Point Cloud","display_name":"PC2IM: An Efficient In-Memory Computing Accelerator for 3D Point Cloud","publication_year":2026,"publication_date":"2026-03-22","ids":{"openalex":"https://openalex.org/W7140200960","doi":"https://doi.org/10.48550/arxiv.2603.21167"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.21167","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21167","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.21167","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Wang, Dengfeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Dengfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Cai, Shunqin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Shunqin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Sun, Yanan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Yanan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.2329999953508377,"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":0.2329999953508377,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.14669999480247498,"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":0.10939999669790268,"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/speedup","display_name":"Speedup","score":0.770799994468689},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6204000115394592},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5920000076293945},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5343000292778015},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.4781000018119812},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.45719999074935913},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.40869998931884766},{"id":"https://openalex.org/keywords/data-access","display_name":"Data access","score":0.3953000009059906},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.3785000145435333}],"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/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.770799994468689},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6204000115394592},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5920000076293945},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5343000292778015},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4781000018119812},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.45719999074935913},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.40869998931884766},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4032000005245209},{"id":"https://openalex.org/C47487241","wikidata":"https://www.wikidata.org/wiki/Q5227230","display_name":"Data access","level":2,"score":0.3953000009059906},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3785000145435333},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3499000072479248},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3427000045776367},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.33469998836517334},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C123593499","wikidata":"https://www.wikidata.org/wiki/Q6008583","display_name":"In-Memory Processing","level":5,"score":0.3167000114917755},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.31049999594688416},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C194080101","wikidata":"https://www.wikidata.org/wiki/Q46306","display_name":"Access time","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.2892000079154968},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C2781357197","wikidata":"https://www.wikidata.org/wiki/Q5757597","display_name":"High memory","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.27730000019073486},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C82687282","wikidata":"https://www.wikidata.org/wiki/Q66221","display_name":"Auxiliary memory","level":2,"score":0.25850000977516174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.21167","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21167","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.21167","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21167","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.8578024506568909,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"3D":[0,67],"point":[1,22,68,106,200],"cloud":[2,23,69,201],"neural":[3],"networks":[4],"have":[5],"significantly":[6],"enhanced":[7,194,210],"the":[8,18,21,77,100,113,117,125,147,186],"perceptual":[9],"capabilities":[10],"of":[11,119],"resource-limited":[12],"mobile":[13],"intelligent":[14],"systems.":[15],"However,":[16],"despite":[17],"transformative":[19],"impact,":[20],"algorithm":[24],"suffers":[25],"from":[26],"substantial":[27],"memory":[28,62,103,151],"access":[29,63,104],"during":[30],"data":[31,72,88],"preprocessing":[32,73],"and":[33,46,83,115,142,179,192,208],"imposes":[34],"a":[35,86,127],"burdensome":[36],"workload":[37],"on":[38,124],"feature":[39,157],"computing,":[40],"resulting":[41],"in":[42,65,169],"high":[43,177],"energy":[44,180,195,211],"consumption":[45],"latency.":[47],"In":[48],"this":[49],"paper,":[50],"an":[51,91,154],"efficient":[52,155],"SRAM-based":[53],"computing-in-memory":[54],"(SRAM-CIM)":[55],"accelerator":[56],"(PC2IM),":[57],"is":[58,81,96,135,163],"proposed":[59,82,187],"to":[60,98,137,165,198,214],"alleviate":[61],"bottlenecks":[64],"point-based":[66],"networks.":[70],"A":[71],"module":[74],"driven":[75],"by":[76,112],"customized":[78],"CIM":[79],"engines":[80],"incorporated":[84],"into":[85],"memory-efficient":[87],"flow.":[89],"Specifically,":[90],"approximate":[92],"distance":[93,121],"SRAM-CIM":[94],"(APD-CIM)":[95],"introduced":[97,136],"eliminate":[99],"repetitive":[101],"on-chip":[102],"for":[105,146],"clouds":[107],"that":[108,185],"are":[109],"spatially":[110],"partitioned":[111],"median":[114],"reduce":[116],"volume":[118],"temporary":[120,140],"data.":[122],"Building":[123],"APD-CIM,":[126],"two-level":[128],"Ping-Pong-MAX":[129],"Content":[130],"Addressable":[131],"Memory":[132],"(Ping-Pong-MAX":[133],"CAM)":[134],"adaptively":[138],"update":[139],"distances":[141],"perform":[143],"in-situ":[144],"search":[145],"maximum,":[148],"further":[149],"reducing":[150],"access.":[152],"Additionally,":[153],"CIM-based":[156],"computing":[158],"engine,":[159],"named":[160],"split-concatenate":[161],"SRAM-CIM,":[162],"presented":[164],"minimize":[166],"computation":[167],"latency":[168],"multi-layer":[170],"perceptron":[171],"with":[172],"high-precision":[173],"input,":[174],"while":[175],"maintaining":[176],"area":[178],"efficiency.":[181],"Experiment":[182],"results":[183],"show":[184],"PC2IM":[188,204],"demonstrates":[189],"1.5x":[190],"speedup":[191,207],"2.7x":[193],"efficiency":[196,212],"compared":[197,213],"state-of-the-art":[199],"accelerator.":[202],"Moreover,":[203],"achieves":[205],"3.5x":[206],"1518.9x":[209],"GPU":[215],"implementations.":[216]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-25T00:00:00"}