{"id":"https://openalex.org/W2780799129","doi":"https://doi.org/10.1145/3139958.3140056","title":"A Spatial Join Algorithm Based on a Non-uniform Grid Technique over GPGPU","display_name":"A Spatial Join Algorithm Based on a Non-uniform Grid Technique over GPGPU","publication_year":2017,"publication_date":"2017-11-07","ids":{"openalex":"https://openalex.org/W2780799129","doi":"https://doi.org/10.1145/3139958.3140056","mag":"2780799129"},"language":"en","primary_location":{"id":"doi:10.1145/3139958.3140056","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3139958.3140056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","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/A5088227756","display_name":"Danial Aghajarian","orcid":"https://orcid.org/0000-0003-3405-3197"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danial Aghajarian","raw_affiliation_strings":["Computer Science Department, Georgia State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Georgia State University","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019829974","display_name":"Sushil K. Prasad","orcid":"https://orcid.org/0000-0002-2028-0703"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sushil K. Prasad","raw_affiliation_strings":["Computer Science Department, Georgia State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Georgia State University","institution_ids":["https://openalex.org/I181565077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181565077"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10996","display_name":"Computational Geometry and Mesh Generation","score":0.9901000261306763,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.8021447658538818},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.6793492436408997},{"id":"https://openalex.org/keywords/general-purpose-computing-on-graphics-processing-units","display_name":"General-purpose computing on graphics processing units","score":0.6632564663887024},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6229760050773621},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5893593430519104},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5787330269813538},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.48142334818840027},{"id":"https://openalex.org/keywords/computational-science","display_name":"Computational science","score":0.40844428539276123},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.27097105979919434},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.2049683928489685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0950976014137268}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8021447658538818},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.6793492436408997},{"id":"https://openalex.org/C50630238","wikidata":"https://www.wikidata.org/wiki/Q971505","display_name":"General-purpose computing on graphics processing units","level":3,"score":0.6632564663887024},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6229760050773621},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5893593430519104},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5787330269813538},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.48142334818840027},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.40844428539276123},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.27097105979919434},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.2049683928489685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0950976014137268},{"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:10.1145/3139958.3140056","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3139958.3140056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1585008090","https://openalex.org/W1839942897","https://openalex.org/W1973582313","https://openalex.org/W1993997820","https://openalex.org/W2087129702","https://openalex.org/W2098994245","https://openalex.org/W2269232576","https://openalex.org/W2567181308"],"related_works":["https://openalex.org/W2983282793","https://openalex.org/W1973046741","https://openalex.org/W1963859303","https://openalex.org/W2364044215","https://openalex.org/W2389600408","https://openalex.org/W240129890","https://openalex.org/W3048701459","https://openalex.org/W2149078538","https://openalex.org/W2080146221","https://openalex.org/W2370314112"],"abstract_inverted_index":{"Grid-based":[0],"techniques":[1,23],"are":[2,24,84],"well-suited":[3],"for":[4],"spatial":[5,51,111,166,237],"join":[6,52,112,167],"algorithms":[7,152],"over":[8,101],"General":[9],"Purpose":[10],"Graphic":[11],"Processing":[12],"Unit":[13],"(GPGPU)":[14],"architectures":[15],"because":[16],"of":[17,30,42,62,150,209,229],"their":[18,71,122],"non-hierarchical":[19],"structure.":[20],"However,":[21],"these":[22],"well-established":[25],"years":[26],"before":[27],"the":[28,139,207,210,224],"existence":[29],"GPU":[31,53,190],"computing.":[32],"As":[33],"a":[34,50,96,188,194],"result,":[35],"they":[36],"do":[37],"not":[38,75],"fully":[39],"take":[40],"advantage":[41],"many-core":[43],"architectures.":[44],"Last":[45],"year,":[46],"we":[47,92],"had":[48],"introduced":[49],"system":[54,168,215],"based":[55],"on":[56,128,132,187],"discarding":[57],"even":[58],"those":[59],"cross-layer":[60],"pairs":[61],"polygons":[63,180],"whose":[64],"Minimum":[65],"Bounding":[66],"Rectangles":[67],"(MBRs)":[68],"intersect":[69],"but":[70],"rectangular":[72],"intersection":[73],"does":[74],"contain":[76],"edges":[77,186],"from":[78],"both":[79],"layers.":[80],"These":[81],"MBR":[82],"intersections":[83],"called":[85],"Common":[86,103],"MBRs.":[87],"In":[88],"this":[89],"extended":[90],"abstract,":[91],"briefly":[93],"introduce":[94],"CMF-Grid:":[95],"non-uniform":[97],"GPU-based":[98,212],"grid":[99],"technique":[100],"such":[102,114],"MBRs,":[104],"that":[105,149,199],"can":[106,136],"be":[107],"used":[108],"in":[109,191],"polygonal":[110],"operations":[113],"as":[115,233,235],"overlay,":[116],"edge-intersection":[117],"etc.":[118],"to":[119,174,205,219],"significantly":[120],"reduce":[121],"computationally-extensive":[123],"refinement":[124,140],"phase":[125,141],"workload.":[126],"Based":[127],"our":[129],"experimental":[130],"results":[131],"real":[133],"datasets,":[134],"CMF-Grid":[135],"cut":[137],"down":[138],"workload":[142],"by":[143,161],"more":[144,176,182],"than":[145,177,183,193],"30,":[146],"000":[147,179],"times":[148],"all-to-all":[151],"and":[153],"it":[154],"improves":[155],"upon":[156],"its":[157],"predecessor,":[158],"CMF":[159],"filter,":[160],"700":[162],"times.":[163],"Our":[164],"upgraded":[165],"with":[169,181,239],"ST_intersect":[170],"predicate":[171],"is":[172,200],"able":[173],"process":[175],"600,":[178],"2":[184],"billions":[185],"single":[189],"less":[192],"second":[195],"end-to-end":[196,221],"processing":[197],"time":[198,202],"225%":[201],"improvement":[203],"compared":[204],"GCMF,":[206],"state":[208],"art":[211],"system.":[213],"The":[214],"also":[216],"achieves":[217],"up":[218],"200-fold":[220],"speedup":[222],"versus":[223],"best":[225],"optimized":[226],"sequential":[227],"routines":[228],"GEOS":[230],"C++":[231],"library":[232],"well":[234],"PostgreSQL":[236],"database":[238],"PostGIS.":[240]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
