{"id":"https://openalex.org/W2783006705","doi":"https://doi.org/10.1109/bigdata.2017.8258042","title":"Fast interpolation of grid data at a non-grid point","display_name":"Fast interpolation of grid data at a non-grid point","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2783006705","doi":"https://doi.org/10.1109/bigdata.2017.8258042","mag":"2783006705"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2017.8258042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","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/A5101774031","display_name":"Hiroshi Inoue","orcid":"https://orcid.org/0000-0002-8238-0371"},"institutions":[{"id":"https://openalex.org/I4210145865","display_name":"IBM Research - Tokyo","ror":"https://ror.org/04915qk43","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210145865"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hiroshi Inoue","raw_affiliation_strings":["IBM Research-Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research-Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I4210145865"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101774031"],"corresponding_institution_ids":["https://openalex.org/I4210145865"],"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":"1163","last_page":"1172"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.8603765964508057},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8068007230758667},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.7485442161560059},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.716997504234314},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.590094268321991},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.508621096611023},{"id":"https://openalex.org/keywords/simd","display_name":"SIMD","score":0.4979851245880127},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.48278844356536865},{"id":"https://openalex.org/keywords/computational-science","display_name":"Computational science","score":0.45988190174102783},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.44649237394332886},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.4342532157897949},{"id":"https://openalex.org/keywords/image-scaling","display_name":"Image scaling","score":0.4176374673843384},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.39613935351371765},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3757726848125458},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3108770251274109},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2987141013145447},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.23628264665603638},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11133205890655518}],"concepts":[{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.8603765964508057},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8068007230758667},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.7485442161560059},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.716997504234314},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.590094268321991},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.508621096611023},{"id":"https://openalex.org/C150552126","wikidata":"https://www.wikidata.org/wiki/Q339387","display_name":"SIMD","level":2,"score":0.4979851245880127},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.48278844356536865},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.45988190174102783},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.44649237394332886},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.4342532157897949},{"id":"https://openalex.org/C27405340","wikidata":"https://www.wikidata.org/wiki/Q440296","display_name":"Image scaling","level":4,"score":0.4176374673843384},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.39613935351371765},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3757726848125458},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3108770251274109},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2987141013145447},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.23628264665603638},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11133205890655518},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2017.8258042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","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":11,"referenced_works":["https://openalex.org/W1974048680","https://openalex.org/W1981354790","https://openalex.org/W1991499584","https://openalex.org/W1997448249","https://openalex.org/W2029570992","https://openalex.org/W2138163882","https://openalex.org/W2157812230","https://openalex.org/W2253316886","https://openalex.org/W2440896129","https://openalex.org/W2540384919","https://openalex.org/W6728864257"],"related_works":["https://openalex.org/W2082634395","https://openalex.org/W2361821952","https://openalex.org/W2390710228","https://openalex.org/W3080827050","https://openalex.org/W2359696437","https://openalex.org/W2372506239","https://openalex.org/W3093557575","https://openalex.org/W2590654039","https://openalex.org/W2352808182","https://openalex.org/W2098518858"],"abstract_inverted_index":{"Defining":[0],"data":[1,9,58],"at":[2,61,84],"a":[3,11,62,120,124],"non-grid":[4,63],"point":[5],"by":[6],"interpolating":[7],"grid":[8,57],"is":[10,46],"common":[12],"operation":[13,32,69],"in":[14,140],"many":[15],"workloads":[16],"including":[17],"scientific":[18],"applications":[19,53],"and":[20,33,99,114,123,136],"imaging":[21,52],"applications.":[22],"This":[23],"paper":[24],"describes":[25],"our":[26,116],"technique":[27,118],"to":[28,92,134],"accelerate":[29],"this":[30,68],"interpolation":[31,122,127,147],"show":[34],"its":[35],"performance":[36,138],"benefit":[37],"using":[38,119],"3D":[39,44],"computed":[40],"tomography":[41],"reconstruction.":[42],"The":[43],"CT":[45],"one":[47],"of":[48,97,109],"the":[49,80,95,107,141,145],"compute-intensive":[50],"medical":[51],"that":[54,105],"frequently":[55],"interpolates":[56],"(2D":[59],"images)":[60],"point.":[64],"To":[65],"efficiently":[66],"execute":[67],"with":[70],"SIMD":[71,110],"instructions,":[72],"we":[73],"create":[74],"an":[75],"in-memory":[76],"pre-computed":[77],"table":[78],"from":[79],"input":[81],"2D":[82],"image":[83,91],"runtime":[85],"before":[86],"projecting":[87],"voxels":[88],"onto":[89],"each":[90],"1)":[93],"reduce":[94],"amount":[96],"computation":[98],"2)":[100],"avoid":[101],"non-contiguous":[102],"memory":[103],"accesses":[104],"attenuate":[106],"benefits":[108],"instructions.":[111],"We":[112],"implemented":[113],"evaluated":[115],"pre-computation":[117],"bilinear":[121],"3rd-degree":[125],"Lagrange":[126],"on":[128],"POWER8":[129],"processors;":[130],"it":[131],"yields":[132],"up":[133],"75%":[135],"57%":[137],"improvements":[139],"RabbitCT":[142],"benchmark":[143],"for":[144],"two":[146],"algorithms":[148],"respectively.":[149]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
