{"id":"https://openalex.org/W2740400896","doi":"https://doi.org/10.1145/3090354.3090445","title":"Novel parallel Givens QR decomposition implementation on VLIW architecture with Efficient memory access for real time image processing applications","display_name":"Novel parallel Givens QR decomposition implementation on VLIW architecture with Efficient memory access for real time image processing applications","publication_year":2017,"publication_date":"2017-03-29","ids":{"openalex":"https://openalex.org/W2740400896","doi":"https://doi.org/10.1145/3090354.3090445","mag":"2740400896"},"language":"en","primary_location":{"id":"doi:10.1145/3090354.3090445","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3090354.3090445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd international Conference on Big Data, Cloud and Applications","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/A5022604506","display_name":"Mohamed Najoui","orcid":"https://orcid.org/0000-0002-3008-0406"},"institutions":[{"id":"https://openalex.org/I119856527","display_name":"Cadi Ayyad University","ror":"https://ror.org/04xf6nm78","country_code":"MA","type":"education","lineage":["https://openalex.org/I119856527"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Mohamed Najoui","raw_affiliation_strings":["LGECOS Lab ENSA-Marrakech, University of Cadi Ayyad, Marrakech, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LGECOS Lab ENSA-Marrakech, University of Cadi Ayyad, Marrakech, Morocco","institution_ids":["https://openalex.org/I119856527"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076574050","display_name":"Anas Hatim","orcid":"https://orcid.org/0000-0002-3540-8036"},"institutions":[{"id":"https://openalex.org/I4210088687","display_name":"Universit\u00e9 Ibn Zohr","ror":"https://ror.org/006sgpv47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210088687"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Anas Hatim","raw_affiliation_strings":["ENSA-Agadir, Ibn Zohr University, Agadir, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ENSA-Agadir, Ibn Zohr University, Agadir, Morocco","institution_ids":["https://openalex.org/I4210088687"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059874562","display_name":"Sa\u00efd Belkouch","orcid":null},"institutions":[{"id":"https://openalex.org/I119856527","display_name":"Cadi Ayyad University","ror":"https://ror.org/04xf6nm78","country_code":"MA","type":"education","lineage":["https://openalex.org/I119856527"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Said Belkouch","raw_affiliation_strings":["LGECOS Lab ENSA-Marrakech, University of Cadi Ayyad, Marrakech, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LGECOS Lab ENSA-Marrakech, University of Cadi Ayyad, Marrakech, Morocco","institution_ids":["https://openalex.org/I119856527"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.247,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5483912,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.998199999332428,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9979000091552734,"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":0.8411000967025757},{"id":"https://openalex.org/keywords/very-long-instruction-word","display_name":"Very long instruction word","score":0.7156848907470703},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.580858051776886},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5411997437477112},{"id":"https://openalex.org/keywords/qr-decomposition","display_name":"QR decomposition","score":0.4829823076725006},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.42794060707092285},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3852836489677429},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3557126224040985}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8411000967025757},{"id":"https://openalex.org/C170595534","wikidata":"https://www.wikidata.org/wiki/Q249743","display_name":"Very long instruction word","level":2,"score":0.7156848907470703},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.580858051776886},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5411997437477112},{"id":"https://openalex.org/C188060507","wikidata":"https://www.wikidata.org/wiki/Q653242","display_name":"QR decomposition","level":3,"score":0.4829823076725006},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.42794060707092285},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3852836489677429},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3557126224040985},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3090354.3090445","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3090354.3090445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd international Conference on Big Data, Cloud and Applications","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":20,"referenced_works":["https://openalex.org/W1973241971","https://openalex.org/W1990668219","https://openalex.org/W2007272792","https://openalex.org/W2017079635","https://openalex.org/W2029015206","https://openalex.org/W2029816571","https://openalex.org/W2029919765","https://openalex.org/W2075894130","https://openalex.org/W2085093708","https://openalex.org/W2103559027","https://openalex.org/W2129638195","https://openalex.org/W2157758640","https://openalex.org/W2165100315","https://openalex.org/W2296616510","https://openalex.org/W2490093473","https://openalex.org/W3023634467","https://openalex.org/W4237207823","https://openalex.org/W4250955649","https://openalex.org/W4254479912","https://openalex.org/W7138849410"],"related_works":["https://openalex.org/W1897551170","https://openalex.org/W4237406352","https://openalex.org/W2000139719","https://openalex.org/W2164795702","https://openalex.org/W1534779213","https://openalex.org/W2171145238","https://openalex.org/W2021406864","https://openalex.org/W2387078853","https://openalex.org/W2374455716","https://openalex.org/W2363990172"],"abstract_inverted_index":{"Compressed":[0],"Sensing":[1],"(CS)":[2],"methods":[3],"impact":[4],"is":[5,23,33,47,65,76,125,142,159,183,189],"important":[6],"in":[7,42,73,87],"the":[8,15,36,66,79,85,93,101,162,180,218],"health":[9],"care":[10],"systems.":[11],"The":[12,62,186,198],"acquisition":[13],"and":[14,55,69,96,130,136,154,170,194,204,215],"processing":[16,181],"speed":[17],"of":[18,35,78,113,217],"many":[19],"medical":[20],"imaging":[21],"applications":[22],"highly":[24],"improved":[25],"using":[26],"this":[27,108],"technique.":[28],"Orthogonal":[29],"Matching":[30],"Pursuit":[31],"(OMP)":[32],"one":[34,77],"widely":[37],"used":[38,82],"image":[39,95],"reconstruction":[40],"algorithms":[41],"CS":[43],"techniques.":[44],"Traditionally,":[45],"OMP":[46],"divided":[48],"on":[49,115,150,191],"two":[50],"main":[51,80],"tasks:":[52],"optimization":[53],"stage":[54],"least":[56],"square":[57],"problem":[58],"(LSP)":[59],"resolution":[60,64],"stage.":[61],"LSP":[63,86],"most":[67],"complex":[68],"time":[70,103,182],"consuming":[71],"step":[72],"OMP.":[74],"QRD":[75,114,140,214],"techniques":[81,158],"to":[83],"solve":[84],"a":[88,110,177],"very":[89,105],"short":[90],"time.":[91],"However,":[92],"increasing":[94],"video":[97],"resolutions":[98],"(UHDTV)":[99],"makes":[100],"real":[102],"constraints":[104],"tight.":[106],"In":[107],"paper,":[109],"novel":[111],"implementation":[112],"VLIW":[116],"DSP":[117,193],"architecture":[118],"with":[119],"an":[120],"efficient":[121],"memory":[122,146,167],"access":[123,147],"approach":[124],"introduced.":[126],"An":[127],"instruction,":[128],"data":[129,156],"loop":[131],"levels":[132],"parallelism":[133],"(ILP,":[134],"DLP":[135],"LLP)":[137],"based":[138,149],"Givens":[139],"kernel":[141],"designed.":[143],"A":[144],"robust":[145],"management":[148],"intelligent":[151],"loading/storing":[152],"strategies":[153],"proficient":[155],"alignment":[157],"adopted":[160],"for":[161],"proposed":[163,187],"parallel":[164],"implementation.":[165],"Therefore,":[166],"read":[168],"misses":[169],"CPU":[171],"stalls":[172],"are":[173,201],"significantly":[174],"diminished.":[175],"As":[176],"final":[178],"result":[179],"greatly":[184],"reduced.":[185],"scheme":[188],"implemented":[190],"C6678":[192],"reaches":[195],"2.22":[196],"GFLOPS.":[197],"performances":[199],"achieved":[200],"7.4,":[202],"3.83":[203],"2":[205],"times":[206],"faster":[207],"than":[208],"standard":[209],"Givens,":[210],"Texas":[211],"Instrument":[212],"optimized":[213],"state":[216],"art,":[219],"respectively.":[220]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
