Parallel computing applied to satellite images processing for solar resource estimates
Resumen:
This article presents the application of parallel computing techniques to process satellite imagery information for solar resource estimates. A distributed memory parallel algorithm is introduced, which is capable to generate the required inputs from visible channel images to feed a statistical solar irradiation model. The parallelization strategy consists in distributing the images within the available processors, and so, every image is accessed only by one process. The experimental analysis demonstrate that a maximum speedup value of 2.32 is achieved when using four computing resources, but beyond that point the performance rather decrease due to hard-disk input/output velocity.
| 2012 | |
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Parallel computing Satellite images Solar resource assessment |
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| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/21636 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC BY-NC-ND 4.0) |
| _version_ | 1875693097502900224 |
|---|---|
| author | Alonso-Suárez, Rodrigo |
| author2 | Nesmachnow, Sergio |
| author2_role | author |
| author_facet | Alonso-Suárez, Rodrigo Nesmachnow, Sergio |
| author_role | author |
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| collection | COLIBRI |
| dc.contributor.filiacion.none.fl_str_mv | Alonso-Suárez Rodrigo, Universidad de la República (Uruguay). Facultad de Ingeniería Nesmachnow Sergio, Universidad de la República (Uruguay). Facultad de Ingeniería |
| dc.creator.none.fl_str_mv | Alonso-Suárez, Rodrigo Nesmachnow, Sergio |
| dc.date.accessioned.none.fl_str_mv | 2019-08-09T18:35:34Z |
| dc.date.available.none.fl_str_mv | 2019-08-09T18:35:34Z |
| dc.date.issued.none.fl_str_mv | 2012 |
| dc.description.abstract.none.fl_txt_mv | This article presents the application of parallel computing techniques to process satellite imagery information for solar resource estimates. A distributed memory parallel algorithm is introduced, which is capable to generate the required inputs from visible channel images to feed a statistical solar irradiation model. The parallelization strategy consists in distributing the images within the available processors, and so, every image is accessed only by one process. The experimental analysis demonstrate that a maximum speedup value of 2.32 is achieved when using four computing resources, but beyond that point the performance rather decrease due to hard-disk input/output velocity. |
| dc.description.es.fl_txt_mv | Trabajo presentado al V High-Performance Computing Latin America Symposium. CLEI Electronic Journal 15. Buenos Aires 2012. |
| dc.format.mimetype.none.fl_str_mv | application/pdf |
| dc.identifier.citation.es.fl_str_mv | Alonso-Suárez, R y Nesmachnow, S. "Parallel computing applied to satellite images processing for solar resource estimates" [Preprint] Publicado en las Actas del V High-Performance Computing Latin America Symposium. CLEI Electronic Journal 15. Buenos Aires, 2012. |
| dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/21636 |
| dc.language.iso.none.fl_str_mv | en eng |
| dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC BY-NC-ND 4.0) |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.other.en.fl_str_mv | Parallel computing Satellite images Solar resource assessment |
| dc.title.none.fl_str_mv | Parallel computing applied to satellite images processing for solar resource estimates |
| dc.type.en.fl_str_mv | Preprint |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/preprint |
| dc.type.version.none.fl_str_mv | info:eu-repo/semantics/submittedVersion |
| description | Trabajo presentado al V High-Performance Computing Latin America Symposium. CLEI Electronic Journal 15. Buenos Aires 2012. |
| eu_rights_str_mv | openAccess |
| format | preprint |
| id | COLIBRI_c130e533e32d1c642889489356caf7b1 |
| identifier_str_mv | Alonso-Suárez, R y Nesmachnow, S. "Parallel computing applied to satellite images processing for solar resource estimates" [Preprint] Publicado en las Actas del V High-Performance Computing Latin America Symposium. CLEI Electronic Journal 15. Buenos Aires, 2012. |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | COLIBRI |
| network_name_str | COLIBRI |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/21636 |
| publishDate | 2012 |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | karina.camps@seciu.edu.uy |
| repository.name.fl_str_mv | COLIBRI - Universidad de la República |
| repository_id_str | 4771 |
| rights_invalid_str_mv | Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC BY-NC-ND 4.0) |
| spelling | Alonso-Suárez Rodrigo, Universidad de la República (Uruguay). Facultad de IngenieríaNesmachnow Sergio, Universidad de la República (Uruguay). Facultad de Ingeniería2019-08-09T18:35:34Z2019-08-09T18:35:34Z2012Alonso-Suárez, R y Nesmachnow, S. "Parallel computing applied to satellite images processing for solar resource estimates" [Preprint] Publicado en las Actas del V High-Performance Computing Latin America Symposium. CLEI Electronic Journal 15. Buenos Aires, 2012.https://hdl.handle.net/20.500.12008/21636Trabajo presentado al V High-Performance Computing Latin America Symposium. CLEI Electronic Journal 15. Buenos Aires 2012.This article presents the application of parallel computing techniques to process satellite imagery information for solar resource estimates. A distributed memory parallel algorithm is introduced, which is capable to generate the required inputs from visible channel images to feed a statistical solar irradiation model. The parallelization strategy consists in distributing the images within the available processors, and so, every image is accessed only by one process. The experimental analysis demonstrate that a maximum speedup value of 2.32 is achieved when using four computing resources, but beyond that point the performance rather decrease due to hard-disk input/output velocity.Submitted by Luna Fabiana (fabiana.luna@fic.edu.uy) on 2019-08-09T18:35:34Z No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) 2012_HPCLatam_parallel_processing.pdf: 306790 bytes, checksum: 5c2dabce500178901461ef86f6c6b989 (MD5)Made available in DSpace on 2019-08-09T18:35:34Z (GMT). No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) 2012_HPCLatam_parallel_processing.pdf: 306790 bytes, checksum: 5c2dabce500178901461ef86f6c6b989 (MD5) Previous issue date: 2012application/pdfenengLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC BY-NC-ND 4.0)Parallel computingSatellite imagesSolar resource assessmentParallel computing applied to satellite images processing for solar resource estimatesPreprintinfo:eu-repo/semantics/preprintinfo:eu-repo/semantics/submittedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaAlonso-Suárez, RodrigoNesmachnow, SergioLICENSElicense.txtlicense.txttext/plain; charset=utf-84267http://localhost:8080/xmlui/bitstream/20.500.12008/21636/5/license.txt6429389a7df7277b72b7924fdc7d47a9MD55CC-LICENSElicense_urllicense_urltext/plain; charset=utf-850http://localhost:8080/xmlui/bitstream/20.500.12008/21636/2/license_urla006180e3f5b2ad0b88185d14284c0e0MD52license_textlicense_texttext/html; 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- Universidad de la Repúblicafalse |
| spellingShingle | Parallel computing applied to satellite images processing for solar resource estimates Alonso-Suárez, Rodrigo Parallel computing Satellite images Solar resource assessment |
| status_str | submittedVersion |
| title | Parallel computing applied to satellite images processing for solar resource estimates |
| title_full | Parallel computing applied to satellite images processing for solar resource estimates |
| title_fullStr | Parallel computing applied to satellite images processing for solar resource estimates |
| title_full_unstemmed | Parallel computing applied to satellite images processing for solar resource estimates |
| title_short | Parallel computing applied to satellite images processing for solar resource estimates |
| title_sort | Parallel computing applied to satellite images processing for solar resource estimates |
| topic | Parallel computing Satellite images Solar resource assessment |
| url | https://hdl.handle.net/20.500.12008/21636 |
