Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA

Autores
Salvador, Jacobo; Sofía, Osiris; Orte, Facundo; Santos, Eder dos; Oyama, Hirofumi; Nagahama, Tomoo; Mizuno, Akira; Uribe Paredes, Roberto
Año de publicación
2015
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Classical applications of Atmospheric Radiative Transfer Model (ARTM) for modelization of absorption coefficient line-by-line on the atmosphere consume large computational time since seconds up to a few minutes depending on the atmospheric characterization chosen. ARTM is used together with Ground- Based or Satellite measurements to retrieve atmospheric parameters such as ozone, water vapour and temperature profiles. Nowadays in the Atmospheric Observatory of Southern Patagonia (OAPA) at the Patagonian City of Río Gallegos have been deployed a Spectral Millimeter Wave Radiometer belonging Nagoya Univ. (Japan) with the aim of retrieve stratospheric ozone profiles between 20-80 Km. Around 2 GBytes of data are recorder by the instrument per day and the ozone profiles are retrieving using one hour integration spectral data, resulting at 24 profiles per day. Actually the data reduction is performed by Laser and Application Research Center (CEILAP) group using the Matlab package ARTS/QPACK2. Using the classical data reduction procedure, the computational time estimated per profile is between 4-5 minutes determined mainly by the computational time of the ARTM and matrix operations. We propose in this work first add a novel scheme to accelerate the processing speed of the ARTM using the powerful multi-threading setup of GPGPU based at Compute Unified Device Architecture (CUDA) and compare it with the existing schemes. Performance of the ARTM has been calculated using various settings applied on a NVIDIA graphic Card GeForce GTX 560 Compute Capability 2.1. Comparison of the execution time between sequential mode, Open-MP and CUDA has been tested in this paper.
XV Workshop de Procesamiento Distribuido y Paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Parallel
radiative transfer model
GPU
openMP
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/50143
Acceder
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spelling Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDASalvador, JacoboSofía, OsirisOrte, FacundoSantos, Eder dosOyama, HirofumiNagahama, TomooMizuno, AkiraUribe Paredes, RobertoCiencias InformáticasParallelradiative transfer modelGPUopenMPClassical applications of Atmospheric Radiative Transfer Model (ARTM) for modelization of absorption coefficient line-by-line on the atmosphere consume large computational time since seconds up to a few minutes depending on the atmospheric characterization chosen. ARTM is used together with Ground- Based or Satellite measurements to retrieve atmospheric parameters such as ozone, water vapour and temperature profiles. Nowadays in the Atmospheric Observatory of Southern Patagonia (OAPA) at the Patagonian City of Río Gallegos have been deployed a Spectral Millimeter Wave Radiometer belonging Nagoya Univ. (Japan) with the aim of retrieve stratospheric ozone profiles between 20-80 Km. Around 2 GBytes of data are recorder by the instrument per day and the ozone profiles are retrieving using one hour integration spectral data, resulting at 24 profiles per day. Actually the data reduction is performed by Laser and Application Research Center (CEILAP) group using the Matlab package ARTS/QPACK2. Using the classical data reduction procedure, the computational time estimated per profile is between 4-5 minutes determined mainly by the computational time of the ARTM and matrix operations. We propose in this work first add a novel scheme to accelerate the processing speed of the ARTM using the powerful multi-threading setup of GPGPU based at Compute Unified Device Architecture (CUDA) and compare it with the existing schemes. Performance of the ARTM has been calculated using various settings applied on a NVIDIA graphic Card GeForce GTX 560 Compute Capability 2.1. Comparison of the execution time between sequential mode, Open-MP and CUDA has been tested in this paper.XV Workshop de Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI)2015-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/50143enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-3806-05-6info:eu-repo/semantics/reference/hdl/10915/50028info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:03:51Zoai:sedici.unlp.edu.ar:10915/50143Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:03:52.239SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA
title Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA
spellingShingle Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA
Salvador, Jacobo
Ciencias Informáticas
Parallel
radiative transfer model
GPU
openMP
title_short Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA
title_full Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA
title_fullStr Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA
title_full_unstemmed Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA
title_sort Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA
dc.creator.none.fl_str_mv Salvador, Jacobo
Sofía, Osiris
Orte, Facundo
Santos, Eder dos
Oyama, Hirofumi
Nagahama, Tomoo
Mizuno, Akira
Uribe Paredes, Roberto
author Salvador, Jacobo
author_facet Salvador, Jacobo
Sofía, Osiris
Orte, Facundo
Santos, Eder dos
Oyama, Hirofumi
Nagahama, Tomoo
Mizuno, Akira
Uribe Paredes, Roberto
author_role author
author2 Sofía, Osiris
Orte, Facundo
Santos, Eder dos
Oyama, Hirofumi
Nagahama, Tomoo
Mizuno, Akira
Uribe Paredes, Roberto
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Parallel
radiative transfer model
GPU
openMP
topic Ciencias Informáticas
Parallel
radiative transfer model
GPU
openMP
dc.description.none.fl_txt_mv Classical applications of Atmospheric Radiative Transfer Model (ARTM) for modelization of absorption coefficient line-by-line on the atmosphere consume large computational time since seconds up to a few minutes depending on the atmospheric characterization chosen. ARTM is used together with Ground- Based or Satellite measurements to retrieve atmospheric parameters such as ozone, water vapour and temperature profiles. Nowadays in the Atmospheric Observatory of Southern Patagonia (OAPA) at the Patagonian City of Río Gallegos have been deployed a Spectral Millimeter Wave Radiometer belonging Nagoya Univ. (Japan) with the aim of retrieve stratospheric ozone profiles between 20-80 Km. Around 2 GBytes of data are recorder by the instrument per day and the ozone profiles are retrieving using one hour integration spectral data, resulting at 24 profiles per day. Actually the data reduction is performed by Laser and Application Research Center (CEILAP) group using the Matlab package ARTS/QPACK2. Using the classical data reduction procedure, the computational time estimated per profile is between 4-5 minutes determined mainly by the computational time of the ARTM and matrix operations. We propose in this work first add a novel scheme to accelerate the processing speed of the ARTM using the powerful multi-threading setup of GPGPU based at Compute Unified Device Architecture (CUDA) and compare it with the existing schemes. Performance of the ARTM has been calculated using various settings applied on a NVIDIA graphic Card GeForce GTX 560 Compute Capability 2.1. Comparison of the execution time between sequential mode, Open-MP and CUDA has been tested in this paper.
XV Workshop de Procesamiento Distribuido y Paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
description Classical applications of Atmospheric Radiative Transfer Model (ARTM) for modelization of absorption coefficient line-by-line on the atmosphere consume large computational time since seconds up to a few minutes depending on the atmospheric characterization chosen. ARTM is used together with Ground- Based or Satellite measurements to retrieve atmospheric parameters such as ozone, water vapour and temperature profiles. Nowadays in the Atmospheric Observatory of Southern Patagonia (OAPA) at the Patagonian City of Río Gallegos have been deployed a Spectral Millimeter Wave Radiometer belonging Nagoya Univ. (Japan) with the aim of retrieve stratospheric ozone profiles between 20-80 Km. Around 2 GBytes of data are recorder by the instrument per day and the ozone profiles are retrieving using one hour integration spectral data, resulting at 24 profiles per day. Actually the data reduction is performed by Laser and Application Research Center (CEILAP) group using the Matlab package ARTS/QPACK2. Using the classical data reduction procedure, the computational time estimated per profile is between 4-5 minutes determined mainly by the computational time of the ARTM and matrix operations. We propose in this work first add a novel scheme to accelerate the processing speed of the ARTM using the powerful multi-threading setup of GPGPU based at Compute Unified Device Architecture (CUDA) and compare it with the existing schemes. Performance of the ARTM has been calculated using various settings applied on a NVIDIA graphic Card GeForce GTX 560 Compute Capability 2.1. Comparison of the execution time between sequential mode, Open-MP and CUDA has been tested in this paper.
publishDate 2015
dc.date.none.fl_str_mv 2015-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/50143
url http://sedici.unlp.edu.ar/handle/10915/50143
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-987-3806-05-6
info:eu-repo/semantics/reference/hdl/10915/50028
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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