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

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-...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Salvador, Jacobo, Sofía, Osiris, Orte, Facundo, Santos, Eder dos, Oyama, Hirofumi, Nagahama, Tomoo, Mizuno, Akira, Uribe Paredes, Roberto
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2015
Materias:
GPU
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/50143
Aporte de:
id I19-R120-10915-50143
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Parallel
radiative transfer model
GPU
openMP
spellingShingle Ciencias Informáticas
Parallel
radiative transfer model
GPU
openMP
Salvador, Jacobo
Sofía, Osiris
Orte, Facundo
Santos, Eder dos
Oyama, Hirofumi
Nagahama, Tomoo
Mizuno, Akira
Uribe Paredes, Roberto
Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA
topic_facet Ciencias Informáticas
Parallel
radiative transfer model
GPU
openMP
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.
format Objeto de conferencia
Objeto de conferencia
author Salvador, Jacobo
Sofía, Osiris
Orte, Facundo
Santos, Eder dos
Oyama, Hirofumi
Nagahama, Tomoo
Mizuno, Akira
Uribe Paredes, Roberto
author_facet Salvador, Jacobo
Sofía, Osiris
Orte, Facundo
Santos, Eder dos
Oyama, Hirofumi
Nagahama, Tomoo
Mizuno, Akira
Uribe Paredes, Roberto
author_sort Salvador, Jacobo
title Performance improvements of an atmospheric radiative transfer model on GPU-based platform using CUDA
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
publishDate 2015
url http://sedici.unlp.edu.ar/handle/10915/50143
work_keys_str_mv AT salvadorjacobo performanceimprovementsofanatmosphericradiativetransfermodelongpubasedplatformusingcuda
AT sofiaosiris performanceimprovementsofanatmosphericradiativetransfermodelongpubasedplatformusingcuda
AT ortefacundo performanceimprovementsofanatmosphericradiativetransfermodelongpubasedplatformusingcuda
AT santosederdos performanceimprovementsofanatmosphericradiativetransfermodelongpubasedplatformusingcuda
AT oyamahirofumi performanceimprovementsofanatmosphericradiativetransfermodelongpubasedplatformusingcuda
AT nagahamatomoo performanceimprovementsofanatmosphericradiativetransfermodelongpubasedplatformusingcuda
AT mizunoakira performanceimprovementsofanatmosphericradiativetransfermodelongpubasedplatformusingcuda
AT uribeparedesroberto performanceimprovementsofanatmosphericradiativetransfermodelongpubasedplatformusingcuda
bdutipo_str Repositorios
_version_ 1764820475523891204