| 1. Identificação | |
| Tipo de Referência | Capítulo de Livro (Book Section) |
| Site | marte3.sid.inpe.br |
| Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identificador | 6qtX3pFwXQZ3r59YCT/H3N3s |
| Repositório | sid.inpe.br/iris@1905/2005/08.04.04.30 (acesso restrito) |
| Última Atualização | 2015:11.19.15.19.23 (UTC) marciana |
| Repositório de Metadados | sid.inpe.br/iris@1905/2005/08.04.04.30.29 |
| Última Atualização dos Metadados | 2018:06.06.03.55.53 (UTC) administrator |
| Chave Secundária | INPE--/ |
| Rótulo | 10669 |
| Chave de Citação | CamposVelhoVijStePreNow:2002:NeNeIm |
| Título | A neural network implementation for data assimilation using MPI, application of high performace computing in engineering  |
| Formato | ISBN 1-85312-924-0 |
| Ano | 2002 |
| Data Secundária | 20020608 |
| Data de Acesso | 28 abr. 2024 |
| Tipo Secundário | PRE LI |
| Número de Arquivos | 1 |
| Tamanho | 540 KiB |
| 2. Contextualização | |
| Autor | 1 Campos Velho, Haraldo Fraga 2 Vijaykumar, Nandamudi Lanlalapalli 3 Stephany, Stephan 4 Preto, Airam Jonatas 5 Nowosad, Alexandre Guirland |
| Grupo | 1 LAC-INPE-MCT-BR 2 LAC-INPE-MCT-BR 3 LAC-INPE-MCT-BR 4 5 LAC-INPE-MCT-BR |
| Editor | Brebia, C. A. Melli, P. Zanasi, A. . |
| Título do Livro | Application of high performace computing in engineering |
| Editora (Publisher) | WIT Press |
| Cidade | Southampton |
| Páginas | Section 5, 211-220 |
| Título da Série | Application of high performace computing in engineering |
| Histórico (UTC) | 2006-11-16 00:44:04 :: administrator -> jefferson :: 2007-08-14 14:04:51 :: jefferson -> administrator :: 2014-09-29 15:09:04 :: administrator -> marciana :: 2002 2015-11-19 15:19:23 :: marciana -> administrator :: 2002 2018-06-06 03:55:53 :: administrator -> jefferson :: 2002 |
| 3. Conteúdo e estrutura | |
| É a matriz ou uma cópia? | é a matriz |
| Estágio do Conteúdo | concluido |
| Transferível | 1 |
| Tipo do Conteúdo | External Contribution |
| Palavras-Chave | Neural networks Data assimilation COMPUTER SCIENCE |
| Resumo | ABSTRACT: Data assimilation is a procedure that uses observational data to improve the prediction made by an inaccurate mathematical model, as is the case of numerical weather prediction, air quality problems and numerical oceanic simulation. In the case of atmospheric continuous data assimilation there are many deterministic and probabilistic methods. Deterministic methods include dynamic relaxation, variational methods and Laplace transform, whereas probabilistic methods include optimal interpolation and Kalman Filtering. Dynamic relaxation assumes the prediction model to be perfect, as does Laplace transform. Variational methods and optimal interpolation can be regarded as minimum-mean-square estimation of the atmosphere. In Kalman filtering the analysis innovation is computed as a linear function of the misfit between observation and forecast. The use of a Multilayer Perceptron Neural Network was proposed in order to emulate Kalman Filtering method aiming at the reduction of the processing time. The training phase of this neural network is controlled by a supervised learning algorithm. Adjustment of the network learning is conducted by a backpropagation algorithm. Classical, hardware-independent optimizations were performed in the sequential code and led to a significant reduction in the processing time for a given set of parameters. Fortran 90 language intrinsics eliminated inefficient hand-coded subroutines. A former attempt to parallelize the code and run it in a 4-processor shared memory machine, made use of HPF (High Performance Fortran) directives imbedded in the optimized code. This work presents an attempt to parallelize the related code through a message passing paradigm, particularly the MPI (Message Passing Interface) standard. Calls to the MPI communication library were imbedded in the optimized code in order to assign chunks of data to individual processors. Besides, the imbedding of HPF directives in the MPI version is expected to further improve the performance of the code.. |
| Área | COMP |
| Arranjo | A neural network... |
| Conteúdo da Pasta doc | acessar |
| Conteúdo da Pasta source | não têm arquivos |
| Conteúdo da Pasta agreement | não têm arquivos |
| 4. Condições de acesso e uso | |
| Idioma | en |
| Arquivo Alvo | campos velho.pdf |
| Grupo de Usuários | administrator jefferson |
| Visibilidade | shown |
| Permissão de Leitura | deny from all and allow from 150.163 |
| Permissão de Atualização | não transferida |
| 5. Fontes relacionadas | |
| Unidades Imediatamente Superiores | 8JMKD3MGPCW/3ESGTTP |
| Divulgação | NTRSNASA; BNDEPOSITOLEGAL. |
| Acervo Hospedeiro | sid.inpe.br/banon/2001/04.03.15.36 |
| 6. Notas | |
| Campos Vazios | affiliation archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel doi e-mailaddress edition electronicmailaddress isbn issn lineage mark mirrorrepository nextedition notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup resumeid rightsholder schedulinginformation secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype translator url versiontype volume |
| 7. Controle da descrição | |
| e-Mail (login) | jefferson |
| atualizar | |