Uma abordagem para a execução paralela de modelos de simulação

Detalhes bibliográficos
Ano de defesa: 2016
Autor(a) principal: Mazzonetto, Angela lattes
Orientador(a): Hölbig, Carlos Amaral lattes
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade de Passo Fundo
Programa de Pós-Graduação: Programa de Pós-Graduação em Computação Aplicada
Departamento: Instituto de Ciências Exatas e Geociências – ICEG
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: http://10.0.217.128:8080/jspui/handle/tede/1185
Resumo: In the current scenario of science and technology, many factors contribute to the increased volume of data used in the solution of real applications in di_erent areas, including data used in simulation models of crops and diseases. The results generated by these models are analyzed after with intent to assist in the decision-making process. However, with the increased coverage area or with the expansion of the simulation period, the amount of data needed can often derail the execution and therefore the processing of the results generated by the models. Thus, the use high-performance tools or computational techniques designed for optimizing and improving the execution of these models becomes essential. This work speci_es an e_cient parallelization method for the parallel execution of growth models of wheat's culture CSM-Cropsim: Wheat and statistical Model Output Calibration correction, applied in the correction of weather forecast generated by the Eta model of the CPTEC-INPE, objects of this research. For these models the master-slave approach, using MPI communication library, proved the most appropriate, since each of the executions are independent in both models evaluated. The results showed the tests were satisfactory and contributed to the e_cient parallel execution of the models and consequently to the extension of their coverage areas and/or the time series to be simulated.