Publicado em: 11/12/2012

Tese de Doutorado em Processamento Paralelo e Distribuído

UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL
INSTITUTO DE INFORMÁTICA
PROGRAMA DE PÓS-GRADUAÇÃO EM COMPUTAÇÃO
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DEFESA DE TESE DE DOUTORADO

Aluno: Claudio Schepke
Orientador: Prof. Dr. Nicolas Bruno Maillard

Título: Exploiting Multilevel Parallelism in Atmospheric Models

Linha de Pesquisa: Processamento Paralelo e Distribuído

Data: 18/12/2012
Horário: 15h30min
Local: Auditório José Mauro Volkmer de Castilho, Prédio 43424 – Instituto de Informática

Banca Examinadora:
Profa. Dra. Andrea Schwertner Charão (UFSM)
Prof. Dr. Cláudio Fernando Resin Geyer (UFRGS)
Prof. Dr. Luiz Gustavo Leão Fernandes (PUCRS)

Presidente da Banca: Prof. Dr. Nicolas Bruno Maillard

Abstract:
Weather forecasts for long periods of time has emerged as increasingly important. The global concern with the consequences of climate changes has stimulated researches to determine the climate in coming decades. At the same time the steps needed to better defining the modeling and the simulation of climate/weather is far of the desired accuracy. Upscaling the land surface and consequently to increase the number of points used in climate modeling and the precision of the computed solutions is a goal that conflicts with the performance of numerical applications. Applications that include the interaction of long periods of time and involve a large number of operations become the expectation for results infeasible in traditional computers. With the introduction of multi-core processors and GPU boards, computers architectures have many parallel layers. Today, there are parallelism inside the processor, among processors and among computers. In order to use the best performance of the computers it is necessary to consider all parallel levels to distribute a concurrent application. However, nothing parallel programming interface abstracts all these different parallel levels. Based in this context, this thesis investigates how to explore different levels of parallelism in climatological models using mixed interfaces of parallel programming and how these models can provide mesh refinement at execution time. The performance results show that is possible to reduce the execution time of atmospheric simulations using different levels of parallelism, through the combined use of parallel programming interfaces. Therefore, more mesh resolution to describe the Earth’s atmosphere can be adopted, and consequently the numerical forecasts are more accurate.

Keywords: Multilevel Parallelism, Online Refinement of Unstructured Meshes, Ocean-Land-Atmosphere Model, Parallel Tasks, High Performance Computing.