high performance computing on graphics processing units: hgpu.org

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. To overcome this situation, a climatic model can take different levels of refinement of the Earth’s surface, using more discretized elements only in regions where more precision are required. This is the case of Ocean-Land- Atmosphere Model, which allows the static refinement of a particular region of the Earth in the early execution of the code. However, a dynamic mesh refinement could allow to better understand specific climatic conditions that appear at execution time of any region of the Earth’s surface, without restarting execution. 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. Higher performance for the execution of atmospheric applications that use online mesh refinement was also provided. Therefore, more mesh resolution to describe the Earth’s atmosphere can be adopted, and consequently the numerical forecasts are more accurate.