Short communication: A framework for automating the configuration of OpenCL

Authors:
Raphael De Souza Rosa Gomes;Josiel Maimone Figueiredo;Claudia Aparecida Martins;Allan Gonçalves De Oliveira;José De Souza Nogueira
Affiliations:
Computer Institute, Federal University of Mato Grosso, Mato Grosso, Brazil;Computer Institute, Federal University of Mato Grosso, Mato Grosso, Brazil;Computer Institute, Federal University of Mato Grosso, Mato Grosso, Brazil;Computer Institute, Federal University of Mato Grosso, Mato Grosso, Brazil;Institute of Physics, Federal University of Mato Grosso, Mato Grosso, Brazil
Venue:
Environmental Modelling & Software
Year:
2014

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Abstract

Environmental research and scientific simulations use information acquired by sensors to validate the modeling and representation of environmental behaviors. The computational processing cost of this context tends to be extremely high due to the amount of information and the model's calculation complexities which demand the use of computational parallel solutions. This paper presents JSeriesCL, a framework for parallel processing of spatiotemporal series using graphics processors (GPGPU), more specifically OpenCL. GPU is cheaper than other solutions for parallel processing, such as clusters or grid, and JSeriesCL changes the way that GPU are used because it automates the configuration and management aspects of such devices. Fractal dimension and SEBS were used to validate the application of JSeriesCL over environmental data.