A framework for automating the configuration of OpenCL

被引：1

作者：

Rosa Gomes, Raphael de Souza ^{[1
]}

Figueiredo, Josiel Maimone ^{[1
]}

Martins, Claudia Aparecida ^{[1
]}

de Oliveira, Allan Goncalves ^{[1
]}

Nogueira, Jose de Souza ^{[2
]}

机构：

[1] Univ Fed Mato Grosso, Comp Inst, Mato Grosso, Brazil

[2] Univ Fed Mato Grosso, Inst Phys, Mato Grosso, Brazil

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2014年 / 53卷

关键词：

GPU; OpenCL; Parallelism; Environmental data; Fractal dimension; SEBS; Spatiotemporal series; BALANCE SYSTEM SEBS;

D O I：

10.1016/j.envsoft.2013.11.005

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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 CPU 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. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：81 / 86

页数：6

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