Abstract
Developing fuzzy applications contain many steps. Each part may require lots of computation cycles depending on applications and target platforms. In this work, we study the parallelism in fuzzy systems using openMP and its possibility in embedded plaforms. Two versions of the parallelization are mentioned: fine-grained and coarse-grained parallelism. In our study, we found that the coarse-grained approach is more effective due to the overhead of openMP which becomes more visible in the low-speed CPU. Thus, the coarse-grained approach is suggested. Two versions using paralle-for and section are proposed. Two versions give different speedup rate depending on characteristics of the applications and fuzzy parameters. In general, the experiments convey that as the system runs continuously the openMP implementation can achieve a certain speedup, overcoming the openMP overhead by the proposed parallelization schemes.
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Chantrapornchai (Phongpensri), C., Pipatpaisan, J. (2010). Fuzzy Application Parallelization Using OpenMP. In: Sato, M., Hanawa, T., Müller, M.S., Chapman, B.M., de Supinski, B.R. (eds) Beyond Loop Level Parallelism in OpenMP: Accelerators, Tasking and More. IWOMP 2010. Lecture Notes in Computer Science, vol 6132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13217-9_10
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DOI: https://doi.org/10.1007/978-3-642-13217-9_10
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