Abstract
The Master/Worker paradigm is one of the most commonly used by parallel/distributed application developers. This paradigm is easy to understand and is fairly close to the abstract concept of a wide range of applications. However, to obtain adequate performance indexes, such a paradigm must be managed in a very precise way. There are certain features, such as data distribution or the number of workers, that must be tuned properly in order to obtain such performance indexes, and in most cases they cannot be tuned statically since they depend on the particular conditions of each execution. In this context, dynamic tuning seems to be a highly promising approach since it provides the capability to change the parameters during the execution of the application to improve performance. In this paper, we demonstrate the usage of a dynamic tuning environment that allows for adaptation of the number of workers based on a theoretical model of Master/Worker behavior. The results show that such an approach significantly improves the execution time when the application modifies its behavior during execution.
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This work has been supported by the MCyT (Spain) under contract TIC2001-2592 and has been partially supported by the Generalitat de Catalunya – GRC 2001SGR-00218
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Morajko, A., César, E., Caymes-Scutari, P., Margalef, T., Sorribes, J., Luque, E. (2005). Automatic Tuning of Master/Worker Applications. In: Cunha, J.C., Medeiros, P.D. (eds) Euro-Par 2005 Parallel Processing. Euro-Par 2005. Lecture Notes in Computer Science, vol 3648. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11549468_14
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DOI: https://doi.org/10.1007/11549468_14
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