Abstract
The memory hierarchy affects the performance of task-scheduling strategies in task-based parallel environments. For data-intensive problems, the flow of data may be explicitly specified as a part of the algorithm, allowing the task scheduler to be aware of the data flow. In this paper, we describe such a task-based environment with explicit data-flow specification. We demonstrate the effect of data-flow awareness on the system performance. The results show that the explicit specification of data flow improves the quality of task scheduling.
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Bednárek, D., Dokulil, J., Yaghob, J., Zavoral, F. (2013). Data-Flow Awareness in Parallel Data Processing. In: Fortino, G., Badica, C., Malgeri, M., Unland, R. (eds) Intelligent Distributed Computing VI. Studies in Computational Intelligence, vol 446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32524-3_19
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DOI: https://doi.org/10.1007/978-3-642-32524-3_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32523-6
Online ISBN: 978-3-642-32524-3
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