Abstract
Dynamically determining the appropriate number of threads for a multi-threaded application may lead to a higher efficiency than predetermining the number of threads beforehand. Interval branch-and-bound (B&B) global optimization algorithms are typically irregular algorithms that may benefit from the use of a dynamic number of threads. The question is how to obtain the necessary on line information to decide on the number of threads. We experiment with a scheme following a SPMD (Single Program, Multiple Data) and AMP (Asynchronous Multiple Pool) model. This means that all threads execute the same code and they are consequently affected by the same types of blocked time.
There exist several methods to measure the blocked time of an application. The basis for the data to be obtained is the information provided by the Linux Operating System (O.S.) for tasks: task_interruptible and task_uninterruptible block time. We elaborate on this, to determine new metrics allowing kernel and applications to collaborate through system calls in order to decide on the number of threads for an application.
This work has been funded by grants from the Spanish Ministry of Science and Innovation (TIN2008-01117), and Junta de Andalucía (P11-TIC-7176), in part financed by the European Regional Development Fund (ERDF). Eligius M. T. Hendrix is a fellow of the Spanish “Ramón y Cajal” contract program, co-financed by the European Social Fund.
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Sanjuan-Estrada, J.F., Casado, L.G., García, I., Hendrix, E.M.T. (2012). Performance Driven Cooperation between Kernel and Auto-tuning Multi-threaded Interval B&B Applications. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31125-3_5
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