Abstract
Elasticity can be seen as the ability of a system to increase or decrease the computing resources allocated in a dynamic and on demand way. Considering its importance, some mechanisms to explore elasticity have been proposed by public providers and by academy. However, these solutions are inappropriate to provide elasticity for scientific applications or are limited to a specific programming model. In this context, we present Cloudine, a platform for development of elastic scientific applications based in simple elasticity primitives. These primitives enable the dynamic allocation and deallocation of resources in several levels, ranging from nodes of a virtual cluster, to virtual processors and memory of a node. Using this basic building blocks it is possible to develop applications in different models. The Cloudine effectiveness is demonstrated in the experiments, where two elastic applications in different models were developed.
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Galante, G., Bona, L.C.E. (2013). Constructing Elastic Scientific Applications Using Elasticity Primitives. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2013. ICCSA 2013. Lecture Notes in Computer Science, vol 7975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39640-3_21
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DOI: https://doi.org/10.1007/978-3-642-39640-3_21
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