Support for Urgent Computing Based on Resource Virtualization. Cencerrado, A., Senar, M., & Cortés, A. In Allen, G., Nabrzyski, J., Seidel, E., van Albada , G. D., Dongarra, J., & Sloot, P. M. A., editors, Computational Science - ICCS 2009, volume 5544, of Lecture Notes in Computer Science, pages 227–236. Springer Berlin Heidelberg, Berlin, Heidelberg, 2009. doi abstract bibtex Virtualization technologies provide flexible execution environments that could bring important benefits for computational problems with strong deadlines. Large Grid infrastructures are becoming available nowadays and they could be a suitable environment to run such on-demand computations that might be used in decision-making processes. For these computation, we encounter the need to deliver as much resources as possible at particular times. These resources may be provided by different institutions belonging to a grid infrastructure but there are two important issues that must be satisfied. Firstly, all resources must be correctly configured and all the components needed by the application must be properly installed. If there is something small missing that is required then applications will fail. Secondly, the execution of urgent applications must be made quickly in order to produce useful results in time. If applications must wait in a queue, results might be useless because they are obtained too late. To address these issues, we describe a job management service, based on virtualization techniques, that avoids configuration problems and increases the number of available resources to run applications with critical deadlines. We describe the main components of our service that can be used on top of common batch queue systems and we show some experimental results that prove the benefits of applying time-sharing techniques on the virtual machines to increase the performance of urgent computations.
@incollection{cencerradoSupportUrgentComputing2009,
title = {Support for {{Urgent Computing Based}} on {{Resource Virtualization}}},
booktitle = {Computational {{Science}} - {{ICCS}} 2009},
author = {Cencerrado, Andr{\'e}s and Senar, Miquel and Cort{\'e}s, Ana},
editor = {Allen, Gabrielle and Nabrzyski, Jaros{\l}aw and Seidel, Edward and {van Albada}, Geert D. and Dongarra, Jack and Sloot, Peter M. A.},
year = {2009},
volume = {5544},
pages = {227--236},
publisher = {{Springer Berlin Heidelberg}},
address = {{Berlin, Heidelberg}},
doi = {10.1007/978-3-642-01970-8\\_23},
abstract = {Virtualization technologies provide flexible execution environments that could bring important benefits for computational problems with strong deadlines. Large Grid infrastructures are becoming available nowadays and they could be a suitable environment to run such on-demand computations that might be used in decision-making processes. For these computation, we encounter the need to deliver as much resources as possible at particular times. These resources may be provided by different institutions belonging to a grid infrastructure but there are two important issues that must be satisfied. Firstly, all resources must be correctly configured and all the components needed by the application must be properly installed. If there is something small missing that is required then applications will fail. Secondly, the execution of urgent applications must be made quickly in order to produce useful results in time. If applications must wait in a queue, results might be useless because they are obtained too late. To address these issues, we describe a job management service, based on virtualization techniques, that avoids configuration problems and increases the number of available resources to run applications with critical deadlines. We describe the main components of our service that can be used on top of common batch queue systems and we show some experimental results that prove the benefits of applying time-sharing techniques on the virtual machines to increase the performance of urgent computations.},
isbn = {978-3-642-01969-2},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-7358874,computational-science,emergency-events,urgent-hpc},
lccn = {INRMM-MiD:c-7358874},
series = {Lecture {{Notes}} in {{Computer Science}}}
}
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