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2018 | OriginalPaper | Chapter

Transparent Model-Driven Provisioning of Computing Resources for Numerically Intensive Simulations

Authors : Fabian Korte, Alexander Bufe, Christian Köhler, Gunther Brenner, Jens Grabowski, Philipp Wieder

Published in: Simulation Science

Publisher: Springer International Publishing

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Abstract

Many simulations require large amounts of computing power to be executed. Traditionally, the computing power is provided by large high performance computing clusters that are solely built for this purpose. However, modern data centers do not only provide access to these high performance computing systems, but also offer other types of computing resources e.g., cloud systems, grid systems, or access to specialized computing resources, such as clusters equipped with accelerator hardware. Hence, the researcher is confronted with the choice of picking a suitable computing resource type for his simulation and acquiring the knowledge on how to access and manage his simulation on the resource type of choice. This is a time consuming and cumbersome process and could greatly benefit from supportive tooling. In this paper, we introduce a framework that allows to describe the simulation application in a resource-independent manner. It furthermore helps to select a suitable resource type according to the requirements of the simulation application and to automatically provision the required computing resources. We demonstrate the feasibility of the approach by providing a case study from the area of fluid mechanics.

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Footnotes
1
At the time of this writing, two versions of the TOSCA standard exist, a formalized version [12] in XML and a simplified rendering in YAML [13]. GroupTemplates and GroupTypes are currently part of the TOSCA YAML rendering, but not part of the TOSCA XML specification.
 
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Metadata
Title
Transparent Model-Driven Provisioning of Computing Resources for Numerically Intensive Simulations
Authors
Fabian Korte
Alexander Bufe
Christian Köhler
Gunther Brenner
Jens Grabowski
Philipp Wieder
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-319-96271-9_11

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