Abstract
User analysis job demands can exceed available computing resources, especially before major conferences. ATLAS physics results can potentially be slowed down due to the lack of resources. For these reasons, cloud research and development activities are now included in the skeleton of the ATLAS computing model, which has been extended by using resources from commercial and private cloud providers to satisfy the demands. However, most of these activities are focused on Monte-Carlo production jobs, extending the resources at Tier-2. To evaluate the suitability of the cloud-computing model for user analysis jobs, we developed a framework to launch an ATLAS user analysis cluster in a cloud infrastructure on demand and evaluated two solutions. The first solution is entirely integrated in the Grid infrastructure by using the same mechanism, which is already in use at Tier-2: A designated Panda-Queue is monitored and additional worker nodes are launched in a cloud environment and assigned to a corresponding HTCondor queue according to the demand. Thereby, the use of cloud resources is completely transparent to the user. However, using this approach, submitted user analysis jobs can still suffer from a certain delay introduced by waiting time in the queue and the deployed infrastructure lacks customizability. Therefore, our second solution offers the possibility to easily deploy a totally private, customizable analysis cluster on private cloud resources belonging to the university.
Highlights
ATLAS user analysis on private cloud resources at GoeGridThis content has been downloaded from IOPscience
Several sites involved in the ATLAS computing model already extend their capacity by using additional computing resources from cloud providers
Above allows to extend Grid and cluster resources with worker nodes launched in cloud environments, it is limited to the configuration of additional computing nodes and lacks the possibility to manage more sophisticated infrastructures
Summary
This content has been downloaded from IOPscience. Please scroll down to see the full text. Ser. 664 022020 (http://iopscience.iop.org/1742-6596/664/2/022020) View the table of contents for this issue, or go to the journal homepage for more. Download details: IP Address: 188.184.3.52 This content was downloaded on 06/01/2016 at 16:08 Please note that terms and conditions apply. 21st International Conference on Computing in High Energy and Nuclear Physics (CHEP2015) IOP Publishing. Journal of Physics: Conference Series 664 (2015) 022020 doi:10.1088/1742-6596/664/2/022020
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