DZero data-intensive computing on the Open Science Grid [electronic resource].
- Washington, D.C. : United States. Dept. of Energy, 2007. and Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Physical Description:
- 8 pages : digital, PDF file
- Additional Creators:
- Fermi National Accelerator Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
- Restrictions on Access:
- Free-to-read Unrestricted online access
- High energy physics experiments periodically reprocess data, in order to take advantage of improved understanding of the detector and the data processing code. Between February and May 2007, the DZero experiment has reprocessed a substantial fraction of its dataset. This consists of half a billion events, corresponding to about 100 TB of data, organized in 300,000 files. The activity utilized resources from sites around the world, including a dozen sites participating to the Open Science Grid consortium (OSG). About 1,500 jobs were run every day across the OSG, consuming and producing hundreds of Gigabytes of data. Access to OSG computing and storage resources was coordinated by the SAM-Grid system. This system organized job access to a complex topology of data queues and job scheduling to clusters, using a SAM-Grid to OSG job forwarding infrastructure. For the first time in the lifetime of the experiment, a data intensive production activity was managed on a general purpose grid, such as OSG. This paper describes the implications of using OSG, where all resources are granted following an opportunistic model, the challenges of operating a data intensive activity over such large computing infrastructure, and the lessons learned throughout the project.
- Published through SciTech Connect., 09/01/2007., "fermilab-pub-07-462-cd", FT, Presented at International Conference on Computing in High Energy and Nuclear Physics (CHEP 07), Victoria, BC, Canada, 2-7 Sep 2007., and Abbott, B.; Garzoglio, G.; Baranovski, A.; Diesburg, M.; Kurca, T.; Mhashilkar, P.
- Funding Information:
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