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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2452

Title: Performance of R-GMA for monitoring grid jobs for CMS data production
Authors: Byrom, R
Colling, D
Fisher, SM
Grandi, C
Hobson, PR
Kyberd, P
MacEvoy, B
Nebrensky, JJ
Traylen, S
Publication Date: 2005
Publisher: IEEE
Citation: 2005 IEEE Nuclear Science Symposium Conference Record. 2: 860 - 864
Abstract: High energy physics experiments, such as the Compact Muon Solenoid (CMS) at the CERN laboratory in Geneva, have large-scale data processing requirements, with data accumulating at a rate of 1 Gbyte/s. This load comfortably exceeds any previous processing requirements and we believe it may be most efficiently satisfied through grid computing. Furthermore the production of large quantities of Monte Carlo simulated data provides an ideal test bed for grid technologies and will drive their development. One important challenge when using the grid for data analysis is the ability to monitor transparently the large number of jobs that are being executed simultaneously at multiple remote sites. R-GMA is a monitoring and information management service for distributed resources based on the grid monitoring architecture of the Global Grid Forum. We have previously developed a system allowing us to test its performance under a heavy load while using few real grid resources. We present the latest results on this system running on the LCG 2 grid test bed using the LCG 2.6.0 middleware release. For a sustained load equivalent to 7 generations of 1000 simultaneous jobs, R-GMA was able to transfer all published messages and store them in a database for 98% of the individual jobs. The failures experienced were at the remote sites, rather than at the archiver's MON box as had been expected.
URI: http://bura.brunel.ac.uk/handle/2438/2452
DOI: http://dx.doi.org/10.1109/NSSMIC.2005.1596391
ISBN: 0-7803-9221-3
ISSN: 1082-3654
Appears in Collections:School of Engineering and Design Research papers
Electronic and Computer Engineering

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