Scalability tests of R-GMA-based grid job monitoring system for CMS Monte Carlo data production

• Published in: IEEE transactions on nuclear science Vol. 51; no. 6; pp. 3026 - 3029
• Main Authors: Bonacorsi, D., Colling, D., Field, L., Fisher, S.M., Grandi, C., Hobson, P.R., Kyberd, P., MacEvoy, B., Nebrensky, J.J., Tallini, H., Traylen, S.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-12-2004; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Collision mitigation; Computer architecture; Data processing; Information management; Job production systems; Large Hadron Collider; Large-scale systems; Monitoring systems; Monte Carlo methods; Remote monitoring; Scalability; Superconducting supercolliders; System testing
• ISSN: 0018-9499; 1558-1578
• DOI: 10.1109/TNS.2004.839094

High-energy physics experiments, such as the compact muon solenoid (CMS) at the large hadron collider (LHC), have large-scale data processing computing requirements. The grid has been chosen as the solution. One important challenge when using the grid for large-scale data processing is the ability to monitor the large numbers of jobs that are being executed simultaneously at multiple remote sites. The relational grid monitoring architecture (R-GMA) is a monitoring and information management service for distributed resources based on the GMA of the Global Grid Forum. We report on the first measurements of R-GMA as part of a monitoring architecture to be used for batch submission of multiple Monte Carlo simulation jobs running on a CMS-specific LHC computing grid test bed. Monitoring information was transferred in real time from remote execution nodes back to the submitting host and stored in a database. In scalability tests, the job submission rates supported by successive releases of R-GMA improved significantly, approaching that expected in full-scale production.