학술논문

The ALICE Data Quality Monitoring system
Document Type
Conference
Source
2009 16th IEEE-NPSS Real Time Conference Real Time Conference, 2009. RT '09. 16th IEEE-NPSS. :354-360 May, 2009
Subject
Computing and Processing
Large Hadron Collider
Data acquisition
Software quality
Algorithm design and analysis
Data visualization
Computerized monitoring
Performance evaluation
Testing
Robustness
Publish-subscribe
Language
Abstract
ALICE is one of the four experiments installed at the CERN Large Hadron Collider (LHC), especially designed for the study of heavy-ion collisions. The online Data Quality Monitoring (DQM) is an important part of the data acquisition (DAQ) software. It involves the online gathering, the analysis by user-defined algorithms and the visualization of monitored data. This paper presents the final design, as well as the latest and coming features, of the ALICE's specific DQM software called AMORE (Automatic MonitoRing Environment). It describes the challenges we faced during its implementation, including the performances issues, and how we tested and handled them, in particular by using a scalable and robust publish-subscribe architecture.We also review the on-going and increasing adoption of this tool amongst the ALICE collaboration and the measures taken to develop, in synergy with their respective teams, efficient monitoring modules for the sub-detectors. The related packaging and release procedure needed by such a distributed framework is also described. We finally overview the wide range of usages people make of this framework, and we review our own experience, before and during the LHC start-up, when monitoring the data quality on both the sub-detectors and the DAQ side in a real-world and challenging environment.