1. The ALICE data quality monitoring Barthélémy von Haller CERN PH/AID For the ALICE Collaboration

2. The ALICE experiment LHC : Large Hadron Collider ALICE : A Large Ion Collider Experiment – 18 detectors – Bandwidth to mass storage : 1.25 GB/s – Event size : 86.5 MB – Trigger rate : 10 KHz 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID1/15

3. Data Quality Monitoring 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID2/24 Online feedback on the quality of data Avoid taking and recording low-quality data Identify and solve problem(s) early Data Quality Monitoring (DQM) involves -Online gathering of data -Analysis by user-defined algorithm -Storage of monitoring data -Visualization

4. Data-Acquisition architecture 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID3/24 DA DQM Sub-event

5. The AMORE framework AMORE : Automatic MOnitoring Environment A DQM framework for the ALICE experiment 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID4/24

6. Publisher – Subscriber paradigm Database used for the data pool Notification with DIM (Distributed Information Management System) 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID5/24 Design & Architecture

7. Published objects are encapsulated into « MonitorObject » structure Plugin architecture using ROOT reflection – Modules are dynamic libraries loaded at runtime 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID6/24 Design & Architecture

8. 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID7/24

9. The Pool 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID8/24 Current implementation based on a database MySQL : reliable, performant, open-source

10. Archiving Short-term history : First-In First-Out (FIFO) Long-term archives : At end of run, regular intervals, and users’ request 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID9/24 Agent Latest value GUI Publish Access X recent values FIFO Temporary and permanent archive Archive triggers : Start and end of run, regular time interval, at shifter’s request

11. Subscriber & User Interface Generic GUI – Display any object of any running agent – Possibility of handling automatically the layout – Layout can be pretty complex and saved for future reuse – Fit the basic needs of the users to check what is published by the agents For more complex needs, users can develop their own GUI 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID10/24

12. The generic GUI 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID11/24 Agent Agents Monitor ObjectsSub-directories

13. The generic GUI 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID12/24 Save Load

14. Custom gui 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID13

15. Packaging & validation Subversion repositories GNU Autotools Distributed as RPM (1+12 packages) Strict release procedure – Build and validate the module on a test machine in a clean and controlled environment Nightly build – Identify broken code (wrong results, unable to compile) 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID14/24

16. Performance & benchmark 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID15/24 Online environment and heavy calculation  ensure performance and scalability To identify and handle performance issues we need : – Metrics – Statistics – Reproducible tests

17. Performance & benchmark Same procedure and environment as for the validation of modules – Estimation of needs for each detector – Identification of variations over time – Comparisons of machines, compilers and architectures 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID16/24

18. Performances & benchmark 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID17/24 Current DQM nodes : Intel(R) Xeon(R) CPU 5130 @2.00GHz Latest generation of intel processor : Intel(R) Core(TM) i7 CPU 965 @3.20GHz

19. Database benchmark All data transit through the pool  critical part of the system Test of extreme and standard use cases Several improvements made : – Concatenate queries and insertions – MySQL engine : MyISAM vs InnoDB 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID18/24

20. InnoDB vs MyISAM 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID19/24

21. Status In production since last summer, used during commissioning and first beam 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID20/24

22. 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID21/24

23. Status In production since last summer, used during commissioning and first beam New features are regularly added, usually at users’ request 18 modules under development 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID22/24

24. Plans Access to monitor objects through the web via the ALICE electronic LogBook Fully automatize the process : comparisons to reference data, identification of problems, notification, actions taken Add features to take full advantage of multi-cores architecture 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID23/24

25. Conclusion AMORE has been in production for almost a year Increasing number of detector agents Proved to be very useful during commissioning and first beam period Capable of handling large number of agents, clients and objects  Ready for the LHC restart ! 14/05/2009 – IEEE RT2009Barthélémy von Haller - CERN PH/AID24/24