P. Vande Vyvre – CERN/PH CERN – January 2011. Research Theme 2: DAQ ARCHITECT – Jan 2011 P. Vande Vyvre – CERN/PH2 Current DAQ status: Large computing.

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P. Vande Vyvre – CERN/PH CERN – January 2011

Research Theme 2: DAQ ARCHITECT – Jan 2011 P. Vande Vyvre – CERN/PH2 Current DAQ status: Large computing system made of 480 DDL links (2 Gb/s) to detectors and 360 DDL links (2 Gb/s) to HLT Computing and storage: 350 PCs and servers, 75 storage arrays Networks: 1-10 Gb Eth, FC 4G SAN Large Sw package (300 kLOC) Dataflow Control and Operation Monitoring of the Data Quality and of the System behavior Main topics of the ALICE upgrade for the DAQ: Automate the operation Take advantage of the recent computing paradigms (multi-core, GPU) Major refactoring of the DAQ sw after 15 years of development Increase performance of the detector readout Improve the system monitoring and reporting

RT 2 – 5 ESRs ARCHITECT – Jan 2011 P. Vande Vyvre – CERN/PH3 ESRSupervisorTopicSpecific Training 1F. CarenaExperiment control automation - Distributed systems - Expert systems technologies - Artificial Intelligence 2S. ChapelandRefactoring of the DAQ sw DATE package - Secure coding in C/C++ - Databases and DB Design - Quality management 3F. CostaDetector readout- Detector readout techniques - Fw and Sw implementations - Future interconnect 4R. DiviaOnline systems dynamic monitoring - Monitoring platforms (home-made, commercial, open-source systems) - Monitoring and error detection standards 5V. ChibanteBusiness Intelligence applied to online systems - High-performance DB - Data Warehouse and Business Intelligence concepts and practices.

RT2 – Partners ARCHITECT – Jan 2011P. Vande Vyvre – CERN/PH4 New computing paradigms (Intel, HP, nVidia) Increase the inherent parallelism of the code to make the best possible use of multi-core machines Evaluate the impact of other computing techniques such as GPUs. Port the code to these new platforms for the appropriate applications. Trainings and “clinic” sessions for all RT2 ESRs with different levels corresponding to the needs Adequate hw and sw will be acquired to allow intensive R&D at CERN on those topics after the training High-performance computing (Frankfurt, Houston) Application of the above to achieve the goals at the system-level Visualization techniques, green computing Readout techniques (CERNTech, KFKI, QLogic) Smooth mix of hw/fw/sw to increase readout performance and flexibility Cluster-File system (Quantum) Fundamental part of the dataflow. Evaluate the impact of its extension to other fields