P. Vande Vyvre – CERN/PHCERN – January 2011

ARCHITECTResearch Theme 2:

Data Acquisition

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Research Theme 2: DAQ

ARCHITECT – Jan 2011 P. Vande Vyvre – CERN/PH

•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

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RT 2 – 5 ESRs

ARCHITECT – Jan 2011 P. Vande Vyvre – CERN/PH

ESR Supervisor Topic Specific Training

1 F. Carena Experiment control automation

- Distributed systems- Expert systems technologies- Artificial Intelligence

2 S. Chapeland Refactoring of the DAQ sw DATE package

- Secure coding in C/C++- Databases and DB Design- Quality management

3 F. Costa Detector readout - Detector readout techniques- Fw and Sw implementations- Future interconnect

4 R. Divia Online systems dynamic monitoring

- Monitoring platforms (home-made, commercial, open-source systems)- Monitoring and error detection standards

5 V. Chibante Business Intelligence applied to online systems

- High-performance DB- Data Warehouse and Business Intelligence concepts and practices.

ARCHITECT – Jan 2011 4

RT2 – Partners

P. Vande Vyvre – CERN/PH

•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