1. The High-Level Trigger of the ALICE Experiment Heinz Tilsner Kirchhoff-Institut für Physik Universität Heidelberg International Europhysics Conference on High-Energy Physics 2003 Aachen Further information: http://www.ti.uni-hd.de/HLT

2. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Content Physics Applications of the High-Level Trigger Online Pattern Recognition and Event Reconstruction Computing Infrastructure

3. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Physics Applications

4. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Physics Applications I Open-charm trigger: Momentum filter (low p t cut) Examination of the event topology Jet-Trigger: Online jet trigger from TPC inspection of central Pb-Pb collisions at 200 Hz Cone jet-finder algorithm for online Pile-up removal: Reconstruction of all tracks in the TPC Reconstruction of the event vertex Pile-up reduction by using a cut on impact parameter of tracks Data reduction about a factor 5

5. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Physics Applications II e + e - Trigger: Di-Muon Trigger: Using information of the di-muon spectrometers to determine the transversal momentum  p t cut HLT reduces event rate about a factor of 10 by: combining TRD tracklets with TPC and ITS tracking adding PID rejection power from TPC dE/dx Reconstructing J/Ψ and Y by their leptonic decays into e+e- pairs

6. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Online Event Reconstruction

7. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics HLT Functionality resulting trigger decision is based on fully analyzed and reconstructed events local pattern recognition (detector specific): cluster finder tracklets global pattern recognition: e.g. global tracking in TPC Time budget: Online analysis needs 12s for one event with dN/dY=4000 or 2400 CPUs at event rate of 200 Hz parallel processing on PC cluster

8. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Fast Pattern Recognition FPGA co-processor: releases CPU resources of host CPU online Hough Transform is essential for tracking in dense environment low multiplicity events sequential feature extraction on space points cluster finder track follower high multiplicity events iterative feature extraction on raw data: tracklet finder (Hough transform) parallel cluster evaluation

9. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Low Occupancy 1.Cluster finder (FPGA): cluster finding centroid calculation deconvolution 2.Tracking (host CPU) Hardware implementation: Decoder: decoding incoming ADC sequences (ALTRO list) calculating charge, sequence charge, and time of a sequence Merger: merges sequences of adjacent pads to clusters Verification of functionality: C++ code = VHDL code

10. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics High Occupancy: Hough Transform Hough Transform: Transformation of coordinate space (R, Φ) to parameter space (Φ 0, κ) Φ 0 :emission angle Κ:curvature

11. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Hough Transform in FPGA Co-Processor Behavioral (VHDL) model of Hough Transform simulated and compared with software

12. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Computing Infrastructure

13. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics FPGA Co-Processor as Part of the Front-End Processor Front-End Prozessor: First layer of the HLT-clusters Input for event data into the cluster (via optical link) “normal“ PC, equipped with Read-Out Receiver Card (RORC) Ordinary PC cluster + PCI RORC = HLT FPGA: implementing the PCIbus protocol co-processor for online analysis

14. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Data Volume + Event Rates

15. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics HLT Cluster Setup achieved event rate = 430 events/s Example: TPC sector

16. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Data Transport within the HLT-Cluster Subscriber Publisher new event new event (Sub)EventScatterer Load balancing Fan - out (Sub) EventGatherer Publisher Subscriber new event new event Publisher Merging Code Subs Event m Block 0 Event m Block 1 Event m Block 0, 1 … (Sub)Event MergerBridging between Nodes

17. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Fault Tolerance (1)Network connection disconnected (2)Faulty PC node is removed from data path (3)Spare node inserted into data path  no single event is lost! Software framework with embedded fault tolerance Automatic re-configuration of the data path Test setup with 7 computers: A B C D E

18. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Prototypes 32 dual Pentium III PCs running Linux Network connection: FastEthernet GigaBit Ethernet SCI

19. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics RORC: Read Out Receiver Card

20. Heinz Tilsner - University of Heidelberg Kirchhoff Institute of Physics Summary èHLT enables event selection based on physical signatures èOnline event analysis assisted by FPGA co-processor èHLT allows for a significant reduction of the data volume èFunctional concept of the HLT exists èFault-tolerant software successfully tested Further information: http://www.ti.uni-hd.de/HLT