DARMA - INFORMATION SYSTEM FOR ACCESSING LHC DATA WITHIN THE ALICE EXPERIMENT AT CERN

The paper deals with the implementation of systems for remote data access in cooperation with the international laboratory CERN in Geneva. The first part discusses extensions of the DARMA information system for archive management. The main goal of this paper is to design and enhance the system with new functionalities and solve known shortcomings, and thus qualitatively increase the potential of the DARMA system in the context of the ALICE DCS (Detector Control System). The final part of the paper deals with the analysis of historical data and the design of a system for the anomaly and failure detection in the infrastructure of high voltage channels within the TRD detector (Transition Radiation Detector).

Space-point calibration of the ALICE TPC with track residuals

In the LHC Run 3, starting in 2021, the upgraded Time Projection Chamber (TPC) of the ALICE experiment will record minimum bias Pb–Pb collisions in a continuous readout mode at an interaction rate up to 50 kHz. This corresponds to typically 4-5 overlapping collisions during the electron drift time in the detector. Despite careful tuning of the new quadruple GEM-based readout chambers, which fulfill the design requirement of an ion backflow below 1%, these conditions will lead to space-charge distortions of several centimeters that fluctuate in time. They will be corrected via a calibration procedure that uses the information of the Inner Tracking System (ITS), which is located inside, and the Transition Radiation Detector (TRD) and Time-Of-Flight system (TOF), located around the TPC, respectively. By using such a procedure the intrinsic track resolution of the TPC of a few hundred micrometers can be restored. The required online tracking algorithm for the TRD, which is based on a Kalman filter, is presented. The procedure matches extrapolated ITS-TPC tracks to TRD space-points utilizing GPUs. Subsequently these global tracks are refitted neglecting the TPC information. The residuals of the TPC clusters to the interpolation of the refitted tracks are used to create a map of spacecharge distortions. Regular updates of the map compensate for changes in the TPC conditions. The map is applied in the final reconstruction of the data. First performance results of the tracking algorithm will be shown.

GPU-based reconstruction and data compression at ALICE during LHC Run 3

In LHC Run 3, ALICE will increase the data taking rate significantly to 50 kHz continuous read out of minimum bias Pb-Pb collisions. The reconstruction strategy of the online offline computing upgrade foresees a first synchronous online reconstruction stage during data taking enabling detector calibration, and a posterior calibrated asynchronous reconstruction stage. The significant increase in the data rate poses challenges for online and offline reconstruction as well as for data compression. Compared to Run 2, the online farm must process 50 times more events per second and achieve a higher data compression factor. ALICE will rely on GPUs to perform real time processing and data compression of the Time Projection Chamber (TPC) detector in real time, the biggest contributor to the data rate. With GPUs available in the online farm, we are evaluating their usage also for the full tracking chain during the asynchronous reconstruction for the silicon Inner Tracking System (ITS) and Transition Radiation Detector (TRD). The software is written in a generic way, such that it can also run on processors on the WLCG with the same reconstruction output. We give an overview of the status and the current performance of the reconstruction and the data compression implementations on the GPU for the TPC and for the global reconstruction.