Fast TPC Online Tracking on GPUs and Asynchronous Data Processing in the ALICE HLT to facilitate Online Calibration
David Rohr, Sergey Gorbunov, Mikolaj Krzewicki, Timo Breitner,, Matthias Kretz, Volker Lindenstruth (for the ALICE Collaboration)

TL;DR
This paper introduces a GPU-accelerated, vendor-independent TPC tracking algorithm and framework extensions for online calibration in ALICE's HLT, enabling real-time event reconstruction and calibration during LHC runs.
Contribution
The paper presents a fast, GPU-based TPC tracking algorithm using Cellular Automaton and Kalman filter, supporting multiple platforms and integrated with online calibration in ALICE HLT.
Findings
Successfully used in 2011 and 2012 ALICE runs
Achieved real-time processing speeds with GPU acceleration
Supported multiple hardware platforms with unified code
Abstract
ALICE (A Large Heavy Ion Experiment) is one of the four major experiments at the Large Hadron Collider (LHC) at CERN, which is today the most powerful particle accelerator worldwide. The High Level Trigger (HLT) is an online compute farm of about 200 nodes, which reconstructs events measured by the ALICE detector in real-time. The HLT uses a custom online data-transport framework to distribute data and workload among the compute nodes. ALICE employs several calibration-sensitive subdetectors, e.g. the TPC (Time Projection Chamber). For a precise reconstruction, the HLT has to perform the calibration online. Online-calibration can make certain Offline calibration steps obsolete and can thus speed up Offline analysis. Looking forward to ALICE Run III starting in 2020, online calibration becomes a necessity. The main detector used for track reconstruction is the TPC. Reconstructing the…
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