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In LHC Run 3, ALICE will increase the data taking rate significantly to 50kHz continuous read-out of minimum bias Pb-Pb collisions. The reconstructionstrategy of the online-offline computing upgrade foresees a first synchronousonline reconstruction stage during data taking enabling detector calibrationand data compression, and a posterior calibrated asynchronous reconstructionstage. Many new challenges arise, among them continuous TPC read-out, moreoverlapping collisions, no a priori knowledge of the primary vertex and oflocation-dependent calibration in the synchronous phase, identification oflow-momentum looping tracks, and sophisticated raw data compression. Thetracking algorithm for the Time Projection Chamber (TPC) will be based on aCellular Automaton and the Kalman filter. The reconstruction shall run online,processing 50 times more collisions per second than today, while yieldingresults comparable to current offline reconstruction. Our TPC track findingleverages the potential of hardware accelerators via the OpenCL and CUDA APIsin a shared source code for CPUs and GPUs for both reconstruction stages. Wegive an overview of the status of Run 3 tracking including performance onprocessors and GPUs and achieved compression ratios.

GPU-based Online Track Reconstruction for the ALICE TPC in Run 3 with Continuous Read-Out