In view of the LHC Run3 starting in 2021, the ALICE experiment is preparing a major upgrade including the construction of an entirely new inner silicon tracker (the Inner Tracking System) and a complete renewal of its Online and Offline systems (O²).
In this context, one of the requirements for a prompt calibration of external detectors and a fast offline data processing is to run online the reconstruction of tracks in the Upgraded Inner Tracking System.
A new algorithm based on Cellular Automata has been developed to tackle this issue. In this algorithm, the tracking is split in multiple phases to profit from data locality and using the same approach it is possible to determine the primary vertex position.
To cope with the specification of the O² and with the foreseen Pb-Pb interaction rate of 50 kHz, this algorithm has been developed exploiting the most common parallelisation technologies available, such as SIMD and multi-threading on x86 CPUs and offloading to GPU using CUDA and OpenCL.
In this contribution we will show the speedup obtained using different technologies to implement the vertexing and tracking algorithms. The obtained computing and physics performance are compliant with the requirements of ALICE for Run 3.