Prototype for GPU Port of the Clustering Algorithm for the Inner Tracking System of ALICE

The clustering algorithm is a key step in the preprocessing of ALICE's Inner Tracking System (ITS) detector data. It not only compresses the data for enhanced storage efficiency but also plays a vital role in the reconstruction of a particle's trajectory. To date, this computational task has been executed on the CPU. In this report, we introduce a prototype that transitions the clustering to a GPU architecture. Preliminary benchmarks yield promising results and demonstrate the feasibility of GPU-based clustering for the ITS, setting the stage for continued research and development in this direction.