GPU-Based Muon Segment Fitting for HL-LHC Reconstruction.

About

**Project Description**: Muon reconstruction is a central component of the ATLAS physics program and a key contributor to the overall computational cost of event reconstruction. The muon spectrometer provides precision tracking in the outermost region of the detector, and muon segment fitting is a core step in the outside-in reconstruction chain. Our group has implemented a highly optimized CUDA-based $\chi^2$ minimization fitter. However, approximately half of the current runtime is spent on host–device memory transfers, limiting suitability for latency-critical applications such as triggering. The proposed project aims to build on this foundation by developing a deeper GPU-resident reconstruction pipeline in which additional steps of the muon reconstruction chain are executed directly on the GPU. By moving hit preparation, region construction, and segment seeding onto the device, the project seeks to minimize data movement and amortize memory transfer costs. The reconstruction will be integrated more deeply with the A Common Tracking Software (ACTS) framework using a realistic ATLAS detector geometry and more complex physics processes, including jets and pileup. A full benchmarking campaign will be carried out to compare the GPU-based pipeline with the existing CPU implementation and to assess the feasibility of GPU acceleration for later-stage triggering and quasi-online reconstruction.

**Supervisor**: Johannes Junggeburth, CERN

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