Development and Optimization of ACTS Tracking Software for High Luminosity Collider Experiments
by Joana Niermann
Date of Examination:2024-08-09
Date of issue:2025-07-21
Advisor:Prof. Dr. Stan Lai
Referee:Prof. Dr. Stan Lai
Referee:Dr. Andreas Salzburger
Persistent Address:
http://dx.doi.org/10.53846/goediss-11401
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Abstract
English
With the dawn of the high luminosity era at the LHC, an unprecedented amount of data will be collected and processed at the ATLAS experiment. This will result in a drastic increase of hit combinatorics during track reconstruction with the ATLAS ITk detector, which will replace the current Inner Detector. New algorithms and methods are investigated to efficiently process the incoming data. One possibility is the deployment of hardware accelerators that provide massive parallelism, like general-purpose computing on GPUs. In this thesis, the detray library will be presented, for which a GPU-friendly tracking geom- etry and navigation was developed. Within the ACTS (A Common Tracking Software) project, which is a detector-agnostic toolkit of tracking algorithms written in modern C++, a dedicated R&D effort was launched to investigate the adaptation of the ACTS tracking chain to GPUs. The final GPU tracking demonstrator will provide a realistic setup of all steps of track recon- struction, from clusterisation to ambiguity resolution, and thus allow an in-depth study of both physics and compute performance of GPU-based tracking within the ATLAS experiment. A crucial ingredient to be able to run track reconstruction is to ensure accurate and efficient modelling of the detector geometry and its material. This is done in ACTS by the tracking geometry, which is a purely surface based representation of the detector with a dedicated material mapping step. The current implementation has been found in previous studies to have several shortcomings concerning an adaptation to GPU computing, like its use of virtual function calls to describe different geometrical shapes for the detector surfaces, or its use of vector-of-vector data containers that rely on dynamic memory allocations. With the detray library, a tracking geometry will be made available that solves these problems by using a combination of static polymorphism and an index-based data management on global, flat data containers in memory. Using the vecmem library for data management, the detray detector can be read in from data files exported from existing tracking geometries in ACTS on the CPU and subsequently be copied to the GPU memory system to run device-side track reconstruction. The geometry description can be provided in full detail compared to ACTS, including the access to material maps. The detray tracking geometry and the track parameter navigation have been validated in a constant magnetic field against a numeric approach using the Newton-Raphson algorithm, enhanced with bisection steps, on several detector geometries, among them the current ITk tracking geometry.
Keywords: particle physics; ATLAS experiment; HL-LHC; CERN; detector geometry; GPU; track reconstruction
