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Bibliographic Details
Main Authors: Gessinger, Paul, Gray, Heather M., Krasznahorkay, Attila, Leggett, Charles, Niermann, Joana, Salzburger, Andreas, Swatman, Stephen Nicholas, Yeo, Beomki
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2505.22822
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author Gessinger, Paul
Gray, Heather M.
Krasznahorkay, Attila
Leggett, Charles
Niermann, Joana
Salzburger, Andreas
Swatman, Stephen Nicholas
Yeo, Beomki
author_facet Gessinger, Paul
Gray, Heather M.
Krasznahorkay, Attila
Leggett, Charles
Niermann, Joana
Salzburger, Andreas
Swatman, Stephen Nicholas
Yeo, Beomki
contents We present the current development status and progress of traccc, a GPU track reconstruction library developed in the context of the A Common Tracking Software (ACTS) project. traccc implements tracking algorithms used in high energy physics (HEP) experiments, including the Kalman filter based track finding and fitting. We benchmark the software with data simulated by Geant4 to measure the physics and computing performance. We show that the physics performance for GPU and CPU are very close. We also show that the GPUs can achieve higher computational performance than the CPU for sufficiently large events.
format Preprint
id arxiv_https___arxiv_org_abs_2505_22822
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle traccc: GPU track reconstruction library for HEP experiments
Gessinger, Paul
Gray, Heather M.
Krasznahorkay, Attila
Leggett, Charles
Niermann, Joana
Salzburger, Andreas
Swatman, Stephen Nicholas
Yeo, Beomki
High Energy Physics - Experiment
We present the current development status and progress of traccc, a GPU track reconstruction library developed in the context of the A Common Tracking Software (ACTS) project. traccc implements tracking algorithms used in high energy physics (HEP) experiments, including the Kalman filter based track finding and fitting. We benchmark the software with data simulated by Geant4 to measure the physics and computing performance. We show that the physics performance for GPU and CPU are very close. We also show that the GPUs can achieve higher computational performance than the CPU for sufficiently large events.
title traccc: GPU track reconstruction library for HEP experiments
topic High Energy Physics - Experiment
url https://arxiv.org/abs/2505.22822