Speaker
Description
Monte Carlo detector simulation plays a central role in high-energy physics, providing the foundation for precision measurements and searches for new phenomena. At the same time, it is extremely computationally demanding. For Run 3, the ATLAS experiment implemented a series of targeted optimizations and tunings to reduce CPU usage while preserving physics accuracy. Collectively, these improvements achieved a factor-of-two speedup compared to the Run-2 baseline. For Run 4, ATLAS is refactoring the simulation code to streamline the interface with Geant4 and make it more maintainable by removing unnecessary layers. In parallel, the collaboration is exploring a transformative direction for Full Simulation by offloading electromagnetic physics to GPUs and moving toward hybrid CPU–GPU execution models. This effort builds on the progress of the AdePT and Celeritas projects, which provide GPU-accelerated EM physics and navigation capabilities. Importantly, ATLAS is already capable of submitting hybrid GPU simulation jobs on the Grid, marking a key milestone toward operational deployment and production quality workflow. This contribution will present the current status of these developments, including CPU/GPU performance, physics accuracy, and practical deployment, and outline the short- and long-term enhancements that will guide the evolution of ATLAS Full Simulation toward Run 4 and beyond.
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