About
High-energy physics trigger systems are traditionally implemented in a two-stage architecture. In the first stage, custom hardware boards—typically FPGA-based—perform fast, coarse reconstruction to identify interactions of interest and forward the selected events to the next stage. There, reconstruction is carried out in greater detail using commercial computing technologies such as CPUs and GPUs. Because of limited resources, high bandwidths, and strict latency constraints, the hardware trigger cannot apply selections as sophisticated as those in the second stage. Technologies such as NVIDIA Holoscan aim to address this limitation by enabling high-bandwidth data streams to be transferred directly into GPU memory, bypassing delays introduced by a CPU host. This talk presents the R&D activities within the ATLAS experiment evaluating the Holoscan technology, initially in the context of data scouting setups, and explores the feasibility of GPU-based trigger and data-acquisition systems for future experiments.
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The talk
Credits and licence
- Institution
- CERN
- Speaker
- Ioannis Xiotidis
- Year
- 2026
- Language
- English
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Teens profiles and older, judged from what the source says about it. How courses are placed