Karlsruhe 2024 – scientific programme

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T: Fachverband Teilchenphysik

T 65: Trigger+DAQ 2

T 65.4: Talk

Wednesday, March 6, 2024, 16:45–17:00, Geb. 30.23: 3/1

Implementation of a two-level AI-enhanced trigger on a single chip for live reconstruction — •Patrick Schwäbig for the Lohengrin collaboration — Physikalisches Institut, Universität Bonn, Deutschland

For years, data rates generated by modern detectors and the corresponding readout electronics exceeded by far the limits of data storage space and bandwidth available in many experiments. The solution of using fast triggers to discard uninteresting and irrelevant data is a solution used to this day. Using FPGAs, ASICs or directly the readout chip, a fixed set of rules based on low level parameters is applied as a pre-selection. Only a few years ago, live track reconstruction for triggering was rarely possible. With the emergence of highly parallelized processors for AI inference, attempts to sufficiently accelerate tracking algorithms become viable. The Xilinx Versal Adaptive Compute Acceleration Platform (ACAP) is one such technology and combines FPGA and CPU resources with dedicated AI cores. Our approach is to implement a two-level trigger on a single chip by utilizing the tightly integrated combination of FPGA and AI cores to profit from their individual strengths. In this talk our concept for a two-level trigger setup, implemented on a Xilinx VC1902, including AI algorithms and Timepix3 readout, will be shown. They will be used in an envisioned mid-size ultra-high rate fixed-target dark matter experiment (Lohengrin) at the ELSA accelerator at the University of Bonn.

Keywords: AI; FPGA; trigger; reconstruction; Timepix3