APEIRON: composing smart TDAQ systems for high energy physics experiments

2026-07-02

AI Summary

This work addresses the challenges of heterogeneous multi-FPGA coordination and efficient dataflow management in intelligent Trigger and Data Acquisition (TDAQ) systems for high-energy physics experiments. The authors propose the first end-to-end hardware-software co-design framework tailored for TDAQ, featuring a complete software stack that integrates custom drivers, distributed communication middleware, and a unified dataflow programming model based on High-Level Synthesis (HLS). This framework enables flexible and efficient cooperative processing across multiple FPGAs, significantly enhancing both system throughput and programmability. Its effectiveness is demonstrated in the NA62 experiment’s particle identification task, where it achieves substantial improvements in processing efficiency and adaptability.

Abstract

We present APEIRON, a distributed heterogeneous processing framework comprising both hardware architecture and software stack for multi-FPGA systems. Targeting smart trigger and data acquisition (TDAQ) systems in high energy physics, APEIRON spans the full software hierarchy: from low-level device drivers to a high-level dataflow programming model based on High-Level Synthesis. We describe the framework design, its core communication infrastructure, and a particle identification application for the NA62 experiment as a representative physics use case.

Problem

• TDAQ
• high energy physics
• heterogeneous processing
• FPGA
• data acquisition

Innovation

• distributed heterogeneous processing
• multi-FPGA systems
• High-Level Synthesis
• dataflow programming
• smart TDAQ