Large-scale real-time signal processing in physics experiments: The ALICE TPC FPGA pipeline

TL;DR

This paper presents a large-scale FPGA-based real-time data processing pipeline for the ALICE TPC detector, capable of handling 3 TB/s raw data at high interaction rates in LHC Run 3.

Contribution

The paper introduces a novel FPGA processing pipeline that performs complete front-end data treatment in-stream, enabling continuous high-rate data processing for large physics experiments.

Findings

Operates at 900 GB/s after processing

Robust common-mode correction on streaming data

Prevents signal loss under high-occupancy conditions

Abstract

For LHC Run 3, the ALICE Time Projection Chamber was upgraded to operate in continuous readout mode. Interaction rates of up to 50 kHz in Pb-Pb collisions require real-time processing of more than 3 TB/s of raw detector data. This requirement is met by a custom FPGA-based processing pipeline that performs the complete front-end data treatment fully in-stream, including common-mode correction, pedestal subtraction, ion-tail filtering, zero suppression, and dense data packing. A central element of the design is a highly parallel common-mode correction algorithm operating directly on the streaming data. It robustly identifies signal-free readout channels on a time-bin basis and applies pad-dependent scaling to compensate for local variations in capacitive coupling in the GEM readout. In combination with pedestal subtraction and ion-tail filtering, this enables accurate baseline restoration under extreme high-occupancy conditions, preventing signal loss while efficiently suppressing noise prior to zero suppression. The pipeline operates continuously at the full detector bandwidth and reduces the raw input rate to about 900 GB/s for Pb-Pb collisions at the target interaction rate. Overall, it represents a large-scale FPGA-based real-time signal-processing implementation for high-energy physics detector readout.