Abstract
Abstract
In the coming years, significant upgrades are planned for ATLAS and other High Energy
Physics experiments at CERN. Both the technologies and methodologies employed will undergo
changes for the scheduled runs at the end of the decade. The LHC accelerator itself will also
undergo multiple modifications, allowing it to achieve a peak of instantaneous luminosity up to
5–7.5 × 1034 cm-2 s-1. These enhancements will necessitate the
experiments to handle a greater number of events at the conclusion of the data acquisition
chain. For instance, ATLAS will be compelled to employ online tracking for its inner detector,
aiming to achieve a final event rate of 10 kHz from the 1 MHz originating from the Calorimeters
and the Muon Spectrometer trigger discrimination. Among the architectures explored to expedite
fast tracking, there is consideration of a “hardware accelerator” farm, an infrastructure made
of interconnected accelerators such as GPUs and FPGAs, designed to accelerate the tracking
processes. The project presented here proposes a tuned Hough Transform algorithm implementation on
high-end FPGA technology, specifically designed to adapt to various tracking situations. A
development platform comprising software and firmware tools has been created to study different
datasets. This platform utilizes software to simulate the firmware and to perform hardware
tests. AMD-Xilinx FPGAs were chosen to implement and asses the system, with specific boards such
as the VC709, the VCU1525 and the Alveo U250. Strategies such as low-level design for the firmware
architecture, leveraging the card's features like PCI Express data transfer, and the > 1 million
gates array available have been exploited. The system underwent testing using internally simulated
events generated within the ATLAS environment. Simulated 200 pile up events were used to evaluate
the algorithm effectiveness. The average processing time was estimated to be below 5 μs,
with the capability to concurrently process two events per algorithm instance. Internal efficiency
tests have shown conditions where track finding performance for single muon tracking exceeded
95%.