FPGA Kernels for Front-End Pre-Processing on ADAPT V1

Field-programmable gate arrays (FPGAs) are widely deployed on high-energy astrophysics telescopes to preprocess and reduce sensor data read out by front-end electronics. Across instruments, these computational pipelines have similar semantics, sharing common stages such as pedestal subtraction, signal integration, zero-suppression, island detection, and centroiding. However, diverse telescope designs require unique implementations of these algorithms, and the logic is often rewritten from scratch for a new instrument.

As an alternative, High-Level Synthesis (HLS) tools enable these algorithms to be implemented in a high-level language, which eases modifications and enables fast prototyping and deployment. Nonetheless, writing performant HLS code requires augmentation of the code with compiler-specific pragmas. In this work, we illustrate these challenges in the context of the Advanced Particle-astrophysics Telescope (APT), a proposed space-based observatory for gamma-ray sources, and its Antarctic Demonstrator (ADAPT). We implement its front-end algorithms using HLS, demonstrate the use of pragmas to enable optimizations, then explore speed and area tradeoffs, which are especially important given the limited power budget afforded by a satellite instrument. We demonstrate that with HLS, ADAPT will be able to process scintillating tile data from 200,000 gamma-ray events per second.