@article{RDM,
      recid = {103658},
      author = {Sudvarg, Marion and Zhao, Chenfeng and Htet, Ye and Konst,  Meagan and Lang, Thomas and Song, Nick and Chamberlain,  Roger and Buhler, Jeremy and Buckley, James},
      title = {FPGA Kernels for Front-End Pre-Processing on ADAPT V1},
      publisher = {Washington University in St. Louis},
      address = {2024-04-09},
      number = {RDM},
      abstract = {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.},
      url = {http://data.library.wustl.edu/record/103658},
      doi = {https://doi.org/10.7936/6rxs-103658},
}