Ultra Fast Transformers on FPGAs for Particle Physics Experiments

Feb 1, 2024
6 pages
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Abstract: (arXiv)
This work introduces a highly efficient implementation of the transformer architecture on a Field-Programmable Gate Array (FPGA) by using the \texttt{hls4ml} tool. Given the demonstrated effectiveness of transformer models in addressing a wide range of problems, their application in experimental triggers within particle physics becomes a subject of significant interest. In this work, we have implemented critical components of a transformer model, such as multi-head attention and softmax layers. To evaluate the effectiveness of our implementation, we have focused on a particle physics jet flavor tagging problem, employing a public dataset. We recorded latency under 2 μ\mus on the Xilinx UltraScale+ FPGA, which is compatible with hardware trigger requirements at the CERN Large Hadron Collider experiments.
Note:
  • 6 pages, 2 figures
  • trigger: hardware
  • jet: flavor
  • FPGA
  • FGPA
  • CERN Lab
  • CERN LHC Coll