Fast Machine Learning for Science Workshop 2023

fwXmachina part 1: Classification with boosted decision trees on FPGA for L1 trigger

25 Sept 2023, 16:15

15m

Blackett Laboratory, Lecture Theatre 1 (Imperial College London)

Standard Talk Contributed Talks Contributed Talks

Speaker

Tae Min Hong (University of Pittsburgh (US))

Description

We introduce the fwXmachina framework for evaluating boosted decision trees on FPGA for implementation in real-time systems. The software and electrical engineering designs are introduced, with both physics and firmware performance detailed. The test bench setup is described. We present an example problem in which fwXmachina may be used to improve the identification of vector boson fusion Higgs production at the L1 triggers in LHC experiments. Comparisons are made to previous results, including comparisons to neural network approaches. The talk describes work in JINST 16 P08016 (2021), [2104.03408], as well as more recent results.

Presentation materials

TMHong20230925_FML_fwX1.pdf