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2023

Symbolic Regression on FPGAs for Fast Machine Learning Inference

Tsoi, Ho Fung, Pol, Adrian Alan, Loncar, Vladimir et al.

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The high-energy physics community is investigating the potential of deploying machine-learning-based solutions on Field-Programmable Gate Arrays (FPGAs) to enhance physics sensitivity while still meeting data processing time constraints.

In this contribution, we introduce a novel end-to-end procedure that utilizes a machine learning technique called symbolic regression (SR).
It searches the equation space to discover algebraic relations approximating a dataset.
We use PySR (a software to uncover these expressions based on an evolutionary algorithm) and extend the functionality of hls4ml (a package for machine learning inference in FPGAs) to support PySR-generated expressions for resource-constrained production environments.

Symbolic Regression on FPGAs for Fast Machine Learning Inference · Around

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E.A. Moreno, O. Cerri, J.M. Duarte, H.B. Newman, T.Q. Nguyen, A. Periwal, M. Pierini, A. Serikova, M. Spiropulu, J.R. Vlimant, Eur. Phys. J. C 80
1908
Earlier work this paper cites.
V. Loncar et al., Mach. Learn. Sci. Tech. 2
2003
Earlier work this paper cites.
CMS Collaboration, JINST 15
2006
Earlier work this paper cites.
C.N. Coelho, A. Kuusela, S. Li, H. Zhuang, T. Aarrestad, V. Loncar, J. Ngadiuba, M. Pierini, A.A. Pol, S. Summers, Nature Mach. Intell. 3
2006
Earlier work this paper cites.
ATLAS Collaboration, JINST 15
2007
Earlier work this paper cites.

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Then

M. Cranmer, PySR: Fast & parallelized symbolic regression in python/julia (2020), https://github.com/MilesCranmer/PySR
2020
Later among the works it cites.
M. Pierini, J.M. Duarte, N. Tran, M. Freytsis, HLS4ML LHC Jet dataset (150 particles) (2020), https://doi.org/10.5281/zenodo.3602260
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Xilinx, Vivado Design Suite User Guide: High-Level Synthesis , https://www.xilinx.com/support/documentation/sw_manuals/xilinx2020_1/ug902-vivado-high-level-synthesis.pdf (2020)
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FastML Team, fastmachinelearning/hls4ml (2021), https://github.com/fastmachinelearning/hls4ml
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B. Hawks, J. Duarte, N.J. Fraser, A. Pappalardo, N. Tran, Y. Umuroglu, Front. Artif. Intell. 4
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