FPGA Acceleration of Matrix-Element Calculations for Monte Carlo Event Generation

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Arance, H. Gutiérrez, Carrió, F., Fiorini, L., Folgueras, S., Álvarez, F. Hervàs, López, P. Leguina, Oyanguren, A., Valero, A., Villalba, C. Vico
Natura: Preprint
Pubblicazione: 2026
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866917525093089280
author Arance, H. Gutiérrez
Carrió, F.
Fiorini, L.
Folgueras, S.
Álvarez, F. Hervàs
López, P. Leguina
Oyanguren, A.
Valero, A.
Villalba, C. Vico
author_facet Arance, H. Gutiérrez
Carrió, F.
Fiorini, L.
Folgueras, S.
Álvarez, F. Hervàs
López, P. Leguina
Oyanguren, A.
Valero, A.
Villalba, C. Vico
contents We present an FPGA-based study of matrix-element acceleration for Monte Carlo event generation, using MadGraph5_aMC@NLO as a benchmark framework. Two complementary scenarios are considered. First, we implement the full matrix-element workflow on an AMD Alveo U250 accelerator for the benchmark process $e^+e^- \to μ^+μ^-$, enabling an end-to-end evaluation of FPGA acceleration for a simple process. Second, for the more complex $gg \to t\bar{t}+X$ processes with increasing jet multiplicity, we investigate FPGA acceleration of the color-algebra kernels as a structured and scalable entry point for selective acceleration. In this second case, the reported speedups correspond to the isolated color-reduction kernel operating on precomputed amplitudes, rather than to the full matrix-element evaluation or the complete event-generation workflow. The proposed implementations are developed using High-Level Synthesis and are evaluated in terms of numerical accuracy, performance, energy efficiency, resource utilization, and scalability. Compared with CPU and GPU implementations available within the MG5aMC framework, the FPGA solutions achieve substantial speedups and significantly improved energy efficiency. For the considered benchmarks, the numerical results remain in close agreement with the corresponding CPU reference calculations, while the resource analysis highlights the importance of numerical representation in determining scalability on FPGA devices. These results support the use of FPGAs as a competitive architecture for selected Monte Carlo event-generation workloads in high-energy physics.
format Preprint
id arxiv_https___arxiv_org_abs_2605_23785
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle FPGA Acceleration of Matrix-Element Calculations for Monte Carlo Event Generation
Arance, H. Gutiérrez
Carrió, F.
Fiorini, L.
Folgueras, S.
Álvarez, F. Hervàs
López, P. Leguina
Oyanguren, A.
Valero, A.
Villalba, C. Vico
High Energy Physics - Experiment
We present an FPGA-based study of matrix-element acceleration for Monte Carlo event generation, using MadGraph5_aMC@NLO as a benchmark framework. Two complementary scenarios are considered. First, we implement the full matrix-element workflow on an AMD Alveo U250 accelerator for the benchmark process $e^+e^- \to μ^+μ^-$, enabling an end-to-end evaluation of FPGA acceleration for a simple process. Second, for the more complex $gg \to t\bar{t}+X$ processes with increasing jet multiplicity, we investigate FPGA acceleration of the color-algebra kernels as a structured and scalable entry point for selective acceleration. In this second case, the reported speedups correspond to the isolated color-reduction kernel operating on precomputed amplitudes, rather than to the full matrix-element evaluation or the complete event-generation workflow. The proposed implementations are developed using High-Level Synthesis and are evaluated in terms of numerical accuracy, performance, energy efficiency, resource utilization, and scalability. Compared with CPU and GPU implementations available within the MG5aMC framework, the FPGA solutions achieve substantial speedups and significantly improved energy efficiency. For the considered benchmarks, the numerical results remain in close agreement with the corresponding CPU reference calculations, while the resource analysis highlights the importance of numerical representation in determining scalability on FPGA devices. These results support the use of FPGAs as a competitive architecture for selected Monte Carlo event-generation workloads in high-energy physics.
title FPGA Acceleration of Matrix-Element Calculations for Monte Carlo Event Generation
topic High Energy Physics - Experiment
url https://arxiv.org/abs/2605.23785