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Speeding up Madgraph5 aMC@NLO through CPU vectorization and GPU offloading: towards a first alpha release

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arxiv 2303.18244 v2 pith:4DAXPVK5 submitted 2023-03-31 physics.comp-ph hep-exhep-ph

classification physics.comp-phhep-exhep-ph
keywords eventalphacalculationdiscussedfirstframeworkgeneratormadgraph5
verification ladder T0 review T1 audit T2 compute T3 formal
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The matrix element (ME) calculation in any Monte Carlo physics event generator is an ideal fit for implementing data parallelism with lockstep processing on GPUs and vector CPUs. For complex physics processes where the ME calculation is the computational bottleneck of event generation workflows, this can lead to large overall speedups by efficiently exploiting these hardware architectures, which are now largely underutilized in HEP. In this paper, we present the status of our work on the reengineering of the Madgraph5_aMC@NLO event generator at the time of the ACAT2022 conference. The progress achieved since our previous publication in the ICHEP2022 proceedings is discussed, for our implementations of the ME calculations in vectorized C++, in CUDA and in the SYCL framework, as well as in their integration into the existing MadEvent framework. The outlook towards a first alpha release of the software supporting QCD LO processes usable by the LHC experiments is also discussed.

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  1. Data-parallel leading-order event generation in MadGraph5_aMC@NLO

    hep-ph 2025-07 conditional novelty 6.0 of 10

    CUDACPP gives MadGraph data-parallel helicity amplitudes, delivering linear SIMD CPU speed-ups and up to order-of-magnitude GPU speed-ups for high-multiplicity QCD event generation.

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