arXiv subjects

Zenny Wettersten

Publications and source records attributed to Zenny Wettersten.

10 recordsLinked to original sources

arXiv2026

A multi-event interface for next-to-leading order calculations in MadGraph5_aMC@NLO

We detail the implementation of a multi-event interface for next-to-leading order (NLO) calculations in MadGraph5_aMC@NLO, allowing tree-level scattering amplitudes for multiple phase space points to be evaluated in each call to the integrated NLO differential cross section during event generation. Additionally, a multithreaded implementation based on this multi-event interface where tree-level amplitudes are evaluated in parallel across multiple CPU threads is presented for the Monte Carlo generation of quantum chromodynamical (QCD) events. Although this work primarily concerns the implemented code, some algorithmic changes involving the order of the application of phase-space cuts and calls to different scattering amplitudes are included. The codebase currently supports multi-threaded execution, but these changes pave the way for continued data parallelism in the form of on-CPU SIMD instructions or SIMT GPU offloading. A study in the runtime fraction spent in different diagrammatic contributions across various processes suggests that NLO QCD event generation are computationally dominated by tree-level scattering amplitude evaluations, which we show are perfectly suited for data parallelisation.

hep-ph↗

arXiv2025

Rapid event extraction and tensorial event adaption: Libraries for efficient access and generic reweighting of parton-level events and their implementation in the MadtRex module

We present Rex and teaRex, C++17 libraries for efficient management of parton-level hard scattering event information and completely generic reweighting of such events, respectively. Rex is primarily an interfacing and I/O library for Les Houches Event format files and provides an internal event format designed with data parallelism in mind, and teaRex extends this format to provide full parton-level reweighting functionality with minimal code needing to be written by the end user. These libraries serve as the foundation for the MadtRex reweighting module for MadGraph5_aMC@NLO, extending the functionality of the CUDACPP plugin to allow for data-parallel model-generic leading order parameter reweighting on SIMD-enabled CPUs and SIMT GPUs, speeding up reweighting by more than two orders of magnitude compared to MadGraph5_aMC@NLO running on the exact same hardware while providing trivial scalability to larger and distributed systems.

hep-ph↗

arXiv2025

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

The CUDACPP plugin for MadGraph5_aMC@NLO aims to accelerate leading order tree-level event generation by providing the MadEvent event generator with data-parallel helicity amplitudes. These amplitudes are written in templated C++ and CUDA, allowing them to be compiled for CPUs supporting SSE4, AVX2, and AVX-512 instruction sets as well as CUDA- and HIP-enabled GPUs. Using SIMD instruction sets, CUDACPP-generated amplitude routines routines are shown to speed up linearly with SIMD register size, and GPU offloading is shown to provide acceleration beyond that of SIMD instructions. Additionally, the resulting speed-up in event generation perfectly aligns with predictions from measured runtime fractions spent in amplitude routines, and proper GPU utilisation can speed up high-multiplicity QCD processes by an order of magnitude when compared to optimal CPU usage in server-grade CPUs.

hep-ph↗

arXiv2025

Madgraph on GPUs and vector CPUs: towards production (The 5-year journey to the first LO release CUDACPP v1.00.00)

The effort to speed up the Madgraph5_aMC@NLO generator by exploiting CPU vectorization and GPUs, which started at the beginning of 2020, has delivered the first production release of the code for leading-order (LO) processes in October 2024. To achieve this goal, many new features, tests and fixes have been implemented in recent months. This process benefitted also from the early feedback of the CMS experiment. In this contribution, we report on these activities and on the status of the LO software at the time of CHEP2024.

physics.comp-ph↗

arXiv2025

Hardware acceleration for next-to-leading order event generation within MadGraph5_aMC@NLO

As the quality of experimental measurements increases, so does the need for Monte Carlo-generated simulated events - both with respect to the total amount and to their precision. In perturbative methods, this involves the evaluation of higher order corrections to the leading order (LO) scattering amplitudes, including real emissions and loop corrections. Although experimental uncertainties today are larger than those of simulations, at the High Luminosity LHC experimental precision is expected to be above the theoretical one for events generated below next-to-leading order (NLO) precision. As forecasted hardware resources will not meet CPU requirements for these simulation needs, speeding up NLO event generation is a necessity. In recent years, collaborators across Europe and the United States have been working on CPU vectorisation of LO event generation within the MadGraph5_aMC@NLO framework, as well as porting it to GPUs, to major success. Recently, development has also started on vectorising NLO event generation. Due to the more complicated nature of NLO amplitudes this development faces several difficulties not accounted for in the LO development, but it shows promise. Here, we present these issues as well as the current status of our event-parallel NLO implementation.

hep-ph↗

arXiv2024

Simplifying QCD event generation with chirality flow, reference vectors and spin directions

The chirality-flow formalism, combined with good choices of gauge reference vectors, simplifies tree-level calculations to the extent that it is often possible to write down amplitudes corresponding to Feynman diagrams immediately. It has also proven to give a very sizable speedup in a proof of concept implementation of massless tree-level QED in MadGraph5_aMC@NLO. In the present paper we extend this analysis to QCD, including massive quarks. We define helicity-dependent versions of the gluon vertices, derive constraints on the spinor structure of propagating gluons, and explore the Schouten identity to simplify the four-gluon vertex further. For massive quarks, the chirality-flow formalism sheds light on how to exploit the freedom to measure spin along any direction to shorten the calculations. Overall, this results in a clear speedup for treating the Lorentz structure at high multiplicities.

hep-ph↗

arXiv2023

Acceleration beyond lowest order event generation: An outlook on further parallelism within MadGraph5_aMC@NLO

An important area of high energy physics studies at the Large Hadron Collider (LHC) currently concerns the need for more extensive and precise comparison data. Important tools in this realm are event reweighing and evaluation of more precise next-to-leading order (NLO) processes via Monte Carlo event generators, especially in the context of the upcoming High Luminosity LHC. Current event generators need to improve throughputs for these studies. MadGraph5_aMC@NLO (MG5aMC) is an event generator being used by LHC experiments which has been accelerated considerably with a port to GPU and vector CPU architectures, but as of yet only for leading order processes. In this contribution a prototype for event reweighing using the accelerated MG5aMC software, as well as plans for an NLO implementation, are presented.

physics.comp-ph↗

arXiv2023

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

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.

physics.comp-ph↗

arXiv2023

Madgraph5_aMC@NLO on GPUs and vector CPUs Experience with the first alpha release

Madgraph5_aMC@NLO is one of the most-frequently used Monte-Carlo event generators at the LHC, and an important consumer of compute resources. The software has been reengineered to maintain the overall look and feel of the user interface while speeding up event generation on CPUs and GPUs. The most computationally intensive part, the calculation of "matrix elements", is offloaded to new implementations optimised for GPUs and for CPU vector instructions, using event-level data parallelism. We present the work to support accelerated leading-order QCD processes, and discuss how this work is going to be released to Madgraph5_aMC@NLO's users.

physics.comp-ph↗

arXiv2022

Automating scattering amplitudes with chirality flow

Recently we introduced the chirality-flow formalism, a method which builds on the spinor-helicity formalism and is inspired by the color-flow idea in QCD. With this formalism, Feynman rules and diagrams are simplified to the extent that it is often possible to immediately, by hand, write down a helicity amplitude given a Feynman diagram. In this paper we show that the method can also speed up numerical evaluation of scattering amplitudes by considering $e^+ e^-$ going to $n$ photons in a MadGraph-based tree-level implementation. We find that the computation time is reduced by roughly a factor ten for six photons, and that it scales better with the number of external particles than the default MadGraph5_aMC@NLO implementation. This performance gain is in part attributed to the more compact Lorentz structures involved, and in part due to a transparent choice of gauge reference vectors which reduces the number of Feynman diagrams considered.

hep-ph↗