9 papers
A multi-event interface for next-to-leading order calculations in MadGraph5_aMC@NLO
Rikkert Frederix, Stefan Roiser, Robert Schöfbeck +2
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 ph…
Enabling Heterogeneous Performance Analysis for Scientific Workloads
Maksymilian Graczyk, Vincent Desbiolles, Stefan Roiser +1
Heterogeneous computing integrates diverse processing elements, such as CPUs, GPUs, and FPGAs, within a single system, aiming to leverage the strengths of each architecture to opti…
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
Stefan Roiser, Robert Schöfbeck, Zenny Wettersten
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, respectivel…
Recommendations for Best Practices for Data Preservation and Open Science in HEP
Simone Campana, Irakli Chakaberia, Gang Chen +33
These recommendations are the result of reflections by scientists and experts who are, or have been, involved in the preservation of high-energy physics data. The work has been don…
Data-parallel leading-order event generation in MadGraph5_aMC@NLO
Stephan Hageböck, Daniele Massaro, Olivier Mattelaer +3
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 amplitud…
Madgraph on GPUs and vector CPUs: towards production (The 5-year journey to the first LO release CUDACPP v1.00.00)
Andrea Valassi, Taylor Childers, Stephan Hageböck +7
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…